From alessandra.sciutti at gmail.com Sun Mar 1 12:32:28 2015 From: alessandra.sciutti at gmail.com (Alessandra Sciutti) Date: Sun, 1 Mar 2015 18:32:28 +0100 Subject: Connectionists: [meetings] Program HRI 2015 Workshop "Cognition: A Bridge between Robotics and Interaction" Message-ID: <000001d05445$b3fb93b0$1bf2bb10$@gmail.com> Dear all, If you happen to be at HRI 2015, please come and discuss with us the importance of Cognition, for robotics and social interaction. Below you can find the full program. ========================================================================= Workshop ?Cognition: A Bridge between Robotics and Interaction?, at HRI 2015, Portland (OR) USA ========================================================================= March 2, 2015 website: http://http://www.macs.hw.ac.uk/~kl360/HRI2015W/ ========================================================================= INVITED SPEAKERS: - Prof. David Vernon, Sk?vde University - Prof. Andrew Meltzoff, University of Washington - Prof. Greg Trafton, Navy Center For Applied Research in Artificial Intelligence - Prof. Ayse P. Saygin, University of California INVITED PANELISTS: - Prof. Giulio Sandini, Italian Institute of Technology - Prof. Minoru Asada, Osaka University A key feature of humans is the ability to anticipate what other agents are going to do and to plan accordingly a collaborative action. This skill, derived from being able to entertain models of other agents, allows for the compensation for intrinsic delays of human motor control and is a primary support to allow for efficient and fluid interaction. Moreover, the awareness that other humans are cognitive agents who combine sensory perception with internal models of the environment and others, enables easier mutual understanding and coordination. Cognition represents therefore an ideal link between different disciplines, as the field of Robotics and that of Interaction studies, performed by neuroscientists and psychologists. From a robotics perspective, the study of cognition is aimed at implementing cognitive architectures leading to efficient interaction with the environment and other agents. From the perspective of the human disciplines, robots could represent an ideal stimulus to study which are the fundamental robot properties necessary to make it perceived as a cognitive agent, enabling natural human-robot interaction. Ideally, the implementation of cognitive architectures may raise new interesting questions for psychologists, and the behavioral and neuroscientific results of the human-robot interaction studies could validate or give new inputs for robotics engineers. The aim of this workshop will be to provide a venue for researchers of different disciplines to discuss the possible points of contact and to highlight the issues and the advantages of bridging different fields for the study of cognition for interaction. This workshop will represent an ideal continuation of the discussion began at HRI 2014, in the workshop ?HRI: a bridge between Robotics and Neuroscience? (http://www.macs.hw.ac.uk/~kl360/HRI2014W/index.html ). LIST OF TOPICS ----------------- - Cognitive Architecture - Development of Social Cognition - Interaction - Prediction - Embodiment - Self and Other ========================================================================= FULL PROGRAM ========================================================================= 9:00 ? 9:05 Opening (A. Sciutti, K. Lohan and Y. Nagai) 9:05 ? 9:40 Invited talk - Greg Trafton 9:40 ? 10.00 Short talk - Embodiment is a Double-Edged Sword in Human-Robot Interaction: Ascribed vs. Intrinsic Intentionality Authors: Tom Ziemke, Serge Thill 10:00 ? 10:30 Coffee Break 10:30 ? 11:05 Invited talk - David Vernon 11:05 ? 11:25 Short talk - State Prediction for Development of Helping Behavior in Robots Authors: Jimmy Baraglia, Yukie Nagai and Minoru Asada 11:25 ? 11:45 Short talk - Social Robots and the Tree of Social Cognition Author: Bertram F. Malle 11:45 - 13:10 Break + Lunch (12:00 ? 13:00) 13:10 ? 13:45 Invited talk [3] Prof. Ayse P. Saygin 13:45 ? 14:05 Short talk [4] Predictive coding and the Uncanny Valley hypothesis: Evidence from electrical brain activity Authors: Burcu A. Urgen, Alvin X. Li, Chris Berka, Marta Kutas, Hiroshi Ishiguro and Ayse P. Saygin 14:05? 14:25 Short talk [5] The audio-motor feedback: a new rehabilitative aid for the developing blind child. Authors: Giulia Cappagli, Elena Cocchi, Sara Finocchietti, Monica Gori 14:25 ? 15:00 Invited talk [4] Prof. Andrew N. Meltzoff 15:00? 15:30 Coffee Break 15:30 ? 15:50 Short talk [6] Interaction as a bridge between cognition and robotics Authors: Serge Thill, Tom Ziemke 15:50 ? 16:50 Panel discussion 16:50 ? 17:00 Closing Remarks (A. Sciutti, K. Lohan and Y. Nagai) ORGANIZERS ---------- - Alessandra Sciutti Italian Institute of Technology - Katrin Solveig Lohan Heriot-Watt University - Yukie Nagai Osaka University From d.wojcik at nencki.gov.pl Mon Mar 2 10:35:29 2015 From: d.wojcik at nencki.gov.pl (=?UTF-8?B?RGFuaWVsIFfDs2pjaWs=?=) Date: Mon, 02 Mar 2015 16:35:29 +0100 Subject: Connectionists: INCF Nodes Workshop in Warsaw, April 16-17 Message-ID: <54F48341.808@nencki.gov.pl> Dear Colleagues, Each Spring, the International Neuroinformatics Coordinating Facility (INCF; http://www.incf.org), holds the INCF Nodes Workshop. This is the main event bringing representatives from each Node country together to present their activities, begin and continue collaborations, and inspire the future directions of INCF: http://incf.org/activities/workshops/node-workshops/node-workshops The next workshop will be organized by the Polish Node of INCF, and will spotlight Polish neuroinformatics research in areas from molecular neuroscience to brain-computer interfaces and supercomputing. It will be held at the Nencki Institute of Experimental Biology of the Polish Academy of Sciences (http://en.nencki.gov.pl/) in Warsaw, 16-17 April 2015, and will be the first Nodes Workshop open to the wider scientific community. Registration is free. Deadline for registration: * March 16* Workshop details: http://bit.ly/incf2015spring Looking forward to welcoming you in Warsaw, Daniel Wojcik On behalf of the Polish Node of INCF -- Daniel K. Wojcik, PhD, DSc Laboratory of Neuroinformatics, Head PhD Studies, Head Nencki Institute of Experimental Biology 3 Pasteur St, 02-093 Warsaw, Poland tel: (+48 22) 5892348 fax: (+48 22) 8225342 skype: danek8317 http://dwojcik.pl/ http://neuroinflab.wordpress.com/ http://orcid.org/0000-0003-0812-9872 -------------- next part -------------- An HTML attachment was scrubbed... URL: From andrea.huber at bcos.uni-freiburg.de Mon Mar 2 10:44:19 2015 From: andrea.huber at bcos.uni-freiburg.de (=?UTF-8?B?QW5kcmVhIEh1YmVyIEJyw7ZzYW1sZQ==?=) Date: Mon, 02 Mar 2015 16:44:19 +0100 Subject: Connectionists: =?utf-8?q?Community_Session_on_reproducibility_in?= =?utf-8?q?_the_neurosciences_-_11th_G=C3=B6ttingen_meeting_of_the_NWG?= Message-ID: <54F48553.9090609@bcos.uni-freiburg.de> ----------------------------------------------------------- Community Session Reproducibility in the neurosciences Novel tools and links to the Human Brain Project (HBP) platforms and the International Neuroinformatics Coordinating Facility (INCF) ----------------------------------------------------------- We invite you to attend a Community Session on Reproducibility in the neurosciences taking place during the 11th G?ttingen Meeting of the German Neuroscience Society. Date and Time: March 19th, 2015, 14:30-16:30h Location: University of G?ttingen, Main Lecture Building, Room 1.141 Snacks and beverages will be served Recently, experiments gathering neuronal data in behaving animals as well as the corresponding data analysis workflows have dramatically gained in complexity. At present, this creates a lack of reproducibility impairing the reliability and efficiency of research. In this community session, the status and approaches to address this challenge will be reviewed and discussed. *Speakers:* Sonja Gr?n (J?lich Researach Centre & RWTH Aachen) Thomas Wachtler (G-Node, LMU Munich) Jeff Muller (EPFL, Lausanne) We are looking forward to seeing you in G?ttingen. Community Session organizer: Sonja Gr?n (J?lich Researach Centre & RWTH Aachen) -------------- next part -------------- An HTML attachment was scrubbed... URL: From zeke.arneodo at gmail.com Mon Mar 2 12:28:55 2015 From: zeke.arneodo at gmail.com (Zeke Arneodo) Date: Mon, 2 Mar 2015 13:28:55 -0400 Subject: Connectionists: Symposium: Sense2Synapse 2015. Registration open. Message-ID: Sense2Synapse is a scientific event that takes place every year since 2012. It gathers researchers from the NY-NJ-Mass area that are working in sensory systems. This year, it will take place in New York University School of Medicine, next Saturday, April 11th from 9AM to 6PM. The list of keynote speakers is: Antony Movshon (NYU) Elena Gracheva (Yale) Robert Datta (Harvard) Martin Chalfie (Columbia) Registration and call for contributed talks and poster presentations is now open at www.sense2synapse.com. -------------- next part -------------- An HTML attachment was scrubbed... URL: From fjaekel at uos.de Tue Mar 3 05:51:27 2015 From: fjaekel at uos.de (=?iso-8859-1?Q?Frank_J=E4kel?=) Date: Tue, 3 Mar 2015 11:51:27 +0100 Subject: Connectionists: INCF Short Course on Information Processing in Neural Systems Message-ID: <08AC1A24-9F85-4BFE-A63E-B022FC82860C@uos.de> +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ INCF Short Course on Information Processing in Neural Systems -- From Single Neurons to Large-Scale Models of Cognition -- May 2-10, 2015 @ Institute of Cognitive Science, Osnabrueck, Germany +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ One of the big challenges in neuroinformatics is bridging the gap between our biophysical understanding of single cells and of networks of neurons on the one side, and the cognitive functions that are characterized in terms of information processing on the other side. This INCF Short Course will provide lectures and hands-on tutorials ranging from dynamical systems theory to cognitive modeling. Target Audience: PhD candidates and post-docs with backgrounds in neuroinformatics, theoretical neuroscience, complex systems, machine learning, applied mathematics/statistics or cognitive modeling. Topics: Dynamical systems: attractors, bifurcations, etc. (Herbert Jaeger) Single neuron dynamics, networks, and computation (Nicolas Brunel) Mean-field theory, neurodynamics, and decision-making (Gustavo Deco) Reservoir computing in simple cognitive systems (Gordon Pipa) Learning of sensory representations in neural systems (Peter K?nig) Distributed Adaptive Control (Paul Verschure) Neural networks, kernel methods, and categorization (Frank J?kel) A tutorial on reservoir computing (Pipa & Jaeger) A tutorial on large-scale simulations in Nengo (Terry Stewart) A tutorial on information processing models with NEST (Marc-Oliver Gewaltig) The yearly, two-day OCCAM workshop (www.occam-os.de) is integrated into the INCF course and participants of the INCF course will also take part in the workshop. Applications will be accepted until March 7, 2015. The registration fee is 250 Euros. We can offer a limited number of travel stipends to support students. More information on the course and on application details can be found on the course webpage: http://www.incf.ni.uos.de/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From fjaekel at uos.de Tue Mar 3 05:44:15 2015 From: fjaekel at uos.de (=?iso-8859-1?Q?Frank_J=E4kel?=) Date: Tue, 3 Mar 2015 11:44:15 +0100 Subject: Connectionists: Osnabrueck Computational Cognition Alliance Meeting (OCCAM 2015) Message-ID: <5F19B719-A7E1-41F9-9A71-ADC865AB6B38@uos.de> Dear Colleague, we would like to invite you to register for the 5th +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Osnabrueck Computational Cognition Alliance Meeting (OCCAM 2015) "From Simple Neurons to Large-Scale Models of Cognition" May 6-7, 2015. +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ List of invited speakers: Nicolas Brunel Gustavo Deco Wolfgang Einh?user Virginia Flanagin Sonja Gr?n Marc-Oliver Gewaltig Herbert Jaeger Gordon Pipa Paul Verschure Kai Vogeley The workshop will take place in Osnabrueck, Germany, and will be hosted by the Institute of Cognitive Science (University of Osnabrueck). Details can be found below and on the following webpage: http://www.occam-os.de The registration deadline is March 7, 2015 (first come first served). The registration fee is 100,- Euros. This year the OCCAM workshop is co-located with an INCF Short Course on the same topic (http://www.incf.ni.uos.de/). The OCCAM workshop series aims at understanding the principles of information processing in the brain with a particular focus on 3 major topics: 1. Neural coding and representation in hierarchical systems 2. Self-organization in dynamical systems 3. Mechanisms for probabilistic inference There will also be a poster session where conference participants will have the opportunity to present their work. The deadline for submitting an abstract for a poster presentation is also March 7. Best regards, Frank J?kel, Peter K?nig, Gordon Pipa (Organizing committee) -------------- next part -------------- An HTML attachment was scrubbed... URL: From simone.seeger at zi-mannheim.de Tue Mar 3 05:20:28 2015 From: simone.seeger at zi-mannheim.de (Seeger, Simone) Date: Tue, 3 Mar 2015 10:20:28 +0000 Subject: Connectionists: Reminder: Call for Workshops - Bernstein Conference 2015 Message-ID: <68B5BBF569FEF84891D3AAB4D3141E4561B520DB@ZIMAIL2.Zi.local> The National Bernstein Network Computational Neuroscience invites proposals for Satellite Workshops directly preceding the Bernstein Conference 2015 in Heidelberg ********************************************************************************** Call for Workshop proposals: Workshops: September 14, 2015 (Main Bernstein Conference: September 15-17, 2015) Deadline of proposal submission: March 15, 2015 Notification of acceptance: April 20, 2015 Conference Registration starts: April 27, 2015 Early Registration Deadline: July 21, 2015 ********************************************************************************** The Bernstein Conference started out as the annual meeting of the National Bernstein Network Computational Neuroscience and has become the largest single-track Computational Neuroscience conference in Europe in recent years. Since 2013, the Bernstein Conference hosts pre-conference workshops, which have developed swiftly into a well-attended event. They supply a stage to debate topical research questions and challenges in Computational Neuroscience and related fields, different points of view and scientific approaches in an informal setting. Workshops addressing controversial issues, open problems, and comparisons of competing approaches are encouraged. SCHEDULE: September 14, 2015, 9:00 - 18:30. You may apply for either half-day or full-day workshops. Workshop costs: The Bernstein Conference does not provide financial support, but workshop organizers and speakers are offered free workshop registration and reduced fees for the main conference. For further information about the conference, please visit the conference website. DETAILS FOR WORKSHOP PROPOSALS: The Workshop Proposal form can be downloaded here. Deadline for submission of Workshop Proposals: March 15, 2015 For more information or the submission of workshop proposals, please contact bc15 at uni-heidelberg.de We are looking forward to meeting you in Heidelberg! THE WORKSHOP PROGRAM COMMITTEE Matthias Bethge (Bernstein Center T?bingen) Upinder Bhalla (NCBS, Bangalore) Carlos Brody (Princeton University) Gustavo Deco (University Pompeu Fabra, Barcelona) Andreas Draguhn (Bernstein Center Heidelberg-Mannheim) Daniel Durstewitz (Bernstein Center Heidelberg-Mannheim) Gaute Einevoll (Norvegian University of Life Sciences, Aas) Andreas Herz (Bernstein Center Munich) Peter Kirsch (Bernstein Center Heidelberg-Mannheim) Sara Solla (Northwestern University, Evanston) *** Simone Seeger, M.A. Administration Bernstein Center for Computational Neuroscience Zentralinstitut f?r Seelische Gesundheit Postfach 12 21 20, 68072 Mannheim J5, 68159 Mannheim Telefon: 0621/1703-1326 oder 06221/54-8310 Fax: 0621/1703-2915 E-Mail: Simone.Seeger at zi-mannheim.de Internet: http://www.bccn-heidelberg-mannheim.de -------------- next part -------------- An HTML attachment was scrubbed... URL: From rjgsousa at gmail.com Tue Mar 3 04:53:00 2015 From: rjgsousa at gmail.com (Ricardo Gamelas Sousa) Date: Tue, 03 Mar 2015 09:53:00 +0000 Subject: Connectionists: (Firm Deadline: March, 9) VISUM Summer School :: Call for Participation Message-ID: <54F5847C.8020400@gmail.com> Apologies for cross-posting. In order to allow candidates to finish their application, we have decided to extend the deadline for visum 2015 applications. More information bellow. --- Call for Participation 3^rd VISion Understanding and Machine intelligence summer school, Porto, Portugal First Computer Vision Summer School with an industrial track 2-9 July, 2015 http://www.fe.up.pt/visum/|Facebook: http://goo.gl/FbVNtq Application Information: http://www.fe.up.pt/visum/visumschool *Important Dates* Application Deadline *March 9, 2015* Decision March 8, 2015 Early Registration April 10, 2015 Late Registration May 8, 2015 Summer School July 2-9, 2015 *Topics* Randomised Decision Forests and Tree-structured Algorithms in Computer Vision Tae-Kyun Kim, Imperial College London, UK Local Features Extraction and Description Jiri Matas, Czech Technical University, CZ Document Image Analysis Alicia Fornes, Universitat Aut?noma de Barcelona, ES Scene Understanding Martial Hebert, CMU, USA Automatic Facial Expression Recognition Michel Valstar, University of Nottingham, UK RGB-D Cameras Thomas Whelan, Imperial College London, UK *Applications* Point Clouds 3D* Jo?o P. Costeira, IST, PT ** *Tentative titles *Industry Track* http://asap54.com/ Daniel Heesch www.enermeter.pt/en Manuel Jo?o Ferreira www.philips.com Jacek Kustra *Venue* visum will take place in Porto, Portugal?s second-largest city, European Best Destination 2012 and Lonely Planet?s top 10 for 2013. Here, you can find famous baroque style monuments, the worldwide known Port Wine cellars, always having the World Heritage Douro River as the background of this youthful, active and charming city. visum?s program includes social activities. *Accommodation*** *Tattva Design Hostel* Students will have 10% of discount. The prices include: Buffet breakfast, Wi-Fi all over the building, 4 computers in Lounge area, free linen, free locks, free City Maps, free Luggage Storage, free Portuguese Lessons, free Walking Tours, Happy Hour (exclusive prices for TattvaBar for guests). *Hotel da M?sica* All accepted participants will have a special price included in visum?s fees. Hotel da M?sica is a luxurious 4-star property set in a prime location in the centre of Porto. Local tourist attractions such as Rotunda da Boavista, Casa da Musica and Hospital Militar are not far from the hotel. Hotel da M?sica is equipped with free wifi. For more details please follow the link: http://www.hoteldamusica.com/and do not forget to check the special conditions at http://www.fe.up.pt/visum/ Please visit our webpage for up to date information: http://www.fe.up.pt/visum/. We are looking forward for your participation! visum organising committee Tiago Esteves, INEB, Faculdade de Engenharia da Universidade do Porto Kelwin Fernandes, INESC TEC, Faculdade de Engenharia da Universidade do Porto Eduardo Marques, INESC TEC, Faculdade de Engenharia da Universidade do Porto Ana Rebelo, INESC TEC, Universidade do Porto Ricardo Sousa, INEB, Universidade do Porto Lu?s Teixeira, INESC TEC, Faculdade de Engenharia da Universidade do Porto Follow us on: Facebook: http://www.facebook.com/pages/visum/402527539813446 Google+: https://plus.google.com/104076275960053201744/posts Twitter: http://www.twitter.com/visumschool -------------- next part -------------- An HTML attachment was scrubbed... URL: From gabbiani at cns.bcm.edu Tue Mar 3 11:45:48 2015 From: gabbiani at cns.bcm.edu (Fabrizio Gabbiani) Date: Tue, 3 Mar 2015 16:45:48 +0000 Subject: Connectionists: postdoctoral position at Rice University/Baylor College of Medicine Message-ID: <54F5E53F.2000609@cns.bcm.edu> POSTDOCTORAL POSITION IN COMPUTATIONAL NEUROSCIENCE/BIOPHYSICAL MODELING Computational and Applied Mathematics Rice University and Department of Neuroscience Baylor College of Medicine Houston, Texas ----- A postdoctoral position in computational neuroscience is available at Rice University and Baylor College of Medicine, in the laboratories of Steven Cox (Rice University) and Fabrizio Gabbiani (Baylor College of Medicine). Our research focuses on understanding the biophysical mechanisms underlying the implementation of non-linear operations by neurons and neuronal circuits. The postdoctoral fellow will model the cellular and network mechanisms underlying collision avoidance behaviors using advanced mathematical techniques and computer simulations. Modeling will be supported by a large data set of experimental data gathered using electrophysiology, pharmacology, calcium imaging, high-speed video imaging and telemetry. We are looking for a highly motivated candidate with a strong background in computational modeling of single neurons and neuronal circuits. Experience with Matlab and NEURON is required. The position is available for one year, with possibility of renewal for a second year, contingent of performance and funding availability. Salary will be commensurate with level of experience, based on an NIH scale. Applications will be accepted until May 15, 2015. Our labs are located at Rice University and in the adjacent Texas Medical Center, close to many of Houston's cultural and outdoor amenities. For further information about Rice University, the Texas Medical Center and Houston please visit http://www.explore.rice.edu/explore/General_Information.asp or https://www.bcm.edu/about-us/life-in-houston For further informal inquiries and to apply, please send CV, the names and full contact information of two to three references, as well as one to two representative publications to cox at rice.edu and gabbiani at bcm.edu. -- Fabrizio Gabbiani phone: (713) 798 1849 Department of Neuroscience fax: (713) 798 3946 Baylor College of Medicine email: gabbiani at bcm.edu One Baylor Plaza, web: glab.bcm.tmc.edu Houston, TX 77030 mail stop: BCM295 From r.jolivet at ucl.ac.uk Tue Mar 3 14:43:40 2015 From: r.jolivet at ucl.ac.uk (Jolivet, Renaud) Date: Tue, 3 Mar 2015 19:43:40 +0000 Subject: Connectionists: Multi-timescale Modeling of Activity-Dependent Metabolic Coupling in the Neuron-Glia-Vasculature Ensemble Message-ID: Dear colleagues, You might be interested by our recent paper: "Multi-timescale Modeling of Activity-Dependent Metabolic Coupling in the Neuron-Glia-Vasculature Ensemble?, recently published in PLOS Computational Biology (http://dx.doi.org/10.1371/journal.pcbi.1004036). From the abstract: Glucose is the main energy substrate in the adult brain under normal conditions. Accumulating evidence, however, indicates that lactate produced in astrocytes (a type of glial cell) can also fuel neuronal activity. The quantitative aspects of this so-called astrocyte-neuron lactate shuttle (ANLS) are still debated. To address this question, we developed a detailed biophysical model of the brain?s metabolic interactions. Our model integrates three modeling approaches, the Buxton-Wang model of vascular dynamics, the Hodgkin-Huxley formulation of neuronal membrane excitability and a biophysical model of metabolic pathways. This approach provides a template for large-scale simulations of the neuron-glia-vasculature (NGV) ensemble, and for the first time integrates the respective timescales at which energy metabolism and neuronal excitability occur. The model is constrained by relative neuronal and astrocytic oxygen and glucose utilization, by the concentration of metabolites at rest and by the temporal dynamics of NADH upon activation. These constraints produced four observations. First, a transfer of lactate from astrocytes to neurons emerged in response to activity. Second, constrained by activity-dependent NADH transients, neuronal oxidative metabolism increased first upon activation with a subsequent delayed astrocytic glycolysis increase. Third, the model correctly predicted the dynamics of extracellular lactate and oxygen as observed in vivo in rats. Fourth, the model correctly predicted the temporal dynamics of tissue lactate, of tissue glucose and oxygen consumption, and of the BOLD signal as reported in human studies. These findings not only support the ANLS hypothesis but also provide a quantitative mathematical description of the metabolic activation in neurons and glial cells, as well as of the macroscopic measurements obtained during brain imaging. Best regards, Renaud -- Renaud Jolivet, PhD Neuroscience, Physiology & Pharmacology University College London r.jolivet at ucl.ac.uk https://sites.google.com/site/renaudjolivet/ +44 20 7679 3243 -------------- next part -------------- An HTML attachment was scrubbed... URL: From k.wong-lin at ulster.ac.uk Wed Mar 4 17:27:28 2015 From: k.wong-lin at ulster.ac.uk (Wong-Lin, Kongfatt) Date: Wed, 4 Mar 2015 22:27:28 +0000 Subject: Connectionists: Ph.D. Studentship at the University of Ulster - Data Analytics in Mental Health Message-ID: Applications are invited for the following DEL CAST studentship (Co-operative Awards in Science and Technology): Title: Extraction and modelling of mental health data: big data analytics approach With the increasing volume of datasets in neuroscience and mental health, data analytics and modelling will become indispensable. This project aims to use data analytics, probabilistic modelling, and high-performance computing to integrate and analyse available open but heterogeneous big data to extract patterns and predict Alzheimer?s disease. This timely, exciting and high-impact project is available in the University of Ulster? Computer Science Research Institute (in collaboration with Asystec Ltd) and is tenable in the Faculty of Computing and Engineering at the Magee Campus. The successful PhD candidate will join an externally funded multidisciplinary research team, and will benefit from the expertise of Ulster?s computational neuroscience and intelligence, and Asystec?s big data management and analytics. The student will also have the opportunity to interact with other biomedical and translational/clinical researchers in the team. The student will gain valuable knowledge in data analytics, high-performance computing, mathematics/statistics and brain sciences, which are all essential in many areas of science, engineering and biology. This training will provide wide opportunities for finding skilled work, especially in the burgeoning field of data analytics. The student will have the opportunity to learn first-hand about advanced software development, knowledge transfer and entrepreneurship with Asystec. Applicants should hold ordinary UK residence to be eligible for both fees and maintenance. Non UK residents who hold ordinary EU residence may also apply but if successful will receive fees only. All applicants should hold a first or upper second class honours (or equivalent) degree in Computer Science, Mathematics, Statistics, Engineering or a related discipline. Applicants must be highly motivated and willing to pursue research and develop skills across disciplines. Successful candidates will enrol on a full-time research programme, of up to three years subject to satisfactory progress, leading to the award of the degree of Doctor of Philosophy. The studentship will comprise tuition fees and a maintenance award (subject to UK residence status) of not less than ?15,057 per annum, funded by DEL (the Department for Employment & Learning in NI) and Asystec Ltd. The application process for the Ph.D. studentship is opened with a closing date for applications on the 30th April 2015, and interviews will be held in May 2015. The studentship is expected to start in September 2015. Further details can be found at: http://research.ulster.ac.uk/info/researchopp/DEL%20CAST%20Asystec.html If you wish to discuss your proposal or receive advice on the research project please contact: Dr KongFatt Wong-Lin, tel: +44 028 7167 5320, email: k.wong-lin at ulster.ac.uk ________________________________ This email and any attachments are confidential and intended solely for the use of the addressee and may contain information which is covered by legal, professional or other privilege. If you have received this email in error please notify the system manager at postmaster at ulster.ac.uk and delete this email immediately. Any views or opinions expressed are solely those of the author and do not necessarily represent those of Ulster University. The University's computer systems may be monitored and communications carried out on them may be recorded to secure the effective operation of the system and for other lawful purposes. Ulster University does not guarantee that this email or any attachments are free from viruses or 100% secure. Unless expressly stated in the body of a separate attachment, the text of email is not intended to form a binding contract. Correspondence to and from the University may be subject to requests for disclosure by 3rd parties under relevant legislation. The University of Ulster was founded by Royal Charter in 1984 and is registered with company number RC000726 and VAT registered number GB672390524.The primary contact address for Ulster University in Northern Ireland is Cromore Road, Coleraine, Co. Londonderry BT52 1SA -------------- next part -------------- An HTML attachment was scrubbed... URL: From lpulina at uniss.it Fri Mar 6 09:15:16 2015 From: lpulina at uniss.it (Luca Pulina) Date: Fri, 06 Mar 2015 15:15:16 +0100 Subject: Connectionists: CALL FOR APPLICATIONS -- The 11th Reasoning Web Summer School (RW 2015) Message-ID: <54F9B674.9080100@uniss.it> An HTML attachment was scrubbed... URL: From burbon000 at yahoo.com Thu Mar 5 20:10:58 2015 From: burbon000 at yahoo.com (Brian Urbon) Date: Fri, 6 Mar 2015 01:10:58 +0000 (UTC) Subject: Connectionists: Machine Vision and Big Data Analyst In-Reply-To: <7B23B9E42696184FA54979758B81966A0122DD368F@exch-mb-l4-01.campus.aston.ac.uk> References: <7B23B9E42696184FA54979758B81966A0122DD368F@exch-mb-l4-01.campus.aston.ac.uk> Message-ID: <2077143948.5505220.1425604258507.JavaMail.yahoo@mail.yahoo.com> unsubscribe On Monday, February 16, 2015 11:31 AM, "Nabney, Ian T" wrote: Aston University and Wheelright Ltd. This KTP project offers a fantastic opportunity for an ambitious PhD graduate to launch a career in industry with the support of company and academic mentors. There are over 5 billion pneumatic tyres within the global vehicle fleet. Their maintenance is critical to safety and fuel efficiency, yet drivers have to rely on manual inspection for tread depth and tyre condition; the simple gauge for pressure.? Automation is absent or limited to tyre pressure monitoring systems (TPMS). WheelRight's unique technology uses the vehicle's motion to capture data to measure tyre pressure, vehicle weight, tread depth and tyre condition.? No equipment is installed on the vehicle. Any vehicle, car, bus or truck can be driven through an installation at up to 15kmh. The data is collected and processed in seconds, identifying faults and automating a safety critical chore for motorists and fleet operators. The first systems are based in the UK but a trial system has been installed in the USA. The market opportunity is global; wherever vehicle tyres are ignored. Aston University has joined forces with WheelRight on this project with the aim of implementing machine-vision techniques to analyse tyre images, identify abnormal tyres and create a data warehouse of tyre information. Their goal is to make the process of tyre inspection, automatic, accurate and easy to use. We are looking for confident, credible and personable candidates with good inter-personal skills to work within WheelRight's small team and with its collaborators and clients. You should be a self-starter with the ability to show high levels of initiative and motivation and the ability to work autonomously to agreed targets and goals. You should be able to articulate ideas, effectively interpret user requirements and have good presentation skills with a strong problem-solving ability. You will need a PhD in a Science, Technology, Engineering or Mathematics based subject, involving both Mathematics and Computing.? You should have experience of some of the following: statistical data modelling or data mining; machine vision techniques; machine learning algorithms; neural networks. Experience of programming in an appropriate language (Matlab, R or C# preferred), and knowledge of how to write well-engineered code are essential to this role. It would also be advantageous to have experience in the presentation of complex analyses to untrained users, the Netlab toolbox for Matlab, knowledge of object-oriented design using C#, .NET or Java, along with an understanding of the full software development and product lifecycle.? Previous experience of data warehouses along with the ability to analyse data domains and create entity relationship diagrams and databases would be useful. As part of this project you will be able to develop your technical skills, including Bayesian methods of model combination, machine learning algorithms for image recognition and regression and software engineering skills (including data modelling of large-scale tasks and 'real world' architectural design of data warehouse). In addition to the KTP Associate Development Programme to develop your management skills, you will have a generous personal development budget for industry standard training, and will be encouraged to join and work towards Chartered status of an appropriate professional body such as the Institute of Mathematics and its Applications (IMA) or the British Computer Society. You will be employed by Aston University but will be based at the company, WheelRight Limited on Begbroke Science Park in Oxford. Deadline: 1st March 2015 Apply at http://jobs.aston.ac.uk reference 150032 Salary is ?26,000 to ?30,000 plus ?4000 individual training budget Contract is fixed term for 2 years == Prof Ian Nabney Head of Computer Science and Head of Mathematics School of Engineering and Applied Science Aston University http://www.aston.ac.uk/ncrg/ 0121 204 3645 -------------- next part -------------- An HTML attachment was scrubbed... URL: From pascal.fua at epfl.ch Fri Mar 6 10:51:38 2015 From: pascal.fua at epfl.ch (Pascal Fua) Date: Fri, 06 Mar 2015 16:51:38 +0100 Subject: Connectionists: Post-doctoral Position in Computer Vision at EPFL Message-ID: <54F9CD0A.3000406@epfl.ch> EPFL's Computer Vision Laboratory (http://cvlab.epfl.ch/) has an opening for a post-doctoral fellow in the field of Computer Vision and Augmented Reality. The position is initially offered for 1 year and can be extended for up to 4 years total. Description: The work will involve 3D tracking of a small robot on a tablet for Augmented Reality purposes and with a view to developing educational tools. Position: The Computer Vision Laboratory offers a creative international environment, a possibility to conduct competitive research on a global scale and involvement in teaching. There will be ample opportunities to cooperate with some of the best groups in Europe and elsewhere. EPFL is located next to Lake Geneva in a beautiful setting 60 kilometers away from the city of Geneva. Salaries are in the order CHF 80,000 per year, the precise amount to be determined by EPFL's department of human resources. Education: Applicants are expected to have finished, or be about to finish their Ph.D. degrees, to have a strong background in Computer Vision and 3D Tracking, and to have a track record of publications in top conferences and journals. Strong programming skills (C or C++) are a plus. French language skills are not required, English is mandatory. Application: Applications must be sent by email to Ms. Gisclon (josiane.gisclon at epfl.ch). They must contain a statement of interest, a CV, a list of publications, and the names of three references. From m.a.wiering at rug.nl Sat Mar 7 01:35:22 2015 From: m.a.wiering at rug.nl (Wiering, M.A.) Date: Sat, 7 Mar 2015 07:35:22 +0100 Subject: Connectionists: Software for deep support vector regression is now available Message-ID: Dear colleagues, The software for the deep SVM for regression problems is now available. It is implemented in Python and C++. The tar-file also contains a README file. If you have any further questions about the software, please contact me. See the following link to download the code: https://www.researchgate.net/publication/273132241_Software_for_deep_SVM_for_regression Kind regards, Marco Wiering, PhD Institute of Artificial Intelligence and Cognitive Engineering (ALICE) University of Groningen -------------- next part -------------- An HTML attachment was scrubbed... URL: From nicosia at dmi.unict.it Sat Mar 7 05:19:48 2015 From: nicosia at dmi.unict.it (Giuseppe Nicosia) Date: Sat, 7 Mar 2015 11:19:48 +0100 Subject: Connectionists: CfP: Synthetic & Systems Biology Summer School, Taormina - Italy July 5-9, 2015 - Application Deadline: March 31st Message-ID: <161B7FAF-FA8D-4E6F-B160-1C08AE7AD53E@dmi.unict.it> ______________________________________________________ Call for Participation (apologies for multiple copies) Please forward to anybody who might be interested. ______________________________________________________ Synthetic and Systems Biology Summer School - 2nd Edition Taormina - Sicily, Italy, July 5-9, 2015 http://www.taosciences.it/ssbss2015/ ssbss.school at gmail.com * News * New Speaker! Ron Weiss, MIT, USA ** Deadlines ** Student Application: March 31, 2015 Oral/Poster Submission: March 31, 2015 ** List of Speakers ** * Adam Arkin, University of California Berkeley, USA * Jef Boeke, New York University, USA * Angela DePace, Harvard University, USA * Forbes Dewey, MIT, USA * Karmella Haynes, Arizona State University, USA * Richard Kitney, Imperial College London, UK * Timothy Lu, MIT, USA * Philip Maini, Oxford University, UK * Giancarlo Mauri, University of Milano - Bicocca, Italy * Steve Oliver, Cambridge University, UK * Velia Siciliano, MIT, USA * Ron Weiss, MIT, USA * Nicola Zamboni, ETH, Switzerland ** Industrial Panel ** * Jon D. Chesnut, Life Sciences Solutions Group -Thermo Fisher Scientific, USA * Speaker TBA, Autodesk Inc., USA * Zach Serber, Zymergen, Inc. USA School Directors Jef D. Boeke, New York University, USA Giuseppe Nicosia, University of Catania, Italy Mario Pavone, University of Catania, Italy Giovanni Stracquadanio, University of Oxford, UK ** Short Talk and Poster Submission ** Students may submit a research abstract for presentation. School directors will review the abstracts and will recommend for poster or short-oral presentation. Abstract should be submitted by March 31, 2015. The abstracts will be published on the electronic hands-out material of the summer school. http://www.taosciences.it/ssbss2015/index.html#applicationForm http://www.taosciences.it/ssbss2015/ ssbss.school at gmail.com -- Giuseppe Nicosia, Ph.D. Associate Professor of Computer Engineering Dept of Mathematics & Computer Science University of Catania Viale A. Doria, 6 - 95125 Catania, Italy P +39 095 7383048 nicosia at dmi.unict.it http://www.dmi.unict.it/nicosia ============================================================= International Synthetic & Systems Biology Summer School - SSBSS 2015 * Biology meets Computer Science & Engineering * July 5-9, 2015 - Taormina, Italy http://www.taosciences.it/ssbss2015/ ============================================================= International Workshop on Machine learning, Optimization and big Data - MOD 2015 July 21-24, 2015 - Taormina, Italy http://www.taosciences.it/mod-2015/ ============================================================= -------------- next part -------------- An HTML attachment was scrubbed... URL: From ahu at cs.stir.ac.uk Sun Mar 8 07:34:51 2015 From: ahu at cs.stir.ac.uk (Dr Amir Hussain) Date: Sun, 8 Mar 2015 11:34:51 +0000 Subject: Connectionists: Increased Impact Factor, Number of Issues & Table of Contents Alert: Cognitive Computation journal (Springer): Vol.7, No.1 / Feb 2015 Issue Message-ID: Dear Colleagues: (with advance apologies for any cross-postings) We are delighted to announce the publication of Volume 7, No.1 / Feb 2015 Issue, of Springer's Cognitive Computation journal - www.springer.com/12559 ================================================================ Important News: Increased Impact Factor & Six bi-monthly Journal Issues from 2015! ================================================================ As you will know, Cognitive Computation was selected for coverage in Thomson Reuter?s products and services in 2011. Beginning with V.1 (1) 2009, this publication is now indexed and abstracted in: ? Science Citation Index Expanded (also known as SciSearch?) ? Journal Citation Reports/Science Edition ? Current Contents?/Engineering Computing and Technology ? Neuroscience Citation Index? Cognitive Computation received its first Impact Factor (IF) of 1.0 in 2011. The IF for 2013/2014 increased to 1.1 (with a first 5 year IF of 1.387) (Thomson Reuters Journal Citation Reports? 2013) Many congratulations to the editors, reviewers and authors of this exciting young journal! Want to be part of the growing success? Visit the journal homepage ( http://springer.com/12559) for instructions on submitting your research. ================================= Quarterly to Bi-monthly Issues, from 2015!! ================================= Due to continuously growing number of high quality submissions, the number of Issues has increased from four (quarterly Issues) to six (bi-monthly Issues) each year, starting Feb 2015! ======================================== The first six papers of the February 2015 Issue comprise a Special Issue on "Neural Signal Processing", Guest Edited by: Jordi Sole?-Casals, Francois-Benoit Vialatte, Justin Dauwels. The Guest Editorial titled: "Alternative Techniques of Neural Signal Processing in Neuroengineering" is available (for free download) here: http://link.springer.com/article/10.1007/s12559-015-9317-0 The 6 Special Issue papers are followed by 8 regular papers. The full listing of 14 published articles (Table of Contents) for this inaugural 2015 Issue can be viewed here (and also at the end of this message, followed by an overview of the previous Issues/Archive listings): http://link.springer.com/journal/12559/7/1/ You may also be interested in the last Special Issue of 2014 (Vol. 6, No.4 / Dec 2014) on "Modeling emotion, behaviour and context in socially believable robots and ICT interfaces", Guest Edited by: Anna Esposito, Leopoldina Fortunati, and Giuseppe Lugano. The Guest Editorial is available (for free download) here: http://link.springer.com/article/10.1007/s12559-014-9309-5 and the full listing of 24 articles can be found here: http://link.springer.com/journal/12559/6/4/page/1 This exciting Special Issue was the outcome of a strategic trans-disciplinary Workshop organized by EU COST (http://www.cost.eu/), on ??The future concept and reality of social robotics: challenges, perception and applications. Role of social robotics in current and future society,?? held in Brussels (Belgium). A list of the journal's most downloaded articles (which can always be read for FREE) can be found here: http://www.springer.com/biomed/neuroscience/journal/12559?hideChart=1#realtime Other 'Online First' published articles not yet in a print issue can be viewed here: http://www.springerlink.com/content/121361/?Content+Status=Accepted All previous Volumes and Issues of the journal can be viewed here: http://link.springer.com/journal/volumesAndIssues/12559 ============================================ Reminder: Cognitive Computation "LinkedIn" Group: ============================================ To further strengthen the bonds amongst the interdisciplinary audience of Cognitive Computation, we have set-up a "Cognitive Computation LinkedIn group", which has nearly 800 members already! We warmly invite you to join us at: http://www.linkedin.com/groups?gid=3155048 For further information on the journal and to sign up for electronic "Table of Contents alerts" please visit the Cognitive Computation homepage: http://www.springer.com/12559 or follow us on Twitter at: http://twitter.com/CognComput for the latest On-line First Issues. For any questions with regards to LinkedIn and/or Twitter, please contact Springer's Publishing Editor: Marleen Moore: Marleen.Moore at springer.com Finally, we would like to invite you to submit short or regular papers describing original research or timely review of important areas - our aim is to peer review all papers within approximately six-eight weeks of receipt. We also welcome relevant high quality proposals for Special Issues - four are already planned for 2015-16 (for CFPs, see: http://www.springer.com/biomed/neuroscience/journal/12559?detailsPage=press ) With our very best wishes to all aspiring readers and authors of Cognitive Computation, Professor Amir Hussain, PhD (Editor-in-Chief: Cognitive Computation) E-mail: ahu at cs.stir.ac.uk (University of Stirling, Scotland, UK) Professor Igor Aleksander, PhD (Honorary Editor-in-Chief: Cognitive Computation) (Imperial College, London, UK) http://www.springer.com/12559 Also consider your work for related Book Series: SpringerBriefs on Cognitive Computation: http://www.springer.com/series/10374 NEW: Springer Series on Socio-Affective Computing: http://www.springer.com/series/13199 ------------------------------------------------------------------------------------------------- ???????????Table of Contents Alert -- Cognitive Computation Vol 7 No 1, Feb 2015 -------------------------------------------------------------------------------------------------- Special Issue on "Neural Signal Processing" Issue Editors: Jordi Sole?-Casals, Francois-Benoit Vialatte, Justin Dauwels -------------------------------------------------------------------------------------------------- Alternative Techniques of Neural Signal Processing in Neuroengineering Jordi Sol?-Casals , Fran?ois-Beno?t Vialatte and Justin Dauwels http://link.springer.com/article/10.1007/s12559-015-9317-0/fulltext.html Multivariate Synchronization Analysis of Brain Electroencephalography Signals: A Review of Two Methods Mahdi Jalili http://link.springer.com/article/10.1007/s12559-013-9213-4 EEG Correlates of Voice and Face Emotional Judgments in the Human Brain K. Hiyoshi-Taniguchi, M. Kawasaki, T. Yokota, H. Bakardjian, H. Fukuyama, A. Cichocki and F. B. Vialatte http://link.springer.com/article/10.1007/s12559-013-9225-0/fulltext.html Biologically Motivated Model for Outdoor Scene Classification Jingjing Zhao, Chun Du, Hao Sun, Xingtong Liu, Jixiang Sun http://link.springer.com/article/10.1007/s12559-013-9227-y Brain Evoked Potential Latencies Optimization for Spatial Auditory Brain?Computer Interface Zhenyu Cai, Shoji Makino, Tomasz M. Rutkowski http://link.springer.com/article/10.1007/s12559-013-9228-x On Automatic Diagnosis of Alzheimer?s Disease Based on Spontaneous Speech Analysis and Emotional Temperature K. L?pez-de-Ipi?a, J. B. Alonso, J. Sol?-Casals, N. Barroso, P. Henriquez, M. Faundez-Zanuy, C. M. Travieso, M. Ecay-Torres, P. Mart?nez-Lage, H. Eguiraun http://link.springer.com/article/10.1007/s12559-013-9229-9 Embedded Implementation of Second-Order Blind Identification (SOBI) for Real-Time Applications in Neuroscience Xun Zhang, Fran?ois-Beno?t Vialatte, Chen Chen, Apurva Rathi, G?rard Dreyfus http://link.springer.com/article/10.1007/s12559-014-9282-z -------REGULAR PAPERS------------------------ Model of the Reticular Formation of the Brainstem Based on Glial?Neuronal Interactions Bernhard J. Mitterauer http://link.springer.com/article/10.1007/s12559-014-9260-5 A Kernel Clustering-Based Possibilistic Fuzzy Extreme Learning Machine for Class Imbalance Learning Shi-Xiong Xia, Fan-Rong Meng, Bing Liu, Yong Zhou http://link.springer.com/article/10.1007/s12559-014-9256-1 Improved Jacobian Eigen-Analysis Scheme for Accelerating Learning in Feedforward Neural Networks N. Ampazis, S. J. Perantonis, D. Drivaliaris http://link.springer.com/article/10.1007/s12559-014-9263-2 A Cognitive Ensemble of Extreme Learning Machines for Steganalysis Based on Risk-Sensitive Hinge Loss Function Vasily Sachnev, Savitha Ramasamy,Suresh Sundaram, Hyoung Joong Kim, Hee Joon Hwang http://link.springer.com/article/10.1007/s12559-014-9268-x Agent-Based Modeling of Emotion Contagion in Groups Tibor Bosse, Rob Duell, Zulfiqar A. Memon, Jan Treur, C. Natalie van der Wal http://link.springer.com/article/10.1007/s12559-014-9277-9 Robust and Sparse Linear Programming Twin Support Vector Machines M. Tanveer http://link.springer.com/article/10.1007/s12559-014-9278-8 Classification of Uncertain Data Streams Based on Extreme Learning Machine Keyan Cao, Guoren Wang, Donghong Han, Jingwei Ning, Xin Zhang http://link.springer.com/article/10.1007/s12559-014-9279-7 A Cognitively Inspired Approach to Two-Way Cluster Extraction from One-Way Clustered Data Ahsan Abdullah, Amir Hussain http://link.springer.com/article/10.1007/s12559-014-9281-0 --------------------------------------------------------- Previous Issues/Archive: Overview: --------------------------------------------------------- All previous Volumes and Issues can be viewed here: http://link.springer.com/journal/volumesAndIssues/12559 Alternatively, the full listing of the Inaugural Vol. 1, No. 1 / March 2009, can be viewed here (which included invited authoritative reviews by leading researchers in their areas - including keynote papers from London University's John Taylor, Igor Aleksander and Stanford University's James McClelland, and invited papers from Ron Sun, Pentti Haikonen, Geoff Underwood, Kevin Gurney, Claudius Gross, Anil Seth and Tom Ziemke): http://www.springerlink.com/content/1866-9956/1/1/ The full listing of Vol. 1, No. 2 / June 2009, can be viewed here (which included invited reviews and original research contributions from leading researchers, including Rodney Douglas, Giacomo Indiveri, Jurgen Schmidhuber, Thomas Wennekers, Pentti Kanerva and Friedemann Pulvermuller): http://www.springerlink.com/content/1866-9956/1/2/ The full listing of Vol.1, No. 3 / Sep 2009, can be viewed here: http://www.springerlink.com/content/1866-9956/1/3/ The full listing of Vol. 1, No. 4 / Dec 2009, can be viewed here: http://www.springerlink.com/content/1866-9956/1/4/ The full listing of Vol.2, No. 1 / March 2010, can be viewed here: http://www.springerlink.com/content/1866-9956/2/1/ The full listing of Vol.2, No. 2 / June 2010, can be viewed here: http://www.springerlink.com/content/1866-9956/2/2/ The full listing of Vol.2, No. 3 / Aug 2010, can be viewed here: http://www.springerlink.com/content/1866-9956/2/3/ The full listing of Vol.2, No. 4 / Dec 2010, can be viewed here: http://www.springerlink.com/content/1866-9956/2/4/ The full listing of Vol.3, No.1 / Mar 2011 (Special Issue on: Saliency, Attention, Active Visual Search and Picture Scanning, edited by John Taylor and Vassilis Cutsuridis), can be viewed here: http://www.springerlink.com/content/1866-9956/3/1/ The Guest Editorial can be viewed here: http://www.springerlink.com/content/hu2245056415633l/ The full listing of Vol.3, No.2 / June 2011 can be viewed here: http://www.springerlink.com/content/1866-9956/3/2/ The full listing of Vol. 3, No. 3 / Sep 2011 (Special Issue on: Cognitive Behavioural Systems, Guest Edited by: Anna Esposito, Alessandro Vinciarelli, Simon Haykin, Amir Hussain and Marcos Faundez-Zanuy), can be viewed here: http://www.springerlink.com/content/1866-9956/3/3/ The Guest Editorial for the special issue can be viewed here: http://www.springerlink.com/content/h4718567520t2h84/ The full listing of Vol. 3, No. 4 / Dec 2011 can be viewed here: http://www.springerlink.com/content/1866-9956/3/4/ The full listing of Vol. 4, No.1 / Mar 2012 can be viewed here: http://www.springerlink.com/content/1866-9956/4/1/ The full listing of Vol. 4, No.2 / June 2012 can be viewed here: http://www.springerlink.com/content/1866-9956/4/2/ The full listing of Vol. 4, No.3 / Sep 2012 (Special Issue on: Computational Creativity, Intelligence and Autonomy, Edited by: J. Mark Bishop and Yasemin J. Erden) can be viewed here: http://www.springerlink.com/content/1866-9956/4/3/ The full listing of Vol. 4, No.4 / Dec 2012 (Special Issue titled: "Cognitive & Emotional Information Processing", Edited by: Stefano Squartini, Bj?rn Schuller and Amir Hussain, which is followed by a number of regular papers), can be viewed here: http://link.springer.com/journal/12559/4/4/page/1 The full listing of Vol. 5, No.1 / March 2013 Special Issue titled: Computational Intelligence and Applications Guest Editors: Zhigang Zeng & Haibo He, which is followed by a number of regular papers), can be viewed here: http://link.springer.com/journal/12559/5/1/page/1 The full listing of Vol. 5, No.2 / June 2013 Special Issue titled: Advances on Brain Inspired Computing, Guest Editors: Stefano Squartini, Sanqing Hu & Qingshan Liu, which is followed by a number of regular papers), can be viewed here: http://link.springer.com/journal/12559/5/2/page/1 The full listing of Vol. 5, No.3 / Sep 2013 Special Issue titled: In Memory of John G Taylor: A Polymath Scholar, Guest Editors: Vassilis Cutsuridis & Amir Hussain, which is followed by a number of regular papers), can be viewed here: http://link.springer.com/journal/12559/5/3/page/1 The full listing of Vol. 5, No.4 / Dec 2013, which includes regular papers (including an invited paper by Professor Ron Sun, Rensselaer Polytechnic Institute, USA, titled: Moral Judgment, Human Motivation, and Neural Networks), and a Special Issue titled: Advanced Cognitive Systems Based on Nonlinear Analysis. Guest Editors: Carlos M. Travieso and Jes?s B. Alonso, can be viewed here: http://link.springer.com/journal/12559/5/4/page/1 The full listing of Vol. 6, No.1 / Mar 2014, can be viewed here: http://link.springer.com/journal/12559/6/1/page/1 The full listing of Vol. 6, No.2 / June 2014, can be viewed here: http://link.springer.com/journal/12559/6/2/page/1 The full listing of Vol. 6, No.3 / Sep 2014, can be viewed here: http://link.springer.com/journal/12559/6/3/page/1 The full listing of Vol. 6, No.4 / Dec 2014 (Special Issue on Modeling emotion, behaviour and context in socially believable robots and ICT interfaces, Guest Editors: Anna Esposito, Leopoldina Fortunati, and Giuseppe Lugano) can be viewed here: http://link.springer.com/journal/12559/6/4/page/1 -- The University of Stirling has been ranked in the top 12 of UK universities for graduate employment*. 94% of our 2012 graduates were in work and/or further study within six months of graduation. *The Telegraph The University of Stirling is a charity registered in Scotland, number SC 011159. -------------- next part -------------- An HTML attachment was scrubbed... URL: From sabu.thampi at iiitmk.ac.in Fri Mar 6 23:21:26 2015 From: sabu.thampi at iiitmk.ac.in (Dr. Sabu M. Thampi) Date: Sat, 7 Mar 2015 09:51:26 +0530 Subject: Connectionists: cfp - International Workshop on Metaheuristic Techniques and Applications (MTA'15) Message-ID: Apologies for cross-postings! International Workshop on Metaheuristic Techniques and Applications (MTA'15) http://icacci-conference.org/ista2015/mta2015.html Co-located with International Symposium on Intelligent Systems Technologies and Applications (ISTA?15) August 10-13, 2015, Kochi, India -------------------------------------------------------------------------------------- Optimization is essentially everywhere, from engineering design to economics and from holiday planning to Internet routing. These problems are often so complex that finding the best solution becomes computationally infeasible. Several metaheuristic algorithms have been proposed to serve as solutions to these problems. They are stochastic in nature and inspired by nature?s way of finding best solution. Quality solutions to difficult optimization problems can be found in a reasonable amount of time. New variants of metaheuristic algorithms are continually being proposed and are being deployed in many real life engineering problems. The International Workshop on Metaheuristic Techniques and Applications (MTA'15) will provide a forum for scientists and researchers to present their latest results and a means to discuss the recent developments in metaheuristics and their applications. We welcome submissions of original and unpublished work in all related areas, including (but not limited to) the following: Metaheuristics Techniques -------------------------- Stochastic Search Firefly Algorithm Cuckoo Search Swarm Intelligence Intelligent Water Drops Algorithm Bacterial Foraging Algorithm Harmony Search Bat Algorithm Photosynthetic and Enzyme Algorithm Genetic Programming Iterated Local Search Ant Colony Optimization Simulated Annealing Tabu Search Hybridization of Metaheuristics Parallelization Memetic Algorithms Greedy Randomized Adaptive Search Procedure Variable Neighborhood Search & Scatter Search Guided Local Search & Fast Local Search Cellular Automata & Artificial Immune Systems Metaheuristics' Applications ------------------------------- Traveling Salesman Problem Maximum Clique Problem Flow Shop Scheduling Problem P-Median Problem Feature Selection Automatic Clustering Neural Network Training Robotics DNA Sequencing Coverage in Wireless Sensor Networks Design Patterns All accepted papers will be published as a special volume in the prestigious Advances in Intelligent Systems and Computing(Springer) Series. All accepted papers will also be archived in the SpringerLink digital Library. Important Dates ---------------- Paper Submission: March 31, 2015 Author Notification: May 10, 2015 Camera-Ready Copy: June 2, 2015 -------------- next part -------------- An HTML attachment was scrubbed... URL: From tbesold at uni-osnabrueck.de Sat Mar 7 07:47:49 2015 From: tbesold at uni-osnabrueck.de (Tarek R. Besold) Date: Sat, 7 Mar 2015 13:47:49 +0100 Subject: Connectionists: Final CfP: JAGI Special Issue on "Computational Creativity, Concept Invention, and General Intelligence" (Deadline: April 5, 2015) Message-ID: <1CE401E6-6EF2-453B-A6D2-1ABE576DB461@uni-osnabrueck.de> **** Apologies for multiple-postings **** Call for Papers: Journal Special Issue on == Computational Creativity, Concept Invention, and General Intelligence == Tarek R. Besold, Kai-Uwe K?hnberger, Tony Veale Special issue of the Journal of Artificial General Intelligence Published by De Gruyter http://www.degruyter.com/view/j/jagi = SCOPE = The targeted authors invited for submission to the special issue are researchers associated with the fields working in the development of computational models for creativity, concept formation, concept discovery, idea generation, and their overall relation and role to general intelligence. Furthermore, researchers coming from application areas, like computer-aided innovation (CAI) are welcome to submit papers for this volume. We invite papers that make a scientific contribution to the fields of computational creativity and, idea generation and/orin the context of artificial general intelligence, with possible topics ranging from theoretical studies of human creativity, inventive capacities and intelligence (that in some way propose a computational model for the respective capability), through more practical contributions reporting on creative, inventive or generally intelligent computer systems (we particularly welcome implementations offering general or at least multiple sorts of results) and studies of systems and software supporting and/or guiding humans in the creative or inventive act, to application-based reports from fields like design, architecture or arts. Submissions connecting to several of the aforementioned topics are highly encouraged and welcome. Due to the open nature of the targeted topics, we hope for contributions from a broad variety of subdisciplines within AI and Computational Creativity Research. = TOPICS = We particularly encourage submissions related to the following non-exhaustive list of topics: - Computational Creativity & Creativity-Support Tools - Analogical Reasoning - Artificial General Intelligence - Automated Story Generation - Computer-Aided & Automated Mathematics - Computer-Aided Innovation - Computational Models for Conceptual Blending - Automated Poetry Generation - Automated Music Generation/Automated Composition - Automated Art Generation - Creativity in Problem Solving Preference is given to contributions specifically addressing aspects related to and/or inspired by human creativity and offering a cognitively-inspired theory, model, or implementation thereof (such as, e.g., computational accounts of creative problem-solving, creative language production, concept blending, etc.). Authors are encouraged to address the problems of modeling intelligence and creativity generally, and not to focus exclusively on specific domains or problems. While papers will likely focus on a given domain or problem, general insights into general intelligence should also be drawn. = SUBMISSIONS = Deadline for submissions is *** April 05, 2015 ***. Details concerning the submission process, accepted paper formats, and an author's kit are available from http://jagi.mindmakers.org/index.php/jagi/about/submissions#onlineSubmissions. The journal in general accepts research articles, surveys, reviews, technical notes, and position statements. The submission must be original and unpublished, and not under review in another journal. Published conference or workshop papers can be submitted to the journal after substantial extension and enhancement. All submissions must be in English. Contributions shall be submitted via the journal's submission system which can be found under http://jagi.mindmakers.org/index.php/jagi/about/submissions#onlineSubmissions and in addition shall be sent by email as .pdf to Tarek R. Besold, tbesold at uni-osnabrueck.de. When submitting their papers online, authors are asked to explicitly indicate that the submission belongs to the special issue by choosing the corresponding section. When resubmitting substantially extended and enhanced versions of workshop or journal papers, authors are asked to shortly indicate the extensions/enhancements over the previous version in an accompanying letter also indicating a reference to the original publication. = IMPORTANT DATES = Deadline for submissions: April 05, 2015 Feedback to authors: May 31, 2015 Submission of revised versions: June 21, 2015 Final notification of acceptance/rejection: July 12, 2015 Publication of the special issue: Summer/autumn 2015 = GUEST EDITORS = Tarek R. Besold, Institute of Cognitive Science, University of Osnabr?ck, Germany Kai-Uwe K?hnberger, Institute of Cognitive Science, University of Osnabr?ck, Germany Tony Veale, UCD School of Computer Science and Informatics, University College Dublin, Ireland ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Tarek R. Besold Institute of Cognitive Science University of Osnabr?ck (Germany) tbesold at uni-osnabrueck.de -------------- next part -------------- An HTML attachment was scrubbed... URL: From Vittorio.Murino at iit.it Sun Mar 8 10:01:07 2015 From: Vittorio.Murino at iit.it (Vittorio Murino) Date: Sun, 08 Mar 2015 15:01:07 +0100 Subject: Connectionists: [GROW 2015 @ CVPR] Call for Papers - EXTENDED DEADLINE: MARCH 17, 2015 Message-ID: <54FC5623.30700@iit.it> We apologize if you receive multiple copies of this message. ************************************************************************ GROW 2015 First International Workshop on GRoup and crOWd behavior analysis and understanding http://qil.uh.edu/grow2015/ June 11, 2015, Boston, MA, United States in association with CVPR 2015 ************************************************************************ >> PAPER submission (EXTENDED!!!): March 17, 2015 << ************************************************************************ CALL FOR PAPERS After years of research on the analysis of individuals by automatic methods, the computer vision community has transferred its attention on the new issue of modeling gatherings of people, commonly referred as groups or crowds, depending on the number of people involved. The aim of GROW 2015 is to bring together a wide range of researchers in computer vision and machine learning from one side, and applied social sciences on the other, to share innovative ideas and solutions for exploiting the potential synergies emerging from the integration of the two domains, for a range of different applications. For this reason, the invited speakers of the workshop will come from the computer science and from the social science domains, promoting an intriguing cross-fertilization among the two areas. SCOPE To address these challenges, contributions are particularly welcome in the following areas: * Group/crowd detection * Group/crowd tracking * Tracking in the crowd * Group/crowd modeling from a drone * Egovision for group/crowd modeling * Group/crowd behavior understanding and activity recognition * Crowd counting * Group profiling * Information fusion for crowd modeling * F-formation/free conversational groups recognition * Jointly focused/commonly focused gathering recognition * Causal, spectator, protest crowd recognition and modeling * Abnormality detection in a group/crowd * Group detection in a crowd * Crowd forecasting * Metrics for group and crowd modeling * Video surveillance and sensor networks * (Collective) Head orientation, gesture recognition in groups and crowd * Groups and crowds datasets INVITED SPEAKERS * Chiara Bassetti, Italy * Shaogang Gong, UK * Clark McPhail, USA * Greg Mori, USA IMPORTANT DATES: Full Papers submission(EXTENDED!): Tuesday, 17th March 2015 Notification to authors: Friday, 17th April 2015 Submission Camera Ready: Monday, 27th April 2015 Workshop: Thursday, 11th June 2015 WORKSHOP CO-CHAIRS: Vittorio Murino, Istituto Italiano di Tecnologia, IT Marco Cristani, University of Verona, IT Shishir Shah, University of Houston, US Silvio Savarese, Stanford University, US WEB CHAIR: LorisBazzani - The Dartmouth College, US PROGRAM COMMITTEE: LorisBazzani - The Dartmouth College, US Alexandre Bernardino - Instituto Superior Tecnico, PT Francois Bremond ??? Inria, FR Wolfram Burgard - University of Freiburg, DE Simone Calderara - Universit? di Modena e Reggio Emilia, IT Andrea Cavallaro - Queen Mary University of London, UK Rama Chellappa - University of Maryland, College Park, US Rita Cucchiara - Universit? di Modena e Reggio Emilia, US Gianfranco Doretto - West Virginia University, US Rogerio Feris - IBM T.J. Watson Research Center, US Andrea Fossati - ETHZ, CH Shaogang Gong - Queen Mary University of London, UK Hayley Hung - Technical University of Delft, NL Frederic Jurie - Universit?? de Caen, FR Xuelong Li - Chinese Academy of Sciences, CN Jean-Marc Odobez - IDIAP, CH Federico Pernici - University of Florence, IT Gerhard Rigoll - TUM, DE Neil Robertson - Heriot-Watt University, UK Amit K. Roy Chowdhury - University of California, Riverside, US Nicu Sebe - University of Trento, IT Lauro Snidaro - University of Udine, IT Stefano Tubaro - Politecnico di Milano, IT Sergio Velastin - Universidad de Santiago de Chile, CL Ramesh Visvanathan - Frankfurt Institute of Advanced Studies, DE Xiaogang Wang - The Chinese University of Hong Kong, HK Tony Xiang - Queen Mary University of London, UK Ming-Hsuan Yang - University of California at Merced, US Wei-Shi Zheng - Sun Yat-sen University, CN SPECIAL ISSUE: An Elsevier book containing the extended versions of a selected number of GROW papers is going to be organized Further Details: Please look at the GROW 2015 website: http://qil.uh.edu/grow2015/ ----------------------------------------------------------------------------------------------- -- Vittorio Murino ******************************************* Prof. Vittorio Murino, Ph.D. Director PAVIS - Pattern Analysis & Computer Vision IIT Istituto Italiano di Tecnologia Via Morego 30 16163 Genova, Italy Phone: +39 010 71781 504 Mobile: +39 329 6508554 Fax: +39 010 71781 236 E-mail:vittorio.murino at iit.it Secretary: Sara Curreli email: sara.curreli at iit.it Phone: +39 010 71781 917 http://www.iit.it/pavis ******************************************** -------------- next part -------------- An HTML attachment was scrubbed... URL: From fjaekel at uos.de Mon Mar 9 12:32:18 2015 From: fjaekel at uos.de (=?iso-8859-1?Q?Frank_J=E4kel?=) Date: Mon, 9 Mar 2015 17:32:18 +0100 Subject: Connectionists: OCCAM 2015 Deadline Extension Message-ID: <68E3AD21-3FAD-4475-8F07-355C0AD936E8@uos.de> Dear Colleague, we would like to invite you to register for the 5th +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Osnabrueck Computational Cognition Alliance Meeting (OCCAM 2015) "From Simple Neurons to Large-Scale Models of Cognition" May 6-7, 2015. +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ List of invited speakers: Nicolas Brunel Jochen Braun Gustavo Deco Wolfgang Einh?user Virginia Flanagin Sonja Gr?n Marc-Oliver Gewaltig Herbert Jaeger Gordon Pipa Terry Stewart Paul Verschure Kai Vogeley The workshop will take place in Osnabrueck, Germany, and will be hosted by the Institute of Cognitive Science (University of Osnabrueck). Details can be found below and on the following webpage: http://www.occam-os.de The registration deadline has been extended to March 16, 2015. The registration fee is 100,- Euros. There will also be a poster session where conference participants will have the opportunity to present their work. The deadline for submitting an abstract for a poster presentation is also March 16. Best regards, Frank J?kel, Peter K?nig, Gordon Pipa (Organizing committee) From dwang at cse.ohio-state.edu Mon Mar 9 21:15:06 2015 From: dwang at cse.ohio-state.edu (DeLiang Wang) Date: Mon, 9 Mar 2015 21:15:06 -0400 Subject: Connectionists: NEURAL NETWORKS, March 2015 Message-ID: <54FE459A.4060301@cse.ohio-state.edu> Neural Networks - Volume 63, March 2015 http://www.journals.elsevier.com/neural-networks A neural network for learning the meaning of objects and words from a featural representation Mauro Ursino, Cristiano Cuppini, Elisa Magosso Circuit design and exponential stabilization of memristive neural networks Shiping Wen, Tingwen Huang, Zhigang Zeng, Yiran Chen, Peng Li Performance improvement of classifier fusion for batch samples based on upper integral Hui-Min Feng, Xi-Zhao Wang Convex nonnegative matrix factorization with manifold regularization Wenjun Hu, Kup-Sze Choi, Peiliang Wang, Yunliang Jiang, Shitong Wang Towards an intelligent framework for multimodal affective data analysis Soujanya Poria, Erik Cambria, Amir Hussain, Guang-Bin Huang Approximate kernel competitive learning Jian-Sheng Wu, Wei-Shi Zheng, Jian-Huang Lai A vector reconstruction based clustering algorithm particularly for large-scale text collection Ming Liu, Chong Wu, Lei Chen Active learning for semi-supervised clustering based on locally linear propagation reconstruction Chin-Chun Chang, Po-Yi Lin Adaptive learning rate of SpikeProp based on weight convergence analysis Sumit Bam Shrestha, Qing Song Fully probabilistic control for stochastic nonlinear control systems with input dependent noise Randa Herzallah Self-organizing maps based on limit cycle attractors Di-Wei Huang, Rodolphe J. Gentili, James A. Reggia Projective synchronization of fractional-order memristor-based neural networks Hai-Bo Bao, Jin-De Cao Estimates on compressed neural networks regression Yongquan Zhang, Youmei Li, Jianyong Sun, Jiabing Ji Global exponential stability of delayed Markovian jump fuzzy cellular neural networks with generally incomplete transition probability Yonggui Kao, Lei Shi, Jing Xie, Hamid Reza Karimi Jackson-type inequalities for spherical neural networks with doubling weights Shaobo Lin, Jinshan Zeng, Lin Xu, Zongben Xu RBF-network based sparse signal recovery algorithm for compressed sensing reconstruction Vidya L., Vivekanand V., Shyamkumar U., Deepak Mishra Finite-time synchronization control of a class of memristor-based recurrent neural networks Minghui Jiang, Shuangtao Wang, Jun Mei, Yanjun Shen Dynamics of neural networks over undirected graphs Eric Goles, Gonzalo A. Ruz Convergence and attractivity of memristor-based cellular neural networks with time delays Sitian Qin, Jun Wang, Xiaoping Xue Massively parallel neural circuits for stereoscopic color vision: Encoding, decoding and identification Aurel A. Lazar, Yevgeniy B. Slutskiy, Yiyin Zhou Neural network for constrained nonsmooth optimization using Tikhonov regularization Sitian Qin, Dejun Fan, Guangxi Wu, Lijun Zhao Robust sequential learning of feedforward neural networks in the presence of heavy-tailed noise Najdan Vukovic, Zoran Miljkovic Fast Clustered Radial Basis Function Network as an adaptive predictive controller Dino Kosic Designing a deep brain stimulator to suppress pathological neuronal synchrony Ghazal Montaseri, Mohammad Javad Yazdanpanah, Fariba Bahrami From jlam at bccn-tuebingen.de Mon Mar 9 04:31:26 2015 From: jlam at bccn-tuebingen.de (Judith Lam) Date: Mon, 09 Mar 2015 09:31:26 +0100 Subject: Connectionists: Computational Vision Summer School, July 28 - Aug 4, 2015 Message-ID: <54FD5A5E.5020203@bccn-tuebingen.de> The Bernstein Center Tuebingen invites advanced PhD students and postdocs to apply for the... * ************************************************************************** Computational Vision **Summer **School, **July 28 - Aug 4, 2015* *Freudenstadt-Lauterbad, Black Forest* *Application deadline: April 7, 2015 http://www.bccn-tuebingen.de/training/cvss2015/ ***************************************************************************** The Computational Vision Summer School offers a broad perspective on biological vision with a thorough understanding of the theoretical and computational challenges involved. The school is unique in bringing together people from diverse disciplines who all share a computational view of vision. The faculty consists of renowned senior researchers in the field teaching lectures and providing hands-on tutorials on topics ranging from early vision to image understanding. * Confirmed Speakers: *Jim DiCarlo (MIT, USA) Rob Fergus (Facebook, NY, USA) Andrew Fitzgibbon (Microsoft Research, UK) Laurence T Maloney (NYU, USA) Anthony J Movshon (NYU, USA) Aude Oliva (MIT, USA) Bruno Olshausen (UC Berkeley, USA) Cordelia Schmid (INRIA, France) Eero Simoncelli (NYU, USA) Garrett Stanley (Georgia Institute of Technology & Emory University, USA) Raquel Urtasun (U Toronto, Canada) Brian A Wandell (Stanford University, USA) Andrew Zisserman (U Oxford, UK) *Program Chairs:* Matthias Bethge, Michael Black, Roland Fleming, Felix Wichmann -- Dr. Judith Lam Executive Coordinator Bernstein Center for Computational Neuroscience T?bingen Eberhard Karls University of T?bingen Max Planck Institute for Biological Cybernetics http://www.bccn-tuebingen.de/about-bccn/contact.html Otfried-M?ller-Str. 25, 72076 T?bingen Tel: +49 7071 29 89019 Fax: +49 7071 29 25015 -------------- next part -------------- An HTML attachment was scrubbed... URL: From maciej.jedynak at upf.edu Sun Mar 8 09:07:38 2015 From: maciej.jedynak at upf.edu (Maciej Jedynak) Date: Sun, 8 Mar 2015 14:07:38 +0100 Subject: Connectionists: International Conference on System Level approaches to Neural Engineering Message-ID: --------------------------------------- FIRST ANNOUNCEMENT --------------------------------------- International Conference on System Level approaches to Neural Engineering Dates: September 21st ? 23rd , 2015 Venue: Barcelona Biomedical Research Park , Barcelona, Spain Website: http://www.neural-engineering.eu/BarcelonaConference2015/index.html The aim of this interdisciplinary conference is to bring together theoretical and experimental neuroscientists and roboticists to discuss the state of the art in the field of Neural Engineering. This three day long event is part of a series of training events organized by the Marie Curie Initial Training Network NETT (Neural Engineering Transformative Technologies). It will also give young researchers an opportunity to present their work. Theme panels are: * Neural Dynamics - mathematical description of neuronal activity * Brain-on-Chip - engineering of neuronal circuits in-vitro with emphasis on microfluidics * Neural Learning and Control - motion planning, controlling and learning neuro-inspired techniques for robotics * Neural Coding - investigation of neuronal strategies for encoding information * Optical Neurotechnology - imaging and engineering techniques that allow recording of neuronal activity --------------------------------------- CONFIRMED SPEAKERS --------------------------------------- Andre Bastos - The Picower Institute for Learning and Memory, MIT, Boston, MA, USA Romain Brette - Institut de la Vision, Paris, France Sophie Deneve - Laboratoire de Neurosciences Cognitives, LNC, Paris, France Dario Farina - Bernstein Center for Computational Neuroscience, G?ttingen, Germany Albert Folch - Department of Bioengineering, University of Washington, Seattle, WA, USA Amanda Foust - Imperial College London, London, UK Sami Haddadin - Institute of Automatic Control, Hannover, Germany Kenneth Harris - Institute of Neurology and the Department of Physiology, Pharmacology, and Neuroscience, UCL, London, UK Fritjof Helmchen - Brain Research Institute, Z?rich, Switzerland Thibault Honegger - Laboratoire des Technologies de la Microelectronique, CNRS-CEA, Grenoble, France Eugene Izhikevich - Brain Corporation, San Diego, CA, USA Viktor Jirsa - Institut de Neurosciences des Syst?mes, Marseille, France David Liley - Swinburne University of Technology, Melbourne, Australia Benjamin Lindner - Bernstein Center for Computational Neuroscience, Berlin, Germany Nikos Logothetis - Max Planck Institute for Biological Cybernetics, T?bingen, Germany Yoonkey Nam - Advanced Institute of Science and Technology, Korea Adam Packer - University College London, London, UK Stefano Panzeri - Neural Computation Lab, Istituto Italiano di Tecnologia, Rovereto, Italy Eftychios Pnevmatikakis - Columbia University, New York, NY, USA Alexandre Pouget - CMU, Geneva, Switzerland Jan Schnupp - Department of Physiology, Anatomy, and Genetics, Oxford, UK Gregor Scho?ner - Institut f?r Neuroinformatik Ruhr-Universit?t Bochum, Germany Reza Shadmehr - John Hopkins University, Baltimore, MD, USA Patrick van der Smagt - BRML labs, TUM, Germany John Terry - College of Engineering, Mathematics and Physical Sciences, University of Exeter, UK International Conference on System Level Approaches to Neural Engineering conference is organised by the Fellows of the Neural Engineering Transformative Technologies (NETT) consortium. On their behalf we cordially invite you to participate in this meeting that will take place in Barcelona, Spain, on September 21st ? 23rd , 2015. The NETT consortium is a Marie Curie Initial Training Network involving neuroscience research laboratories from the UK, France, Italy, the Netherlands, Spain and Portugal and industrial partners. The network is coordinated by Professor Stephen Coombes from the University of Nottingham, UK. --------------------------------------- REGISTRATION --------------------------------------- Registration can be done on our registration form . Registration opens: 1st March 2015 Registration deadline: 30th May 2015 Conference fee will be 200 euros plus 50 euros for an optional conference dinner. Details about the payment will be posted on the conference website. --- Call for posters --- Posters will be selected from half-page abstracts, which should be submitted by email to nett.barcelona.2015 at gmail.com. Please specify in the object to which theme panel you are submitting your abstract. Abstract Submission opens: 1st of March 2015 Abstract Submission closes: 30th May 2015 Abstract Acceptance Notification: 30th June 2015 Best regards, on behalf of the NETT Fellows, Maciej Jedynak, Neural Engineering Transformative Technologies Universitat Polit?cnica de Catalunya, Universitat Pompeu Fabra. Barcelona, Spain. -------------- next part -------------- An HTML attachment was scrubbed... URL: From eros.pasero at polito.it Mon Mar 9 21:21:54 2015 From: eros.pasero at polito.it (PASERO EROS GIAN ALESSANDRO) Date: Tue, 10 Mar 2015 09:21:54 +0800 Subject: Connectionists: WIRN 2015 NEW DEADLINES Message-ID: NEW DEADLINES! We apologize if you receive multiple copies of this message. Due to several requests, the deadline for the paper submission will be extended to April 5, 2015. ************************************************************************ WIRN 201WIRN5 - First Call for Papers 25th Italian Workshop on Neural Networks May 21-22, Vietri sul Mare, Salerno, Italy WIRN 2015 - CALL FOR PAPERS The Italian Workshop on Neural Networks (WIRN) is the annual conference of the Italian Society of Neural Networks (SIREN). The conference is organized, since 1989, in co-operation with the International Institute for Advanced Scientific Studies (IIASS) located in Vietri S/M (Italy), and is a traditional event devoted to the discussion of novelties and innovations related to field of Artificial Neural Networks. In recent years, it also became a multidisciplinary forum on psychological and cognitive theories for modelling human behaviours. The 25th Edition of the Italian Workshop on Neural Networks (WIRN 2015) will be held at the IIASS in Vietri sul Mare, near Salerno, Italy. CALL FOR PAPERS, SPECIAL SESSIONS PROPOSALS: Prospective authors are invited to contribute high quality papers in the topic areas listed below and proposals for special sessions. Special sessions aim to bring together researchers in special focused topics. Each special session should include at least 3 contributing papers. A proposal for a special session should include a summary statement (1 page long) describing the motivation and relevance of the proposed special session, together with the article titles and author names of the papers that will be included in the track. Contributions should be high quality, original and not published elsewhere or submitted for publication during the review period. Please visit the web site for details on the required paper format. Papers will be reviewed by the Program Committee, and may be accepted for oral or poster presentation. All contributions will be published in the Springer volume series Smart Innovation, Systems and Technologies (http://www.springer.com/series/8767) and indexed by SCOPUS. Manuscripts should not exceed the limits of 8 pages. The description of the submission procedure can be found on the WIRN 2015 Website www.wirn2015.polito.it Confirmed key note speakers - Cesare Alippi, Politecnico of Milan - Nikolas Kasabov, Auckland University of Technology - Marios M. Polycarpou, University of Cyprus The WIRN 2015 will host the Special Session "Computational Intelligence Methods for Biomedical ICT in Neurological Diseases" co-funded by the EU program CONNECT2SEA; with guest speakers: - Vo Van Toi, Ho Chi Min International University, Vietnam Lipo Wang, Nanyang Technological University, Singapore TOPIC AREAS: Suggested topics for the conference include, but are not limited to, the following research and application areas: General Topics of Interest about Computational Intelligence: Neural Networks, Fuzzy Systems, Evolutionary Computation and Swarm Intelligence, Support Vector Machines, Complex Networks, Bayesian and Kernel Networks, Consciousness and Models of Emotion Cognitive and Psychological Models of Human Behavior Algorithms & Architectures: Among others: Opportunist Networks, Metabolic Networks, ICA and BSS, Deep Neural Networks, Bio-inspired Neural Networks, Wavelet Neural Networks, Intelligent Algorithms for Signal (Speech, Faces, Gestures, Gaze, etc) Processing and Recognition Implementations: Among others: Hardware Implementations and Embedded Systems, Neuromorphic Circuits and Hardware, Spike-based VLSI NNs, Intelligent Interactive Dialogue Systems, Embodied Conversational Agents Applications: Among others: Finance and Economics, Big Data Analysis, Neuroinformatics and Bioinformatics, Brain-Computer Interface and Systems, Data Fusion, Time Series Modelling and Prediction, Intelligent Infrastructure and Transportation Systems, Sensors and Network of Sensors, Smart Grid, Process Monitoring and Diagnosis, Intelligent and Adaptive Systems for Human-Machine Interaction. PAPER SUBMISSION: Important Dates cid:image004.gif at 01D03B52.F92457D0 Special Session/Workshop proposals: February 15, 2015 cid:image004.gif at 01D03B52.F92457D0 Paper Submission deadline: April 5, 2015 NEW! cid:image004.gif at 01D03B52.F92457D0 Notification of acceptance: April 30, 2015 NEW! cid:image004.gif at 01D03B52.F92457D0 Camera-ready copy: May 15, 2015 cid:image004.gif at 01D03B52.F92457D0 Conference Dates: May 21-22, 2015 More detailed instructions will follow soon on www.wirn2015.polito.it Prof. Eros Pasero SIREN President Now with: cid:image001.png at 01CC0B71.5BE66EA0 Sino-Italian Campus,Tongji University Siping Road, N? 1239, Shanghai Tel/fax: +86 21 65983561 Cell. +86 137 6448926 Laboratorio di Neuronica Dip. Elettronica e Telecomunicazioni - Politecnico di Torino c.so Duca d. Abruzzi 24 10129 Torino - Italy ______________________________________ ' Tel +39 011 0904043, +393316796014 6 Fax 0+39 011 0904216 *e-mail eros.pasero at polito.it WEB: www.neuronica.polito.it P THINK BEFORE YOU PRINT: before printing this e-mail think whether it is really necessary ______________________________________________ "The eternal mystery of the world is its comprehensibility" ______________________________________ -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image001.gif Type: image/gif Size: 201 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image002.jpg Type: image/jpeg Size: 2950 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image003.png Type: image/png Size: 10833 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image004.gif Type: image/gif Size: 201 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image005.png Type: image/png Size: 9192 bytes Desc: not available URL: From tbesold at uni-osnabrueck.de Tue Mar 10 05:48:35 2015 From: tbesold at uni-osnabrueck.de (Tarek R. Besold) Date: Tue, 10 Mar 2015 10:48:35 +0100 Subject: Connectionists: Call for Papers: 10th Intl. Workshop on Neural-Symbolic Learning and Reasoning (NeSy'15) @ IJCAI-15 Message-ID: **** Apologies for multiple-postings **** 10th International Workshop on Neural-Symbolic Learning and Reasoning (NeSy?15) July 25, 26, or 27, 2015 In conjunction with IJCAI-15 Buenos Aires, Argentina Artificial Intelligence researchers continue to face huge challenges in their quest to develop truly intelligent systems. The recent developments in the field of neural-symbolic integration bring an opportunity to integrate well-founded symbolic artificial intelligence with robust neural computing machinery to help tackle some of these challenges. The Workshop on Neural-Symbolic Learning and Reasoning is intended to create an atmosphere of exchange of ideas, providing a forum for the presentation and discussion of the key topics related to neural-symbolic integration. Topics of interest include: ? The representation of symbolic knowledge by connectionist systems; ? Neural Learning theory. ? Integration of logic and probabilities, e.g., in neural networks, but also more generally; ? Structured learning and relational learning in neural networks; ? Logical reasoning carried out by neural networks; ? Integrated neural-symbolic learning approaches; ? Extraction of symbolic knowledge from trained neural networks; ? Integrated neural-symbolic reasoning; ? Neural-symbolic cognitive models; ? Biologically-inspired neural-symbolic integration; ? Applications in robotics, simulation, fraud prevention, natural language processing, semantic web, software engineering, fault diagnosis, bioinformatics, visual intelligence, etc. Submission Researchers and practitioners are invited to submit original papers that have not been submitted for review or published elsewhere. Submitted papers must be written in English, use the IJCAI style, and should not exceed 6 pages in the case of research and experience papers, and 4 pages in the case of position papers (including figures, bibliography and appendices). All submitted papers will be judged based on their quality, relevance, originality, significance, and soundness. Papers must be submitted through EasyChair (please see http://www.neural-symbolic.org/NeSy15/ for details). Presentation Selected papers will be presented during the workshop. The workshop will include extra time for audience discussion of the presentation allowing the group to have a better understanding of the issues, challenges, and ideas being presented. Publication Accepted papers will be published in official workshop proceedings, which will be distributed during the workshop. Authors of the best papers will be invited to submit a revised and extended version of their papers to the Journal of Logic and Computation. Important Dates Deadline for submission: April 27, 2015 Notification of acceptance: May 20, 2015 Camera-ready paper due: May 30, 2015 Workshop day: July 25, 26, or 27, 2015 IJCAI-14 main conference dates: July 28-31, 2015 Workshop Organisers Tarek Besold (Universit?t Osnabr?ck, Germany) Thomas Icard (Stanford University, USA) Luis Lamb (Universidade Federal do Rio Grande do Sul, Brazil) Risto Miikkulainen (The University of Texas at Austin, USA) Programme Committee Artur d?Avila Garcez (City University London, UK) Ross Gayler (Melbourne, Australia) Ramanathan V. Guha (Google Inc., USA) Pascal Hitzler (Wright State University, USA) Steffen H?lldobler (TU Dresden, Germany) Frank J?kel (Universit?t Osnabr?ck, Germany) Kai-Uwe K?hnberger (Universit?t Osnabr?ck, Germany) Alan Perotti (University of Turin, Italy) Christopher Potts (Stanford University, USA) Ron Sun (Rensselaer Polytechnic Institute, USA) Jakub Szymanik (University of Amsterdam, The Netherlands) Gerson Zaverucha (Federal University of Rio de Janeiro, Brazil) Keynote speaker(s) Dan Roth (University of Illinois at Urbana-Champaign, USA) Additional Information General questions concerning the workshop should be addressed to Luis Lamb at LuisLamb at acm.org. For additional information, please see the workshop website at http://www.neural-symbolic.org/NeSy15/ The neural-symbolic integration mailing list will be used for announcements and discussions. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Tarek R. Besold Institute of Cognitive Science University of Osnabr?ck (Germany) tbesold at uni-osnabrueck.de From ste at disi.unige.it Tue Mar 10 06:58:55 2015 From: ste at disi.unige.it (Stefano Rovetta) Date: Tue, 10 Mar 2015 11:58:55 +0100 Subject: Connectionists: cfp: CIBB - Int. Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics Message-ID: <54FECE6F.4080501@disi.unige.it> TWELFTH INTERNATIONAL MEETING ON COMPUTATIONAL INTELLIGENCE METHODS FOR BIOINFORMATICS AND BIOSTATISTICS CIBB 2015 CNR Research Area, Naples (Italy) 10-12 September 2015 Submission deadline: April 10, 2015 FOR FULL INFO PLEASE HEAD ON TO http://bioinfo.na.iac.cnr.it/cibb2015/ CIBB (Computational Intelligence methods for Bioinformatics and Biostatistics) is a meeting with more than 10 years of history. Its main goal is to provide a forum open to researchers from different disciplines to present problems concerning computational techniques in bioinformatics, systems biology and medical informatics, to discuss cutting edge methodologies and accelerate life science discoveries. Technical areas: High dimensional statistical analysis of omic data; Next generation sequencing bioinformatics; Multi-omic data integration; Methods for supervised and unsupervised learning; Prediction of protein structures; Methods for comparative genomics; Algorithms for molecular evolution and phylogenetic analysis; Mathematical modelling and simulation of biological systems; Systems and synthetic biology; Bio-molecular databases and data mining; Bio-medical text mining and imaging; Statistical methods for the analysis of clinical data; Methods for the visualization of high dimensional complex omic data; Software tools for bioinformatics. --Stefano Rovetta DIBRIS University of Genova, Italy From publicity at ecmlpkdd2015.org Tue Mar 10 07:37:12 2015 From: publicity at ecmlpkdd2015.org (ECMLPKDD 2015) Date: Tue, 10 Mar 2015 11:37:12 -0000 Subject: Connectionists: ECMLPKDD 2015 : Call for Papers Message-ID: <006101d05b26$8f1fdfa0$ad5f9ee0$@ecmlpkdd2015.org> The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD) will take place in Porto, Portugal, from September 7th to 11th, 2015 (http://www.ecmlpkdd2015.org). This event is the leading European scientific event on machine learning and data mining and builds upon a very successful series of 25 ECML and 18 PKDD conferences, which have been jointly organized for the past 14 years. ECMLPKDD 2015 will host three tracks, tutorials and a set of workshops. Therefore, we invite all researchers and practitioners from different communities to submit papers and/or present tutorial and workshop proposals. ************************* CALL FOR PAPERS ************************* JOURNAL TRACK ********************* Articles for this track are submitted all year long directly to either Machine Learning or Data Mining and Knowledge Discovery, and are reviewed like regular journal articles. Accepted articles appear in full in the journal and the authors are given a presentation slot at the conference. Articles deemed insufficiently mature for journal publication may be accepted for inclusion in the proceedings. Submissions to the journal track will be managed by the Guest Editorial Board. Paper Submission: Cut-off dates for the bi-weekly batches are 18 Jan, 1 Feb, 15 Fev, 1 Mar, 15 Mar, 29 Mar, 12 Apr, 26 Apr of 2015 Web Page: http://www.ecmlpkdd2015.org/submission/journal-track RESEARCH PROCEEDINGS TRACK ******************************************* The research proceedings track, which is organized in the traditional way. Accepted papers will be published in the Lecture Notes in Artificial Intelligence (LNCS/LNAI) of Springer, after reviewing by the programme committee. Abstract Submission Deadline: March 26, 2015 Paper Submission Deadline: April 2, 2015 Paper Acceptance Notification: June 1, 2015 Paper Camera Ready Submission: June 15, 2015 Web Page: http://www.ecmlpkdd2015.org/submission/research-proceedings-track INDUSTRIAL, GOVERNMENTAL & NON-GOVERNMENTAL PROCEEDINGS TRACK **************************************************************************** ************************** The NEW industrial, governmental & non-governmental (NGO) proceedings track is independent and distinct from the Research Track. Submissions to this track should solve real-world problems and focus on engineering systems, applications, and challenges. Accepted papers will be published in the Lecture Notes in Artificial Intelligence (LNCS/LNAI) of Springer, after reviewing by the programme committee. Abstract Submission Deadline: March 26, 2015 Paper Submission Deadline: April 2, 2015 Paper Acceptance Notification: June 1, 2015 Paper Camera Ready Submission: June 15, 2015 Web Page: http://www.ecmlpkdd2015.org/submission/industrial-proceedings-track Hope to see you all soon in Porto, Portugal!!! The publicity chairs of the ECMLPKDD 2015, Carlos Abreu Ferreira Ricardo Campos --- Este e-mail foi verificado em termos de v?rus pelo software antiv?rus Avast. http://www.avast.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From m.gomez.rodriguez at gmail.com Tue Mar 10 14:48:52 2015 From: m.gomez.rodriguez at gmail.com (Manuel Gomez Rodriguez) Date: Tue, 10 Mar 2015 22:48:52 +0400 Subject: Connectionists: Postdoctoral Position in Networks & Machine Learning @ MPI-SWS Message-ID: Postdoctoral Position in Networks & Machine Learning ========================================== The newly established Machine Learning group at the Max Planck Institute for Software Systems (MPI-SWS, http://www.mpi-sws.org/), led by Manuel Gomez-Rodriguez, is looking for a postdoctoral researcher with a strong interest in networks & machine learning. In our group, we are interested in developing machine learning and large-scale data mining methods for the analysis and modeling of large real-world networks and processes that take place over them. We are particularly interested in problems arising in the Web and social media. For further information on our research, please, visit http://www.mpi-sws.org/~manuelgr/. Applicants should have a strong machine learning and/or data mining background with a track record of research publications in top tier conferences (e.g., ICML, NIPS, KDD, WSDM, WWW) and/or journals (e.g., JMLR, TKDD, TOIS, Network Science). A Ph.D. in a relevant field (e.g., Computer Science, Information Science, Engineering, Statistics & Optimization) is a must. Research experience in social networks or social media data is a big plus. MPI-SWS currently has 9 tenured and tenure-track faculty and about 50 doctoral and post-doctoral researchers and is located in Kaiserslautern and Saarbruecken, in the tri-border area of Germany, France and Luxembourg. The institute maintains an open, international and diverse work environment and we seek applications from outstanding candidates regardless of national origin or citizenship. Working language at MPI-SWS is English -- German is not required. The salary is highly competitive and you will have great support to do outstanding research. The position is for one year in the first instance, with expectation of renewal subject to good performance. In order to apply, please, use the online application system at http://www.mpi-sws.org/index.php?n=careers/postdoctoral and drop me an email to manuelgr at mpi-sws.org to highlight your application. Review of applications will start immediately, and continue until the position is filled. From martaruizcostajussa at gmail.com Tue Mar 10 15:25:14 2015 From: martaruizcostajussa at gmail.com (Marta Ruiz) Date: Tue, 10 Mar 2015 13:25:14 -0600 Subject: Connectionists: Final CFP *EXTENDED DEADLINE*: JAIR Special Track on Cross-language Algorithms and Applications Message-ID: JAIR Special Track on Cross-language Algorithms and Applications Track Editor Llu?s M?rquez, Qatar Computing Research Institute Associate Track Editors Marta R. Costa-?juss?, Instituto Polit?cnico Nacional Srinivas Bangalore, AT&T Labs-Research Patrik Lambert, Universitat Pompeu Fabra Elena Montiel-Ponsoda, Universidad Polit?cnica de Madrid The Journal of Artificial Intelligence Research (JAIR) is pleased to announce the launch of the Special Track on Cross-language Algorithms and Applications. The core Artificial Intelligence technologies of speech and natural language processing need to address the challenges of processing multiple languages. While the first challenge of multilingualism is to bridge the nomenclature gap for the same concepts, the next significant challenge is to develop algorithms and applications that not only scale to multiple languages but also leverage cross-lingual similarities for improved natural language processing. The goal of this special track is to serve as a home for the publication of leading research on Cross-language Algorithms and Applications, focusing on developing unified themes leading to the development of the science of multi- and cross-lingualism. Topics of interest include, but are not limited to: efforts in the direction of multilingual transliteration; multilingual document summarization; rapid prototyping of cross language tools for low resource languages; and machine translation. Articles published in the Cross-language Algorithms and Applications track must meet the highest quality standards as measured by originality and significance of the contribution and clarity of presentation. Papers will be coordinated by the track editor and associate editors, and reviewed by peer reviewers drawn from the JAIR Editorial Board and the larger community. All articles should be submitted using the normal JAIR submission process. Please indicate that the submission is intended for the Special Track in the section "Special Information for editors". For more information and submission instructions, please see: http://www.jair.org/specialtrack-claa.html Timetable 24th March 2015 *EXTENDED* Deadline for Submissions 24th June 2015 Notification of Acceptance/Revision/Rejection 5th August 2015 Deadline for Re-submission of papers requiring revision 5th October 2015 Notification of Final Acceptance 24th November 2015 Final manuscript due Contact: martaruizcostajussa at gmail.com Submission Instructions: Use JAIR conventional submissions instructions available at http://www.jair.org/submission_info.html -------------- next part -------------- An HTML attachment was scrubbed... URL: From publicity at ecmlpkdd2015.org Tue Mar 10 16:18:57 2015 From: publicity at ecmlpkdd2015.org (ECMLPKDD 2015) Date: Tue, 10 Mar 2015 20:18:57 -0000 Subject: Connectionists: ECMLPKDD 2015 : Nectar Track Message-ID: <002001d05b6f$728dfdb0$57a9f910$@ecmlpkdd2015.org> The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD 2015) will take place on September 7 of 2015, in Porto Portugal ( http://www.ecmlpkdd2015.org/) and includes a Nectar Track that offers conference attendees a compact overview of recent scientific advances at the frontier of machine learning and data mining with other disciplines, as published in related conferences and journals. We invite senior and junior researchers to submit summaries of their own work published in neighboring fields, such as (but not limited to) artificial intelligence, data analytics, bioinformatics, games, computational linguistics, computer vision, geoinformatics, health informatics, database theory, human computer interaction, information and knowledge management, robotics, pattern recognition, statistics, social network analysis, theoretical computer science, uncertainty in AI, network science, complex systems science, and computationally oriented sociology, economy, statistics and biology. Particularly welcome is work that illustrates the pervasiveness of data-driven exploration and modelling in science and technology, as well as innovative applications. Accepted NECTAR contributions will be presented as talks or posters and included in the conference proceedings. Important dates Submission deadline: May 4, 2015 Notifications of acceptance: June 1, 2015 Submission of camera ready copies: June 15, 2015 Detailed information about the Nectar Track is available on: http://www.ecmlpkdd2015.org/submission/call-nectar-track-contributions For further information please contact the ECMLPKDD 2015 Nectar Track Chairs: Ricard Gavald? (Universitat Polit?cnica de Catalunya) Dino Pedreschi (Universit? di Pisa) Hope to see you all soon in Porto, Portugal!!! The publicity chairs of the ECMLPKDD 2015, Carlos Abreu Ferreira Ricardo Campos --- Este e-mail foi verificado em termos de v?rus pelo software antiv?rus Avast. http://www.avast.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From neurogirl at hotmail.com Wed Mar 11 19:13:17 2015 From: neurogirl at hotmail.com (neuro girl) Date: Wed, 11 Mar 2015 19:13:17 -0400 Subject: Connectionists: Brain States Meeting Message-ID: Dear Colleagues, We would like to invite you to reserve the date for our upcoming meeting: Novel Approaches to the Characterization of Healthy and Dysfunctional Brain States November 12-13, 2015 Cologne, Germany This symposium will explore the most up-to-date theories of normal brain function and how these processes may be altered to produce pathological states. Furthermore, it will explore the models and methods used to describe the proposed neural strategies subserving these different brain states. Our list of confirmed speakers include: Hagai Bergman (Hebrew University of Jerusalem)Emad N. Eskandar (Massachusetts General Hospital-Harvard Medical School)John J. Foxe (Albert Einstein College of Medicine)Marc Goodfellow (University of Exeter) Anthony A. Grace (University of Pittsburgh)Viktor Jirsa (Aix-Marseille Universit? /CNRS)Fernando Lopes da Silva(University of Amsterdam)Christoph M. Michel (University of Geneva)Urs Ribary (Simon Fraser University)G?nter Schiepek (Paracelsus Medical University)Wolf Singer (Max Planck Institute for Brain Research)Dimitri van de Ville(University of Geneva) Registration and further details will be forthcoming and also available at http://bit.ly/1Eaha1o.We look forward to welcoming you to Cologne in November! With best regards,Rowshanak Hashemiyoon, PhDChief, Behavioral Neurophysiology and Computational NeuroscienceKlinik f?r Stereotaxie und Funktionelle Neurochirurgie Universit?tsklinikum K?lnKerpener Str. 62 D - 50937 K?ln Email: row.hashemiyoon at uk-koeln.de http://www.uk-koeln.de/de/stereotaxie Univ.-Prof. Dr. med. Veerle Visser-Vandewalle Direktorin der Klinik f?r Stereotaxie und Funktionelle Neurochirurgie Universit?tsklinikum K?ln (A?R) Kerpener Str. 62 D - 50937 K?ln Email: veerle.visser-vandewalle at uk-koeln.de http://www.uk-koeln.de/kliniken/stereotaxie -------------- next part -------------- An HTML attachment was scrubbed... URL: From terry at salk.edu Wed Mar 11 23:33:32 2015 From: terry at salk.edu (Terry Sejnowski) Date: Wed, 11 Mar 2015 20:33:32 -0700 Subject: Connectionists: How many bits can you store at a synapse? In-Reply-To: Message-ID: http://biorxiv.org/content/early/2015/03/11/016329 Hippocampal Spine Head Sizes are Highly Precise Thomas M Bartol, Cailey Bromer, Justin P Kinney, Michael A Chirillo, Jennifer N Bourne, Kristen M Harris, Terrence J Sejnowski The precision of synaptic weights is thought to be only a few bits. By analyzing pairs of synapses from one axon onto the same dendrite we found that the precision was suprisingly high. Terry ----- From malin.sandstrom at incf.org Thu Mar 12 06:05:55 2015 From: malin.sandstrom at incf.org (=?UTF-8?Q?Malin_Sandstr=C3=B6m?=) Date: Thu, 12 Mar 2015 11:05:55 +0100 Subject: Connectionists: Students: spend the summer improving brain research software tools in Google Summer of Code Message-ID: Hi all, (apologies for cross-posting) are you a student interested in brain research and software development? Or do you know one? This year again, INCF is participating as mentoring organization in the Google Summer of Code, a global program that offers students stipends to spend the summer writing code for open source projects. INCF has 27 project proposals offered by mentors from the international research community, many of them with a computational neuroscience slant. All projects deal with development and/or improvement of open source tools that are used in the neuroscience community. You can see our full list of projects here: https://incf.org/gsoc/2015/proposals To be eligible, students must fulfill the Google definition of 'student': an individual enrolled in or accepted into an accredited institution including (but not necessarily limited to) colleges, universities, masters programs, PhD programs and undergraduate programs. Student applications open on *Monday, March 16.* Please forward to anyone you think might be interested! Best regards, Malin Sandstr?m (INCF org admin for GSoC) GSoC questions welcome to: gsoc at incf.org -- Malin Sandstr?m, PhD Community Engagement Officer malin.sandstrom at incf.org International Neuroinformatics Coordinating Facility Karolinska Institutet Nobels v?g 15 A SE-171 77 Stockholm Sweden http://www.incf.org -------------- next part -------------- An HTML attachment was scrubbed... URL: From n.lepora at bristol.ac.uk Wed Mar 11 18:26:43 2015 From: n.lepora at bristol.ac.uk (Nathan Lepora) Date: Wed, 11 Mar 2015 22:26:43 +0000 Subject: Connectionists: [meetings] Living Machines IV: Final Call for Papers, Satellite Events and Sponsors Message-ID: ______________________________________________________________ Final Call for Papers, Satellite Events and Sponsors Living Machines IV: The 4th International Conference on Biomimetic and Biohybrid Systems 28th to 31st July 2015 http://csnetwork.eu/livingmachines To be hosted at the La Pedrera Barcelona, Spain In association with the Universitat Pompeu Fabra Accepted papers will be published in Springer Lecturer Notes in Artificial Intelligence Submission deadline March 16th, 2015 ______________________________________________________________ ABOUT LIVING MACHINES 2015 The development of future real-world technologies will depend strongly on our understanding and harnessing of the principles underlying living systems and the flow of communication signals between living and artificial systems. Biomimetics is the development of novel technologies through the distillation of principles from the study of biological systems. The investigation of biomimetic systems can serve two complementary goals. First, a suitably designed and configured biomimetic artefact can be used to test theories about the natural system of interest. Second, biomimetic technologies can provide useful, elegant and efficient solutions to unsolved challenges in science and engineering. Biohybrid systems are formed by combining at least one biological component?an existing living system?and at least one artificial, newly-engineered component. By passing information in one or both directions, such a system forms a new hybrid bio-artificial entity. The following are some examples: ? Biomimetic robots and their component technologies (sensors, actuators, processors) that can intelligently interact with their environments. ? Active biomimetic materials and structures that self-organize and self-repair. ? Biomimetic computers?neuromimetic emulations of the physiological basis for intelligent behaviour. ? Biohybrid brain-machine interfaces and neural implants. ? Artificial organs and body-parts including sensory organ-chip hybrids and intelligent prostheses. ? Organism-level biohybrids such as robot-animal or robot-human systems. ACTIVITIES The main conference will take the form of a three-day single-track oral and poster presentation programme, 29th to 31st July 2015, hosted at the La Pedrera, Barcelona, Spain. The conference programme will include five plenary lectures from leading international researchers in biomimetic and biohybrid systems, and the demonstrations of state-of-the-art living machine technologies. Agreed speakers are: Roger Quinn, Robots Insect Locomotion (Case Western Reserve University) Ryad Benosman, Neuromorphic. Event-based time oriented vision (Universit? Pierre et Marie Curie-Paris 6, France) Barbara Mazzolai, Biomimetic Robots (IIT at SSSA, Italy) Robert Richardson, Exploration Robotics (Leeds University, UK) Jose Halloy, Collective intelligence in natural and artificial systems (Universit? Paris Diderot LIED) Also a special talk on Biomimetics in Design Nimish Biloria, Bio-inspired performative design (TU Delf University of Technology, The Netherlands) The full conference will be preceded by a day of Satellite Events hosted by the Universitat Pompeu Fabra in Barcelona. SUBMITTING TO LIVING MACHINES 2015 We invite both full papers and short papers in areas related to the conference themes. All contributions will be refereed and accepted papers will appear in the Living Machines 2015 proceedings which we expect to be published in the Springer-Verlag LNAI Series. Full papers (minimum 8 and up to 12 pages) are invited from researchers at any stage in their career but should present significant findings and advances in biomimetic or biohybid research; more preliminary work would be better suited to shorter paper submission (minimum 4 pages with a maximum of eight references and no more than two self-citations) Further details of submission formats will be circulated in an updated CfP and will be posted on the conference web-site. http://csnetwork.eu/livingmachines/conf2015/submission Full papers will be accepted for either oral presentation (single track) or poster presentation. Extended abstracts will be accepted for poster presentation only. Authors of the best full papers will be invited to submitted extended versions of their paper for publication in a special issue of Bioinspiration and Biomimetics. Satellite events Active researchers in biomimetic and biohybrid systems are invited to propose topics for 1-day tutorials, symposia or workshops on related themes to be held 27-28th July at Universitat Pompeu Fabra. Attendance at satellite events will attract a small fee intended to cover the costs of the meeting. There is a lot of flexibility about the content, organisation, and budgeting for these events. Please contact us if you are interested in organising a satellite event! EXPECTED DEADLINES March 16th, 2015 Paper submission deadline May 1st, 2015 Notification of acceptance May 22nd, 2015 Camera ready copy July 27-31 2015 Conference SPONSORSHIP Living Machines 2015 is sponsored by the Convergent Science Network (CSN) for Biomimetics and Neurotechnology. CSN is an EU FP7 Future Emerging Technologies Co-ordination Activity that also organises two highly successful workshop series: the Barcelona Summer School on Brain, Technology and Cognition (http://bcbt.upf.edu and the Capocaccia Neuromorphic Cognitive Engineering Workshop. The 2015 Living Machines conference will also be hosted and sponsored by the Universitat Pompeu Fabra. Call for Sponsors. Other organisations wishing to sponsor the conference in any way and gain the corresponding benefits by promoting themselves and their products to through conference publications, the conference web-site, and conference publicity are encouraged to contact the conference organisers to discuss the terms of sponsorship and necessary arrangements. We offer a number of attractive and good-value packages to potential sponsors. ABOUT THE VENUE Living Machines 2015 returns to the venue of our first conference at the beautiful biomimetic building La Pedrera (Casa Mila) (https://www.lapedrera.com/en/home) designed by renowned modernist architect Antoni Gaudi. Attendees at the conference will get a free ticket to visit this historic building in the centre the Barcelona. Workshops will be held at the Poblenou Campus of Universitat Pompeu Fabra, close to hotel and restaurant area of the Diagonal and Ramblas de Poblenou and a short walk from Barcelona?s famous beaches. Organising Committee: Paul Verschure, Universitat Pompeu Fabra (Co-chair) Tony Prescott, University of Sheffield (Co-chair) Stuart Wilson, University of Sheffield (Program Chair) Anna Mura, Universitat Pompeu Fabra (Communications, Local Organiser) Nathan Lepora, University of Bristol (Communications) Living Machines 2015 Program Committee: Andrew Adamatzky, Robert Allen, Joseph Ayers, Yoseph Bar-Cohen, Lucia Beccai, Fr?d?ric Boyer, Federico Carpi, Hillel Chiel, Anders Christensen, Danilo De Rossi, Angel del Pobil, St?phane Doncieux, Marco Dorigo, Armin Duff, Volker D?rr Wolfgang Eberle, Beno?t Girard, Roderich Gross, Jos? Halloy, Koh Hosoda, Ioannis Ieropoulos, Auke Ijspeert, Holger Krapp, Cecilia Laschi, Nathan Lepora, Ben Mitchinson, Keisuke Morishima, Anna Mura, Jiro Okada, Enrico Pagello, Martin Pearson, Andrew Philippides, Tony Pipe, Tony Prescott, Roger Quinn, Sylvain Saighi, Thomas Schmickl, Reiko Tanaka, Eleni Vasilaki, Stefano Vassanelli, Paul Verschure, Stuart Wilson (Chair), Hartmut Witte From matthias at ams.eng.osaka-u.ac.jp Thu Mar 12 02:33:18 2015 From: matthias at ams.eng.osaka-u.ac.jp (Matthias Rolf) Date: Thu, 12 Mar 2015 15:33:18 +0900 Subject: Connectionists: IEEE ICDL-EPIROB 2015 & Babybot Challenge (Deadline extension) Message-ID: <5501332E.4050203@ams.eng.osaka-u.ac.jp> ======================================================== NOTE: DEADLINE EXTENDED TO 23 MARCH. Call for Papers, Tutorials and Thematic Workshops New Conference Feature: BABYBOT CHALLENGE IEEE ICDL-EPIROB 2015 The Fifth Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics Brown University, Providence, Rhode Island, USA August 13-16, 2015 http://www.icdl-epirob.org/ == Conference description The past decade has seen the emergence of a new scientific field that studies how intelligent biological and artificial systems develop sensorimotor, cognitive, emotional and social abilities, over extended periods of time, through dynamic interactions with their physical and social environments. This field lies at the intersection of a number of scientific and engineering disciplines including Neuroscience, Developmental Psychology, Developmental Linguistics, Cognitive Science, Computational Neuroscience, Artificial Intelligence, Machine Learning, and Robotics. Various terms have been associated with this new field such as Autonomous Mental Development, Epigenetic Robotics, Developmental Robotics, etc., and several scientific meetings have been established. The two most prominent conference series of this field, the International Conference on Development and Learning (ICDL) and the International Conference on Epigenetic Robotics (EpiRob), are now joining forces for the fifth time and invite submissions for a joint conference in 2015, to explore and extend the interdisciplinary boundaries of this field. == BABYBOT CHALLENGE -- CASH PRIZES FOR THE TOP SUBMISSIONS We are excited to announce a new ICDL-EpiRob conference feature: the BABYBOT CHALLENGE. The goal of the challenge is to use the tools of developmental robotics to replicate and extend the key findings from one of three selected human-infant studies. Please visit www.icdl-epirob.org for the full announcement, including the three target studies, details on the submission process, and a description of how the winning submissions will be judged and selected. == Keynote speakers (confirmed) Prof. Dare Baldwin, Dept. of Psychology, University of Oregon, USA Prof. Kerstin Dautenhahn, School of Computer Science, University of Hertfordshire, UK Prof. Asif Ghazanfar, Department of Psychology, Princeton University, USA == Call for Submissions We invite submissions for this exciting window into the future of developmental sciences. Submissions which establish novel links between brain, behavior and computation are particularly encouraged. == Topics of interest include (but are not limited to): * the development of perceptual, motor, cognitive, emotional, social, and communication skills in biological systems and robots * embodiment * general principles of development and learning * interaction of nature and nurture * sensitive/critical periods * developmental stages * grounding of knowledge and development of representations * architectures for cognitive development and open-ended learning * neural plasticity * statistical learning * reward and value systems * intrinsic motivations, exploration and play * interaction of development and evolution * use of robots in applied settings such as autism therapy * epistemological foundations and philosophical issues Any of the topics above can be simultaneously studied from the neuroscience, psychology or modeling/robotic point of view. == Submissions will be accepted in several formats: 1. Full six-page paper submissions: Accepted papers will be included in the conference proceedings and will be selected for either an oral presentation or a featured poster presentation. Featured posters will have a 1 minute "teaser" presentation as part of the main conference session and will be showcased in the poster sessions. Maximum two-extra pages can be acceptable for a publication fee of $100 per page. 2. Two-page poster abstract submissions: To encourage discussion of late-breaking results or for work that is not sufficiently mature for a full paper, we will accept 2-page abstracts. These submissions will NOT be included in the conference proceedings. Accepted abstracts will be presented during poster sessions. 3. Tutorials and workshops: We invite experts in different areas to organize either a tutorial or a workshop to be held on the first day of the conference. Tutorials are meant to provide insights into specific topics as well as overviews that will inform the interdisciplinary audience about the state-of-the-art in child development, neuroscience, robotics, or any of the other disciplines represented at the conference. A workshop is an opportunity to present a topic cumulatively. Workshops can be half- or full-day in duration including oral presentations as well as posters. Submission format: two pages including title, list of speakers, concept and target audience. 4. Babybot challenge (Deadline June 15, 2015): Special submissions are invited for the Babybot challenge, which is for the first time introduced to this conference. For detailed information please visit www.icdl-epirob.org and navigate to ?Babybot Challenge.? All submissions will be peer reviewed. Submission website through paperplaza at: http://ras.papercept.net == Important dates March 23, 2015, paper submission deadline May 15, 2015, author notification July 1, 2015, final version (camera ready) due August 13th-16th, 2015, conference == Program committee General Chairs: Matthew Schlesinger (Southern Illinois Univ.) Dima Amso (Brown University) Bridge Chairs: Jeffrey Krichmar (UC Irvine) Bertram Malle (Brown University) Program Chairs: Anne Warlaumont (UC Merced) Clem?nt Moulin-Frier (INRIA) Publications Chairs: Lisa Meeden (Swarthmore College) Publicity Chairs: Lola Ca?amero (Univ. of Hertfordshire) Matthias Rolf (Osaka University) Benjamin Rosman (CSIR) Local chairs: David Sobel (Brown University) Thomas Serre (Brown University) Finance chairs: Clayton Morrison (University of Arizona) From hans.ekkehard.plesser at nmbu.no Thu Mar 12 07:26:27 2015 From: hans.ekkehard.plesser at nmbu.no (Hans Ekkehard Plesser) Date: Thu, 12 Mar 2015 11:26:27 +0000 Subject: Connectionists: NEST User and Developer Workshop, 20-22 April 2015, Geneva Message-ID: Dear Colleagues! The NEST simulator is used by a growing number of neuroscientist. To strengthen the growing NEST community and foster the dialog between NEST users across a broad spectrum of modelling approaches, as well as between users and developers, we would like to invite you to the First NEST User Workshop, Monday 20 April (evening) til Wednesday 22 April (late afternoon) at Campus Biotech in Geneva, Switzerland. The workshop is primarily intended for users and developers of NEST and you will benefit most if you already have practical experience with NEST. However, if you are interested in using NEST in the future, this workshop will also be useful for you. We will present the new NEST Git Repository and Code Review Platform as part of the workshop. For a limited number of participants, we offer the possibility to present your scientific work done with NEST. If you are interested in presenting, please contact the workshop organizers Hans Ekkehard Plesser (hans.ekkehard.plesser at nmbu.no) Marc-Oliver Gewaltig (marc-oliver.gewaltig at epfl.ch) For more information and registration, please go to https://www.eventbrite.com/e/nest-user-workshop-tickets-15974979594 Registration is free, but limited. Registration deadline: 11 April 2015 We can offer (very) limited travel support to younger participants, kindly provided by the HBP Education Program. This workshop is organized in collaboration between the NEST Initiative and the HBP Education Program. We are looking forward to seeing you in Geneva! Hans E Plesser Marc-Oliver Gewaltig http://www.nest-initiative.org http://humanbrainproject.eu ? Dr. Hans Ekkehard Plesser, Associate Professor Acting section Head Dept. of Mathematical Sciences and Technology Norwegian University of Life Sciences PO Box 5003, 1432 Aas, Norway Phone +47 6723 1560 Email hans.ekkehard.plesser at nmbu.no Home http://arken.umb.no/~plesser From juergen at idsia.ch Thu Mar 12 13:58:16 2015 From: juergen at idsia.ch (Schmidhuber Juergen) Date: Thu, 12 Mar 2015 18:58:16 +0100 Subject: Connectionists: Who introduced the term "Deep Learning" to NNs? Message-ID: <7F460A0F-E239-4EC7-B3E7-EFA0CBCC9D9C@idsia.ch> Dear connectionists, to my knowledge, the ancient term "Deep Learning" was introduced to the NN field by Aizenberg & Aizenberg & Vandewalle's book (2000): "Multi-Valued and Universal Binary Neurons: Theory, Learning and Applications.? Is anyone aware of older NN papers using it? (Of course, the field itself is much older - Ivakhnenko started his work on deep learning networks in the mid 1960s.) Thanks! Juergen http://people.idsia.ch/~juergen/whatsnew.html From geoffrey.hinton at gmail.com Thu Mar 12 16:16:46 2015 From: geoffrey.hinton at gmail.com (Geoffrey Hinton) Date: Thu, 12 Mar 2015 16:16:46 -0400 Subject: Connectionists: Who introduced the term "Deep Learning" to NNs? In-Reply-To: <7F460A0F-E239-4EC7-B3E7-EFA0CBCC9D9C@idsia.ch> References: <7F460A0F-E239-4EC7-B3E7-EFA0CBCC9D9C@idsia.ch> Message-ID: I think the current popularity of the term started with the paper by Hinton Osindero and Teh in 2006 called "A fast learning algorithm for deep belief nets". After this paper there was a lot of talk about deep belief nets. In about 2007 the term "deep belief net" started changing its meaning and was used (rather sloppily) to refer to deep neural nets that were pre-trained as deep belief nets. The term gained a lot of popularity because these nets were used to make good acoustic models and that triggered the re-introduction of neural nets into mainline speech recognizers. People eventually made a clear terminological distinction between deep belief nets (DBNs) and deep neural nets that were initialized as deep belief nets (DNNs or DBN-DNNs). Then they discovered that with large datasets and sensible initial scales for the weights the pre-training was not needed and they generalized DNNs to any old deep neural net. Its clearly true that people had previously used the term deep neural net but that was not the origin of the resurgence of the term in about 2007. Its pretty obvious by now that deep neural networks of the type that people were using in the 1980's work very well when they have enough data and enough computation, and its pretty obvious that the deep convnets that Yann has been using since about 1987 are deep neural nets, so what does it matter where the name came from? Deep neural nets are finally living up to their promise so lets all enjoy it. Geoff On Thu, Mar 12, 2015 at 1:58 PM, Schmidhuber Juergen wrote: > Dear connectionists, > > to my knowledge, the ancient term "Deep Learning" was introduced to the NN field by Aizenberg & Aizenberg & Vandewalle's book (2000): "Multi-Valued and Universal Binary Neurons: Theory, Learning and Applications." > > Is anyone aware of older NN papers using it? > > (Of course, the field itself is much older - Ivakhnenko started his work on deep learning networks in the mid 1960s.) > > Thanks! > > Juergen > > http://people.idsia.ch/~juergen/whatsnew.html From juergen at idsia.ch Thu Mar 12 17:35:22 2015 From: juergen at idsia.ch (Juergen Schmidhuber) Date: Thu, 12 Mar 2015 22:35:22 +0100 Subject: Connectionists: Who introduced the term "Deep Learning" to NNs? In-Reply-To: References: <7F460A0F-E239-4EC7-B3E7-EFA0CBCC9D9C@idsia.ch> Message-ID: <0A2132A5-CEF5-47DE-9FF2-8EE2A5ED8F3B@idsia.ch> Thanks. Hm, sure, ?deep neural nets? are old, and Ivakhnenko?s deep nets worked well even in the 1960s. But what I?d like to know is: who was the first to use the term ?deep learning? in an NN publication? Aizenberg et al (2000) wrote about ?deep learning of the features of threshold Boolean functions, one of the most important objects considered in the theory of perceptrons ?? Brian Mingus, however, pointed me to a paper by Rina Dechter (1986). Brian wrote: "Deep learning as compared to shallow learning is terminology used in the study of constraint satisfaction. Constraint satisfaction networks then became RBMs. I would argue this is a good basis for the origin of the modern usage. I like this paper for provenance: http://www.aaai.org/Papers/AAAI/1986/AAAI86-029.pdf " But perhaps the term occurred even earlier in the NN literature? Juergen > On 12 Mar 2015, at 21:16, Geoffrey Hinton wrote: > > I think the current popularity of the term started with the paper by > Hinton Osindero and Teh in 2006 called "A fast learning algorithm for > deep belief nets". After this paper there was a lot of talk about > deep belief nets. In about 2007 the term "deep belief net" started > changing its meaning and was used (rather sloppily) to refer to deep > neural nets that were pre-trained as deep belief nets. The term gained > a lot of popularity because these nets were used to make good acoustic > models and that triggered the re-introduction of neural nets into > mainline speech recognizers. People eventually made a clear > terminological distinction between deep belief nets (DBNs) and deep > neural nets that were initialized as deep belief nets (DNNs or > DBN-DNNs). Then they discovered that with large datasets and sensible > initial scales for the weights the pre-training was not needed and > they generalized DNNs to any old deep neural net. > > Its clearly true that people had previously used the term deep neural > net but that was not the origin of the resurgence of the term in about > 2007. > > Its pretty obvious by now that deep neural networks of the type that > people were using in the 1980's work very well when they have enough > data and enough computation, and its pretty obvious that the deep > convnets that Yann has been using since about 1987 are deep neural > nets, so what does it matter where the name came from? Deep neural > nets are finally living up to their promise so lets all enjoy it. > > Geoff > > > > > On Thu, Mar 12, 2015 at 1:58 PM, Schmidhuber Juergen wrote: >> Dear connectionists, >> >> to my knowledge, the ancient term "Deep Learning" was introduced to the NN field by Aizenberg & Aizenberg & Vandewalle's book (2000): "Multi-Valued and Universal Binary Neurons: Theory, Learning and Applications." >> >> Is anyone aware of older NN papers using it? >> >> (Of course, the field itself is much older - Ivakhnenko started his work on deep learning networks in the mid 1960s.) >> >> Thanks! >> >> Juergen >> >> http://people.idsia.ch/~juergen/whatsnew.html -------------- next part -------------- An HTML attachment was scrubbed... URL: From Vittorio.Murino at iit.it Thu Mar 12 19:07:35 2015 From: Vittorio.Murino at iit.it (Vittorio Murino) Date: Fri, 13 Mar 2015 00:07:35 +0100 Subject: Connectionists: ICIAP2015: Deadline extension and possible CVIU and PR special issues Message-ID: <55021C37.1030004@iit.it> Apologise for multiple posting ========================================================================== >>> NEWS: - Deadline extendend to 23 March 2015! - Possible CVIU and PR special issues in discussion for selected papers! ========================================================================== 18th International Conference on Image Analysis and Processing ICIAP 2015 ========================================================================== Genova, Italy 7-11 September, 2015 http://www.iciap2015.eu Main Conference: 9-11 September, 2015 Workshop and Tutorials: 7-8 September, 2015 ======================================================= IMPORTANT DATES >>> Full paper submission: (NEW) March 23, 2015 Papers should be submitted following the SPRINGER LNCS format for a maximum of 10 pages + 1 page for references. Full paper evaluation notification: May 15, 2015 Camera ready submission: June 15, 2015 Author registration: June 22, 2015 ======================================================= CALL FOR PAPERS ICIAP 2015 is the 18th edition of a series of conferences organized biennially by the Italian Member Society (GIRPR) of the International Association for Pattern Recognition (IAPR). The conference covers the following topic areas, each one overseen by scientists, among the main experts in their respective areas: - Video Analysis & Understanding - Multiview Geometry and 3D Computer Vision - Pattern Recognition and Machine Learning - Image Analysis, Detection and Recognition - Shape Analysis and Modeling - Multimedia - Biomedical Applications >>>> NEWS: Journal Special Issues Agreements are in progress for the organization of two journal special issues, dedicated to ICIAP 2015. Authors of selected papers will be invited to submit an extended version of their manuscripts to Computer Vision and Image Understanding and Pattern Recognition journals for inclusion in the ICIAP 2015 special issues. INVITED SPEAKERS * Samy Bengio, Google * Kristen Grauman, University of Texas at Austin * Michal Irani, Weizmann Institute of Science * Bernt Schiele, Max Planck Institute for Informatics * Arnold Smeulders, University of Amsterdam * Xiaogang Wang, The Chinese University of Hong Kong ORGANIZATION - General Chair: V. Murino (IIT and U. of Verona) - Program Chairs: E. Puppo (U. of Genova), G. Vernazza (U. of Genova) ======================================================================= -- Vittorio Murino ******************************************* Prof. Vittorio Murino, Ph.D. Director PAVIS - Pattern Analysis & Computer Vision IIT Istituto Italiano di Tecnologia Via Morego 30 16163 Genova, Italy Phone: +39 010 71781 504 Mobile: +39 329 6508554 Fax: +39 010 71781 236 E-mail: vittorio.murino at iit.it Secretary: Sara Curreli email: sara.curreli at iit.it Phone: +39 010 71781 917 http://www.iit.it/pavis ******************************************** From alessandro at idsia.ch Thu Mar 12 16:42:30 2015 From: alessandro at idsia.ch (Alessandro Antonucci) Date: Thu, 12 Mar 2015 21:42:30 +0100 Subject: Connectionists: =?utf-8?q?IJCAI=E2=80=9915_Workshop_on_Sensitivit?= =?utf-8?q?y_Analysis_and_Robustness_in_Probabilistic_Graphical_Mod?= =?utf-8?q?els_=282nd_CFP=29?= Message-ID: IJCAI?15 Workshop on Sensitivity Analysis and Robustness in Probabilistic Graphical Models Buenos Aires, July 25-27, 2015 - http://ipg.idsia.ch/wijcai15/ SECOND CALL FOR PAPERS Probabilistic graphical models are important tools in machine learning and artificial intelligence for reasoning with uncertainty. They provide means to represent large multivariate domains compactly and to perform sophisticated learning and reasoning efficiently. Examples of probabilistic graphical models are Bayesian networks, Markov Random fields, chain and factor graphs, Gaussian graphical models, to name but a few. The quantification of these models usually requires sharp (i.e., precise) assessments of the model local potentials and might be subject to robustness issues. For instance, perturbations of some parameter values may lead to different decisions from those which would be achieved by the unperturbed model, suggesting that decisions are not reliable. Reliability might also be in question because of missing data and assumptions behind the process. The workshop invites submissions of papers on all aspects of sensitivity analysis and robustness in probabilistic graphical models. Contributions may have a theoretical focus and/or an applied focus. A non-exhaustive list of topics follows. - Local and/or global sensitivity analysis. - Parameter-based and/or decision-based sensitivity analysis. - Design of robust learning, inference and/or decision making approaches. - Robust analysis and design of robustness measurements. - Extensions of probabilistic graphical models. - Reliable qualitative learning and reasoning. - Robust treatment of missing data. - Imprecise probability and other theories related to sensitivity analysis. - Computational complexity, exact and approximate algorithms. Each submission will be reviewed by peers using a double-blind process (please use the third person in self citations and take all necessary care not to identify yourselves). Accepted papers will be published electronically in a volume of the JMLR Workshop and Conference Proceedings series. There will be no rebuttal phase, but contributions considered worth publishing and needing substantial revision might be subject to a second round of reviewing/evaluation. All accepted papers will be presented at the workshop. At least one of the paper's authors should register and attend the workshop to present the work. Submissions must be formatted according to style and template files available for the Journal of Machine Learning Research (JMLR) Workshop and Conference Proceedings - two-column version. The files are available at http://ipg.idsia.ch/wijcai15/sarpgm15.tar.gz. Papers (including figures, tables, references, etc) are expected to have between 6 and 10 pages. IMPORTANT DATES Apr 27, 2015 - Deadline for submissions of contributions May 20, 2015 - Workshop paper acceptance notification May 30, 2015 - Deadline for workshop camera-ready copy (in case of minor revision; contributions needing major revision might need additional time - this will be arranged case by case) PC MEMBERS Alessandro Antonucci*, IDSIA, Switzerland. Alessio Benavoli, IDSIA, Switzerland. Cassio P. de Campos*, Queen's University Belfast, UK. Arthur Choi, University of California, Los Angeles, USA. Giorgio Corani*, IDSIA, Switzerland. Fabio Cozman, University of Sao Paulo, Brazil. Adnan Darwiche, University of California, Los Angeles, USA. Sebastien Destercke, Univ. de Technologie de Compiegne, France. Marek Druzdzel, University of Pittsburgh, USA. Johan Kwisthout, Radboud University Nijmegen, The Netherlands. Agnieszka Onisko, Bialystok University of Technology, Poland. Denis Maua, University of Sao Paulo, Brazil. Serafin Moral, Universidad de Granada, Spain. Silja Renooij, Universiteit Utrecht, The Netherlands. Matthias Troffaes, University of Durham, UK. (*: Workshop organizers.) More details about the submission procedure are available online. http://ipg.idsia.ch/wijcai15/ ++++++++++++++++++++++++++++++++++++++++ (We apologize in case you receive multiple copies of this announcement, but yet we hope to reach the greatest possible number of people. Finding a trade-off is not an easy task.) -- _________________________________ Alessandro Antonucci IDSIA Dalle Molle Institute for Artificial Intelligence Via Cantonale (Galleria 2) CH-6928, Manno-Lugano, CH mail: alessandro at idsia.ch skype: alessandro.antonucci tel: +41 916108515 web: www.idsia.ch/~alessandro _________________________________ From pkoenig at uos.de Thu Mar 12 20:57:41 2015 From: pkoenig at uos.de (=?UTF-8?B?UGV0ZXIgS8O2bmln?=) Date: Thu, 12 Mar 2015 20:57:41 -0400 Subject: Connectionists: 3 Research Assistants at the Institute of Cognitive Science Message-ID: <55023605.7030704@uos.de> The Neurobiopsychology Research Group (Prof. Dr. Peter K?nig) of the Institute of Cognitive Science invites applications for *3 Research Assistants *** *(Salary level E 13 TV-L, 50 %)* ** to be filled as soon as possible for a period of 3 years. *Description of Responsibilities:* The positions involve participation in the research activities within the European Community funded research project /Socialising Sensori-Motor Contingencies./ This project investigates processing multimodal information and sensorimotor integration under natural conditions and utilizes a variety of methods. They include behavioral studies, psychophysical methods, physiological measurements (EEG, MEG, TMS), methods of sensory augmentation, mathematical modelling, computer simulations and brain-computer interfaces. *Required Qualifications:* Applicants are expected to have an excellent academic degree (Master, Diploma or PhD), experience in several of the domains listed above, a good record in statistical methods including multivariate analyses and Bayesian technics, good programming skills as well as a good command of the English language. As a certified family-friendly institution, Osnabr?ck University is committed to furthering the compatibility between work/studies and family life. As an employer, Osnabr?ck University is particularly concerned with creating equality opportunities for women and men. Woman with relevant qualifications are therefore strongly encouraged to apply for the positions. Preference will be given to women with equal qualifications. Qualified applicants with disabilities will be favored. Applications with the usual documentation should be submitted by e-mail in a *_single_* PDF-file to Prof. Dr. Peter K?nig (pkoenig at uni-osnabrueck.de ) with a cc to office at ikw.uni-osnabrueck.de no later than *March 31, 2015*. Further information can be obtained from Prof. Dr. Peter K?nig (pkoenig at uni-osnabrueck.de). -- *http://www.facebook.com/CognitiveScienceOsnabruck* Prof. Dr. Peter K?nig Institute of Cognitive Science University Osnabr?ck Albrechtstr. 28 49076 Osnabr?ck +49 541 969 2399 http://cogsci.uni-osnabrueck.de/~NBP/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From minaiaa at gmail.com Fri Mar 13 00:17:53 2015 From: minaiaa at gmail.com (Ali Minai) Date: Fri, 13 Mar 2015 00:17:53 -0400 Subject: Connectionists: Who introduced the term "Deep Learning" to NNs? In-Reply-To: <0A2132A5-CEF5-47DE-9FF2-8EE2A5ED8F3B@idsia.ch> References: <7F460A0F-E239-4EC7-B3E7-EFA0CBCC9D9C@idsia.ch> <0A2132A5-CEF5-47DE-9FF2-8EE2A5ED8F3B@idsia.ch> Message-ID: Juergen, I would say that the instances you point out are not really examples of "deep learning" in the sense the term is being used today. The way we use it now, it refers really to "learning in deep networks", whereas "deep learning" (as opposed to "shallow learning") would mean learning something in a deep sense, e.g., at a conceptual, relational or causal level, rather than in a shallow sense, e.g., at a purely correlational level. This latter sense of "deep learning" may also be implicit in some "deep learning" models, but I don't think the "deep" today refers to this aspect of depth. Any discussion of early "deep networks" must surely also refer to Fukushima's Neocognitron. Ali On Thu, Mar 12, 2015 at 5:35 PM, Juergen Schmidhuber wrote: > Thanks. Hm, sure, ?deep neural nets? are old, and Ivakhnenko?s deep nets > worked well even in the 1960s. But what I?d like to know is: who was the > first to use the term ?deep learning? in an NN publication? > > Aizenberg et al (2000) wrote about ?deep learning of the features of > threshold Boolean functions, one of the most important objects considered > in the theory of perceptrons ?? > > Brian Mingus, however, pointed me to a paper by Rina Dechter (1986). Brian > wrote: "Deep learning as compared to shallow learning is terminology used > in the study of constraint satisfaction. Constraint satisfaction networks > then became RBMs. I would argue this is a good basis for the origin of the > modern usage. I like this paper for provenance: > http://www.aaai.org/Papers/AAAI/1986/AAAI86-029.pdf " > > But perhaps the term occurred even earlier in the NN literature? > > Juergen > > > > On 12 Mar 2015, at 21:16, Geoffrey Hinton > wrote: > > I think the current popularity of the term started with the paper by > Hinton Osindero and Teh in 2006 called "A fast learning algorithm for > deep belief nets". After this paper there was a lot of talk about > deep belief nets. In about 2007 the term "deep belief net" started > changing its meaning and was used (rather sloppily) to refer to deep > neural nets that were pre-trained as deep belief nets. The term gained > a lot of popularity because these nets were used to make good acoustic > models and that triggered the re-introduction of neural nets into > mainline speech recognizers. People eventually made a clear > terminological distinction between deep belief nets (DBNs) and deep > neural nets that were initialized as deep belief nets (DNNs or > DBN-DNNs). Then they discovered that with large datasets and sensible > initial scales for the weights the pre-training was not needed and > they generalized DNNs to any old deep neural net. > > Its clearly true that people had previously used the term deep neural > net but that was not the origin of the resurgence of the term in about > 2007. > > Its pretty obvious by now that deep neural networks of the type that > people were using in the 1980's work very well when they have enough > data and enough computation, and its pretty obvious that the deep > convnets that Yann has been using since about 1987 are deep neural > nets, so what does it matter where the name came from? Deep neural > nets are finally living up to their promise so lets all enjoy it. > > Geoff > > > > > On Thu, Mar 12, 2015 at 1:58 PM, Schmidhuber Juergen > wrote: > > Dear connectionists, > > to my knowledge, the ancient term "Deep Learning" was introduced to the NN > field by Aizenberg & Aizenberg & Vandewalle's book (2000): "Multi-Valued > and Universal Binary Neurons: Theory, Learning and Applications." > > Is anyone aware of older NN papers using it? > > (Of course, the field itself is much older - Ivakhnenko started his work > on deep learning networks in the mid 1960s.) > > Thanks! > > Juergen > > http://people.idsia.ch/~juergen/whatsnew.html > > > -- Ali A. Minai, Ph.D. Professor Complex Adaptive Systems Lab Department of Electrical Engineering & Computing Systems University of Cincinnati Cincinnati, OH 45221-0030 Phone: (513) 556-4783 Fax: (513) 556-7326 Email: Ali.Minai at uc.edu minaiaa at gmail.com WWW: http://www.ece.uc.edu/~aminai/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From morr9 at vbi.vt.edu Fri Mar 13 00:43:34 2015 From: morr9 at vbi.vt.edu (Mark Orr) Date: Fri, 13 Mar 2015 00:43:34 -0400 Subject: Connectionists: Who introduced the term "Deep Learning" to NNs? In-Reply-To: References: <7F460A0F-E239-4EC7-B3E7-EFA0CBCC9D9C@idsia.ch> <0A2132A5-CEF5-47DE-9FF2-8EE2A5ED8F3B@idsia.ch> Message-ID: <7E45B68D-3CF8-4BDB-8D64-C17CE3023A85@vbi.vt.edu> See a recent book by Stellan Ohlsson from either Oxford or Cambridge Press with the title in question. Mark ------------------------------------------------------- Mark Orr Research Associate Professor Social and Decision Analytics Laboratory Virginia Tech-National Capital Region 900 North Glebe Rd. Arlington, VA 22203 p: 571-858-3116 f: 571-858-3015 morr9 at vbi.vt.edu On Mar 13, 2015, at 12:17 AM, Ali Minai wrote: > Juergen, > > I would say that the instances you point out are not really examples of "deep learning" in the sense the term is being used today. The way we use it now, it refers really to "learning in deep networks", whereas "deep learning" (as opposed to "shallow learning") would mean learning something in a deep sense, e.g., at a conceptual, relational or causal level, rather than in a shallow sense, e.g., at a purely correlational level. This latter sense of "deep learning" may also be implicit in some "deep learning" models, but I don't think the "deep" today refers to this aspect of depth. > > Any discussion of early "deep networks" must surely also refer to Fukushima's Neocognitron. > > Ali > > On Thu, Mar 12, 2015 at 5:35 PM, Juergen Schmidhuber wrote: > Thanks. Hm, sure, ?deep neural nets? are old, and Ivakhnenko?s deep nets worked well even in the 1960s. But what I?d like to know is: who was the first to use the term ?deep learning? in an NN publication? > > Aizenberg et al (2000) wrote about ?deep learning of the features of threshold Boolean functions, one of the most important objects considered in the theory of perceptrons ?? > > Brian Mingus, however, pointed me to a paper by Rina Dechter (1986). Brian wrote: "Deep learning as compared to shallow learning is terminology used in the study of constraint satisfaction. Constraint satisfaction networks then became RBMs. I would argue this is a good basis for the origin of the modern usage. I like this paper for provenance: http://www.aaai.org/Papers/AAAI/1986/AAAI86-029.pdf " > > But perhaps the term occurred even earlier in the NN literature? > > Juergen > > > >> On 12 Mar 2015, at 21:16, Geoffrey Hinton wrote: >> >> I think the current popularity of the term started with the paper by >> Hinton Osindero and Teh in 2006 called "A fast learning algorithm for >> deep belief nets". After this paper there was a lot of talk about >> deep belief nets. In about 2007 the term "deep belief net" started >> changing its meaning and was used (rather sloppily) to refer to deep >> neural nets that were pre-trained as deep belief nets. The term gained >> a lot of popularity because these nets were used to make good acoustic >> models and that triggered the re-introduction of neural nets into >> mainline speech recognizers. People eventually made a clear >> terminological distinction between deep belief nets (DBNs) and deep >> neural nets that were initialized as deep belief nets (DNNs or >> DBN-DNNs). Then they discovered that with large datasets and sensible >> initial scales for the weights the pre-training was not needed and >> they generalized DNNs to any old deep neural net. >> >> Its clearly true that people had previously used the term deep neural >> net but that was not the origin of the resurgence of the term in about >> 2007. >> >> Its pretty obvious by now that deep neural networks of the type that >> people were using in the 1980's work very well when they have enough >> data and enough computation, and its pretty obvious that the deep >> convnets that Yann has been using since about 1987 are deep neural >> nets, so what does it matter where the name came from? Deep neural >> nets are finally living up to their promise so lets all enjoy it. >> >> Geoff >> >> >> >> >> On Thu, Mar 12, 2015 at 1:58 PM, Schmidhuber Juergen wrote: >>> Dear connectionists, >>> >>> to my knowledge, the ancient term "Deep Learning" was introduced to the NN field by Aizenberg & Aizenberg & Vandewalle's book (2000): "Multi-Valued and Universal Binary Neurons: Theory, Learning and Applications." >>> >>> Is anyone aware of older NN papers using it? >>> >>> (Of course, the field itself is much older - Ivakhnenko started his work on deep learning networks in the mid 1960s.) >>> >>> Thanks! >>> >>> Juergen >>> >>> http://people.idsia.ch/~juergen/whatsnew.html > > > > > -- > Ali A. Minai, Ph.D. > Professor > Complex Adaptive Systems Lab > Department of Electrical Engineering & Computing Systems > University of Cincinnati > Cincinnati, OH 45221-0030 > > Phone: (513) 556-4783 > Fax: (513) 556-7326 > Email: Ali.Minai at uc.edu > minaiaa at gmail.com > > WWW: http://www.ece.uc.edu/~aminai/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From juergen at idsia.ch Fri Mar 13 08:57:49 2015 From: juergen at idsia.ch (Juergen Schmidhuber) Date: Fri, 13 Mar 2015 13:57:49 +0100 Subject: Connectionists: Who introduced the term "Deep Learning" to NNs? In-Reply-To: References: <7F460A0F-E239-4EC7-B3E7-EFA0CBCC9D9C@idsia.ch> <0A2132A5-CEF5-47DE-9FF2-8EE2A5ED8F3B@idsia.ch> Message-ID: <3B04D873-4D7C-48B4-9EC0-78A36AA84470@idsia.ch> Ali, thanks! Of course, Fukushima had deep learning nets in the 1970s, and Ivakhnenko had them in the 1960s. But they did not use the term ?deep learning.? Dechter (1986) used the term all over the place, writing not only about ?deep learning?, but also ?deep first-order learning? and ?second-order deep learning.? Dechter?s paper, however, is not really about NNs. My own team started to use such terms only in the new millennium (the GECCO 2005 paper with Faustino Gomez had the word combination ?learn deep? in the title, and was about deep learning in the modern sense). But apparently Aizenberg et al (2000) were really the first to use ?deep learning? in an NN context. Again: my question was not about who invented deep learning half a century ago, only about which publication introduced the terminology to NNs :-) Juergen http://people.idsia.ch/~juergen/deep-learning-overview.html > On 13 Mar 2015, at 05:17, Ali Minai wrote: > > Juergen, > > I would say that the instances you point out are not really examples of "deep learning" in the sense the term is being used today. The way we use it now, it refers really to "learning in deep networks", whereas "deep learning" (as opposed to "shallow learning") would mean learning something in a deep sense, e.g., at a conceptual, relational or causal level, rather than in a shallow sense, e.g., at a purely correlational level. This latter sense of "deep learning" may also be implicit in some "deep learning" models, but I don't think the "deep" today refers to this aspect of depth. > > Any discussion of early "deep networks" must surely also refer to Fukushima's Neocognitron. > > Ali > > On Thu, Mar 12, 2015 at 5:35 PM, Juergen Schmidhuber wrote: > Thanks. Hm, sure, ?deep neural nets? are old, and Ivakhnenko?s deep nets worked well even in the 1960s. But what I?d like to know is: who was the first to use the term ?deep learning? in an NN publication? > > Aizenberg et al (2000) wrote about ?deep learning of the features of threshold Boolean functions, one of the most important objects considered in the theory of perceptrons ?? > > Brian Mingus, however, pointed me to a paper by Rina Dechter (1986). Brian wrote: "Deep learning as compared to shallow learning is terminology used in the study of constraint satisfaction. Constraint satisfaction networks then became RBMs. I would argue this is a good basis for the origin of the modern usage. I like this paper for provenance: http://www.aaai.org/Papers/AAAI/1986/AAAI86-029.pdf " > > But perhaps the term occurred even earlier in the NN literature? > > Juergen >> On 12 Mar 2015, at 21:16, Geoffrey Hinton wrote: >> >> I think the current popularity of the term started with the paper by >> Hinton Osindero and Teh in 2006 called "A fast learning algorithm for >> deep belief nets". After this paper there was a lot of talk about >> deep belief nets. In about 2007 the term "deep belief net" started >> changing its meaning and was used (rather sloppily) to refer to deep >> neural nets that were pre-trained as deep belief nets. The term gained >> a lot of popularity because these nets were used to make good acoustic >> models and that triggered the re-introduction of neural nets into >> mainline speech recognizers. People eventually made a clear >> terminological distinction between deep belief nets (DBNs) and deep >> neural nets that were initialized as deep belief nets (DNNs or >> DBN-DNNs). Then they discovered that with large datasets and sensible >> initial scales for the weights the pre-training was not needed and >> they generalized DNNs to any old deep neural net. >> >> Its clearly true that people had previously used the term deep neural >> net but that was not the origin of the resurgence of the term in about >> 2007. >> >> Its pretty obvious by now that deep neural networks of the type that >> people were using in the 1980's work very well when they have enough >> data and enough computation, and its pretty obvious that the deep >> convnets that Yann has been using since about 1987 are deep neural >> nets, so what does it matter where the name came from? Deep neural >> nets are finally living up to their promise so lets all enjoy it. >> >> Geoff >> On Thu, Mar 12, 2015 at 1:58 PM, Schmidhuber Juergen wrote: >>> Dear connectionists, >>> >>> to my knowledge, the ancient term "Deep Learning" was introduced to the NN field by Aizenberg & Aizenberg & Vandewalle's book (2000): "Multi-Valued and Universal Binary Neurons: Theory, Learning and Applications." >>> >>> Is anyone aware of older NN papers using it? >>> >>> (Of course, the field itself is much older - Ivakhnenko started his work on deep learning networks in the mid 1960s.) >>> >>> Thanks! >>> >>> Juergen >>> >>> http://people.idsia.ch/~juergen/whatsnew.html > From ranzato at cs.toronto.edu Fri Mar 13 10:23:18 2015 From: ranzato at cs.toronto.edu (Marc'Aurelio Ranzato) Date: Fri, 13 Mar 2015 10:23:18 -0400 (EDT) Subject: Connectionists: Who introduced the term "Deep Learning" to NNs? In-Reply-To: <3B04D873-4D7C-48B4-9EC0-78A36AA84470@idsia.ch> References: <7F460A0F-E239-4EC7-B3E7-EFA0CBCC9D9C@idsia.ch> <0A2132A5-CEF5-47DE-9FF2-8EE2A5ED8F3B@idsia.ch> <3B04D873-4D7C-48B4-9EC0-78A36AA84470@idsia.ch> Message-ID: Although the term has been used before, the semantics of what researchers nowadays call "deep learning" really comes from the Hinton Osindero and Teh 2006 paper. By semantics I mean: 1) types of network considered, 2) interpretation of feature hierarchy and 3) training procedure (which was strictly unsupervised followed by supervised finetuning until 2010 or so, and then just simply supervised backprop as in the older literature). It's a re-discovery but it was anything but obvious at that time, and it seems reasoanble to me to give credit to those people who initiated this process/scientific "revolution". Marc'Aurelio On Fri, 13 Mar 2015, Juergen Schmidhuber wrote: > Ali, > > thanks! Of course, Fukushima had deep learning nets in the 1970s, and Ivakhnenko had them in the 1960s. But they did not use the term ?deep learning.? > > Dechter (1986) used the term all over the place, writing not only about ?deep learning?, but also ?deep first-order learning? and ?second-order deep learning.? Dechter?s paper, however, is not really about NNs. > > My own team started to use such terms only in the new millennium (the GECCO 2005 paper with Faustino Gomez had the word combination ?learn deep? in the title, and was about deep learning in the modern sense). But apparently Aizenberg et al (2000) were really the first to use ?deep learning? in an NN context. > > Again: my question was not about who invented deep learning half a century ago, only about which publication introduced the terminology to NNs :-) > > Juergen > > http://people.idsia.ch/~juergen/deep-learning-overview.html > > > >> On 13 Mar 2015, at 05:17, Ali Minai wrote: >> >> Juergen, >> >> I would say that the instances you point out are not really examples of "deep learning" in the sense the term is being used today. The way we use it now, it refers really to "learning in deep networks", whereas "deep learning" (as opposed to "shallow learning") would mean learning something in a deep sense, e.g., at a conceptual, relational or causal level, rather than in a shallow sense, e.g., at a purely correlational level. This latter sense of "deep learning" may also be implicit in some "deep learning" models, but I don't think the "deep" today refers to this aspect of depth. >> >> Any discussion of early "deep networks" must surely also refer to Fukushima's Neocognitron. >> >> Ali > > >> >> On Thu, Mar 12, 2015 at 5:35 PM, Juergen Schmidhuber wrote: > >> Thanks. Hm, sure, ?deep neural nets? are old, and Ivakhnenko?s deep nets worked well even in the 1960s. But what I?d like to know is: who was the first to use the term ?deep learning? in an NN publication? >> >> Aizenberg et al (2000) wrote about ?deep learning of the features of threshold Boolean functions, one of the most important objects considered in the theory of perceptrons ?? >> >> Brian Mingus, however, pointed me to a paper by Rina Dechter (1986). Brian wrote: "Deep learning as compared to shallow learning is terminology used in the study of constraint satisfaction. Constraint satisfaction networks then became RBMs. I would argue this is a good basis for the origin of the modern usage. I like this paper for provenance: http://www.aaai.org/Papers/AAAI/1986/AAAI86-029.pdf " >> >> But perhaps the term occurred even earlier in the NN literature? >> >> Juergen > > > >>> On 12 Mar 2015, at 21:16, Geoffrey Hinton wrote: >>> >>> I think the current popularity of the term started with the paper by >>> Hinton Osindero and Teh in 2006 called "A fast learning algorithm for >>> deep belief nets". After this paper there was a lot of talk about >>> deep belief nets. In about 2007 the term "deep belief net" started >>> changing its meaning and was used (rather sloppily) to refer to deep >>> neural nets that were pre-trained as deep belief nets. The term gained >>> a lot of popularity because these nets were used to make good acoustic >>> models and that triggered the re-introduction of neural nets into >>> mainline speech recognizers. People eventually made a clear >>> terminological distinction between deep belief nets (DBNs) and deep >>> neural nets that were initialized as deep belief nets (DNNs or >>> DBN-DNNs). Then they discovered that with large datasets and sensible >>> initial scales for the weights the pre-training was not needed and >>> they generalized DNNs to any old deep neural net. >>> >>> Its clearly true that people had previously used the term deep neural >>> net but that was not the origin of the resurgence of the term in about >>> 2007. >>> >>> Its pretty obvious by now that deep neural networks of the type that >>> people were using in the 1980's work very well when they have enough >>> data and enough computation, and its pretty obvious that the deep >>> convnets that Yann has been using since about 1987 are deep neural >>> nets, so what does it matter where the name came from? Deep neural >>> nets are finally living up to their promise so lets all enjoy it. >>> >>> Geoff > > > >>> On Thu, Mar 12, 2015 at 1:58 PM, Schmidhuber Juergen wrote: > >>>> Dear connectionists, >>>> >>>> to my knowledge, the ancient term "Deep Learning" was introduced to the NN field by Aizenberg & Aizenberg & Vandewalle's book (2000): "Multi-Valued and Universal Binary Neurons: Theory, Learning and Applications." >>>> >>>> Is anyone aware of older NN papers using it? >>>> >>>> (Of course, the field itself is much older - Ivakhnenko started his work on deep learning networks in the mid 1960s.) >>>> >>>> Thanks! >>>> >>>> Juergen >>>> >>>> http://people.idsia.ch/~juergen/whatsnew.html >> > > > > > From juergen at idsia.ch Fri Mar 13 12:53:28 2015 From: juergen at idsia.ch (Schmidhuber Juergen) Date: Fri, 13 Mar 2015 17:53:28 +0100 Subject: Connectionists: Who introduced the term "Deep Learning" to NNs? In-Reply-To: References: <7F460A0F-E239-4EC7-B3E7-EFA0CBCC9D9C@idsia.ch> <0A2132A5-CEF5-47DE-9FF2-8EE2A5ED8F3B@idsia.ch> <3B04D873-4D7C-48B4-9EC0-78A36AA84470@idsia.ch> Message-ID: <4C4DEB03-76E5-4D75-BA3A-342C871B9D9A@idsia.ch> Sorry, but the ?semantics of what researchers nowadays call deep learning" are much older. In RNNs, the deepest of all NNs, your "strictly unsupervised followed by supervised finetuning? goes back to Schmidhuber's hierarchical deep RNN stacks of 1991 (the neural history compressors). They were largely replaced (still in the 1990s) by deep supervised LSTM RNNs. History repeated itself between 2006 and 2010, when deep unsupervised FNN stacks (kudos to Hinton et al) were replaced by deep standard supervised FNNs, as you pointed out. (It's hardly clear, however, that the re-popularization of supervised NNs wouldn't have occurred without the work on unsupervised NNs.) Antoine Bordes' Google-generated graph seems to indicate that the usage of the term went up right after Aizenberg et al.?s book came out (2000). As Yoshua Bengio pointed out, however, it includes all kinds of ancient usages of ?Deep Learning,? and is not limited to NN-specific usage in the sense of this thread. Again, I am just trying locate the introduction of the term. It's an interesting question in its own right, outside of when the principles of deep learning came into being. Juergen http://people.idsia.ch/~juergen/deep-learning-overview.html > On 13 Mar 2015, at 15:23, Marc'Aurelio Ranzato wrote: > > Although the term has been used before, the semantics of what researchers nowadays call "deep learning" really comes from the Hinton Osindero and Teh 2006 paper. By semantics I mean: 1) types of network considered, 2) interpretation of feature hierarchy and 3) training procedure (which was strictly unsupervised followed by supervised finetuning until 2010 or so, and then just simply supervised backprop as in the older literature). > > It's a re-discovery but it was anything but obvious at that time, and it seems reasoanble to me to give credit to those people who initiated this process/scientific "revolution". > > Marc?Aurelio > On 13 Mar 2015, at 15:15, Yoshua Bengio wrote: > > There has been many many uses of the term 'deep learning' even before (even since 1840), but of course they are mostly not relevant the current use of the term in the machine learning community. See how many in this Google-generated graph (from Google books): > > -- Yoshua Bengio > > P.S. Thanks Antoine Bordes for pointing this out. > On Fri, 13 Mar 2015, Juergen Schmidhuber wrote: > >> Ali, >> >> thanks! Of course, Fukushima had deep learning nets in the 1970s, and Ivakhnenko had them in the 1960s. But they did not use the term ?deep learning.? >> >> Dechter (1986) used the term all over the place, writing not only about ?deep learning?, but also ?deep first-order learning? and ?second-order deep learning.? Dechter?s paper, however, is not really about NNs. >> >> My own team started to use such terms only in the new millennium (the GECCO 2005 paper with Faustino Gomez had the word combination ?learn deep? in the title, and was about deep learning in the modern sense). But apparently Aizenberg et al (2000) were really the first to use ?deep learning? in an NN context. >> >> Again: my question was not about who invented deep learning half a century ago, only about which publication introduced the terminology to NNs :-) >> >> Juergen >> >> http://people.idsia.ch/~juergen/deep-learning-overview.html >> >> >> >>> On 13 Mar 2015, at 05:17, Ali Minai wrote: >>> >>> Juergen, >>> >>> I would say that the instances you point out are not really examples of "deep learning" in the sense the term is being used today. The way we use it now, it refers really to "learning in deep networks", whereas "deep learning" (as opposed to "shallow learning") would mean learning something in a deep sense, e.g., at a conceptual, relational or causal level, rather than in a shallow sense, e.g., at a purely correlational level. This latter sense of "deep learning" may also be implicit in some "deep learning" models, but I don't think the "deep" today refers to this aspect of depth. >>> >>> Any discussion of early "deep networks" must surely also refer to Fukushima's Neocognitron. >>> >>> Ali >> >> >>> >>> On Thu, Mar 12, 2015 at 5:35 PM, Juergen Schmidhuber wrote: >> >>> Thanks. Hm, sure, ?deep neural nets? are old, and Ivakhnenko?s deep nets worked well even in the 1960s. But what I?d like to know is: who was the first to use the term ?deep learning? in an NN publication? >>> >>> Aizenberg et al (2000) wrote about ?deep learning of the features of threshold Boolean functions, one of the most important objects considered in the theory of perceptrons ?? >>> >>> Brian Mingus, however, pointed me to a paper by Rina Dechter (1986). Brian wrote: "Deep learning as compared to shallow learning is terminology used in the study of constraint satisfaction. Constraint satisfaction networks then became RBMs. I would argue this is a good basis for the origin of the modern usage. I like this paper for provenance: http://www.aaai.org/Papers/AAAI/1986/AAAI86-029.pdf " >>> >>> But perhaps the term occurred even earlier in the NN literature? >>> >>> Juergen >> >> >> >>>> On 12 Mar 2015, at 21:16, Geoffrey Hinton wrote: >>>> >>>> I think the current popularity of the term started with the paper by >>>> Hinton Osindero and Teh in 2006 called "A fast learning algorithm for >>>> deep belief nets". After this paper there was a lot of talk about >>>> deep belief nets. In about 2007 the term "deep belief net" started >>>> changing its meaning and was used (rather sloppily) to refer to deep >>>> neural nets that were pre-trained as deep belief nets. The term gained >>>> a lot of popularity because these nets were used to make good acoustic >>>> models and that triggered the re-introduction of neural nets into >>>> mainline speech recognizers. People eventually made a clear >>>> terminological distinction between deep belief nets (DBNs) and deep >>>> neural nets that were initialized as deep belief nets (DNNs or >>>> DBN-DNNs). Then they discovered that with large datasets and sensible >>>> initial scales for the weights the pre-training was not needed and >>>> they generalized DNNs to any old deep neural net. >>>> >>>> Its clearly true that people had previously used the term deep neural >>>> net but that was not the origin of the resurgence of the term in about >>>> 2007. >>>> >>>> Its pretty obvious by now that deep neural networks of the type that >>>> people were using in the 1980's work very well when they have enough >>>> data and enough computation, and its pretty obvious that the deep >>>> convnets that Yann has been using since about 1987 are deep neural >>>> nets, so what does it matter where the name came from? Deep neural >>>> nets are finally living up to their promise so lets all enjoy it. >>>> >>>> Geoff >> >> >> >>>> On Thu, Mar 12, 2015 at 1:58 PM, Schmidhuber Juergen wrote: >> >>>>> Dear connectionists, >>>>> >>>>> to my knowledge, the ancient term "Deep Learning" was introduced to the NN field by Aizenberg & Aizenberg & Vandewalle's book (2000): "Multi-Valued and Universal Binary Neurons: Theory, Learning and Applications." >>>>> >>>>> Is anyone aware of older NN papers using it? >>>>> >>>>> (Of course, the field itself is much older - Ivakhnenko started his work on deep learning networks in the mid 1960s.) >>>>> >>>>> Thanks! >>>>> >>>>> Juergen >>>>> >>>>> http://people.idsia.ch/~juergen/whatsnew.html >>> >> >> >> >> From smart at neuralcorrelate.com Fri Mar 13 14:22:51 2015 From: smart at neuralcorrelate.com (Susana Martinez-Conde) Date: Fri, 13 Mar 2015 14:22:51 -0400 Subject: Connectionists: 2nd call for illusion submissions: the 11th Best Illusion of the Year Contest In-Reply-To: <005c01d05dba$82495a90$86dc0fb0$@neuralcorrelate.com> References: <004b01d05dba$33c4cc60$9b4e6520$@neuralcorrelate.com> <005c01d05dba$82495a90$86dc0fb0$@neuralcorrelate.com> Message-ID: <007d01d05dba$b7b61c90$272255b0$@neuralcorrelate.com> ****2ND CALL FOR ILLUSION SUBMISSIONS: THE WORLD'S 11TH ANNUAL BEST ILLUSION OF THE YEARSM CONTEST**** http://illusionoftheyear.com *** We are happy to announce the 11th edition of world's Best Illusion of the YearSM Contest!!*** Submissions are now welcome! Starting this year, the Best Illusion of the YearSM Contest will bring the creativity of the illusion creator community all around the world. To accomplish this, the Contest will become an annual online event, in which anybody with an internet connection can participate! No matter where you live, you can participate as a contestant, and/or vote for the Top 3 winners yourself! Contestants are invited to submit 1-minute videos featuring novel illusions (unpublished, or published no earlier than 2014) of all sensory modalities (visual, auditory, etc.), in mp4 format. The content of the 1-minute video presenting your illusion is solely up to you, and the only requirement is that it wows all viewers! Some examples include, but are not limited to, a: * Slide presentation, or succession of images, with a voice over (or written text, if you prefer) * Video of yourself describing your illusion * Video of your illusion, expressed in interpretative dance (just kidding -or not-, but you get the idea!) An international panel of impartial judges will rate all the videos and narrow them down to the Top 10. Then, online voters around the world will choose their favorite illusions from the Top 10 finalists. All Top 10 finalists will receive a commemorative plaque. In addition, the Top 3 winners will receive cash prizes: $3,000 for first place; $2,000 for second place, and $1,000 for third place. The Judge Panel will rate illusions according to: * Significance to our understanding of the human mind and brain * Simplicity of the description * Sheer beauty * Counterintuitive quality * Spectacularity Submissions will be held in strict confidence by the Judge Panel and the authors/creators will retain copyright of their works. The Top 10 illusions will be posted online to allow worldwide voting. As with submitting your work to any conference, participating in the Best Illusion of the YearSM Contest does not preclude you from also submitting your work for publication elsewhere. Illusions submitted to previous editions of the Contest can be re-submitted to the 2015 Contest, as long as they meet the above requirements and were not among the Top 10 illusions in previous years. You can send your 1-minute video to Dr. Susana Martinez-Conde via email ( smart at neuralcorrelate.com) until April 1, 2015. On behalf of the Executive Board of the Neural Correlate Society: Jose-Manuel Alonso, Stephen Macknik, Susana Martinez-Conde, Luis Martinez, Xoana Troncoso, Peter Tse ---------------------------------------------------------------- Susana Martinez-Conde, PhD Professor of Ophthalmology, Neurology, and Physiology & Pharmacology Director, Laboratory of Integrative Neuroscience Scholar, Empire Innovator Program State University of New York (SUNY) Downstate Medical Center 450 Clarkson Ave, Brooklyn NY 11203, USA Email: smart at neuralcorrelate.com Phone: +1 718-270-4520 http://smc.neuralcorrelate.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From jose at psychology.rutgers.edu Fri Mar 13 14:36:10 2015 From: jose at psychology.rutgers.edu (Stephen =?ISO-8859-1?Q?Jos=E9?= Hanson) Date: Fri, 13 Mar 2015 14:36:10 -0400 Subject: Connectionists: Who introduced the term "Deep Learning" to NNs? Message-ID: <1426271770.2667.16.camel@edison> I think there is a confusion here about "Deep Learning". I think Deep Learning is not so much about the words "deep" and "learning", but the architecture of the learning system--or neural network. Those of us who were doing Auto-Encoders back in the 80s, had tried many time to increase the number of hidden layers, especially doing some sort of language task or grammer task. I was particularly inspired to try this after seeing Yann's early work on conv-nets, in which he employed many layers. Also Geoff had a "kinship network" that consisted of 6 layers or so.. (cog sci,'86), ....so we had all tried to train auto-encoders with multiple layers.. and miserably failed using back-propagations with sigmoidal activation functions... So the actual concept of Deep Learning is more about this representational compression and abstraction (not so much theory about this part, I think). So again, really not about "deep" or "learning".. etc.. I think searching for these words in documents from the 60s will miss the critical aspects of the multiple layers of representational structure that is extracted and used to generalize. This is really an extension of stuff that was happening in the mid to late 1980s. Cheers Steve -- Stephen Jos? Hanson Director RUBIC (Rutgers Brain Imaging Center) Professor of Psychology Member of Cognitive Science Center (NB) Member EE Graduate Program (NB) Member CS Graduate Program (NB) Rutgers University email: jose at rubic.rutgers.edu web: psychology.rutgers.edu/~jose lab: www.rumba.rutgers.edu fax: 866-434-7959 voice: 973-353-3313 (RUBIC) -------------- next part -------------- An HTML attachment was scrubbed... URL: From movellan at mplab.ucsd.edu Fri Mar 13 14:02:04 2015 From: movellan at mplab.ucsd.edu (MPLab) Date: Fri, 13 Mar 2015 11:02:04 -0700 Subject: Connectionists: Who introduced the term "Deep Learning" to NNs? In-Reply-To: <4C4DEB03-76E5-4D75-BA3A-342C871B9D9A@idsia.ch> References: <7F460A0F-E239-4EC7-B3E7-EFA0CBCC9D9C@idsia.ch> <0A2132A5-CEF5-47DE-9FF2-8EE2A5ED8F3B@idsia.ch> <3B04D873-4D7C-48B4-9EC0-78A36AA84470@idsia.ch> <4C4DEB03-76E5-4D75-BA3A-342C871B9D9A@idsia.ch> Message-ID: <2A26E9B7-C920-41C5-B7C1-CEDE3584CFDA@mplab.ucsd.edu> The fishermen in the north of Spain have been using Deep Networks for centuries. Their contribution should be recognized even though they use the Spanish version (Redes Profundas) rather than the English version of the term. -Javier > On Mar 13, 2015, at 9:53 AM, Schmidhuber Juergen wrote: > > Sorry, but the ?semantics of what researchers nowadays call deep learning" are much older. In RNNs, the deepest of all NNs, your "strictly unsupervised followed by supervised finetuning? goes back to Schmidhuber's hierarchical deep RNN stacks of 1991 (the neural history compressors). They were largely replaced (still in the 1990s) by deep supervised LSTM RNNs. History repeated itself between 2006 and 2010, when deep unsupervised FNN stacks (kudos to Hinton et al) were replaced by deep standard supervised FNNs, as you pointed out. (It's hardly clear, however, that the re-popularization of supervised NNs wouldn't have occurred without the work on unsupervised NNs.) > > Antoine Bordes' Google-generated graph seems to indicate that the usage of the term went up right after Aizenberg et al.?s book came out (2000). As Yoshua Bengio pointed out, however, it includes all kinds of ancient usages of ?Deep Learning,? and is not limited to NN-specific usage in the sense of this thread. > > Again, I am just trying locate the introduction of the term. It's an interesting question in its own right, outside of when the principles of deep learning came into being. > > Juergen > > http://people.idsia.ch/~juergen/deep-learning-overview.html > > >> On 13 Mar 2015, at 15:23, Marc'Aurelio Ranzato wrote: >> >> Although the term has been used before, the semantics of what researchers nowadays call "deep learning" really comes from the Hinton Osindero and Teh 2006 paper. By semantics I mean: 1) types of network considered, 2) interpretation of feature hierarchy and 3) training procedure (which was strictly unsupervised followed by supervised finetuning until 2010 or so, and then just simply supervised backprop as in the older literature). >> >> It's a re-discovery but it was anything but obvious at that time, and it seems reasoanble to me to give credit to those people who initiated this process/scientific "revolution". >> >> Marc?Aurelio > > >> On 13 Mar 2015, at 15:15, Yoshua Bengio wrote: >> >> There has been many many uses of the term 'deep learning' even before (even since 1840), but of course they are mostly not relevant the current use of the term in the machine learning community. See how many in this Google-generated graph (from Google books): >> >> -- Yoshua Bengio >> >> P.S. Thanks Antoine Bordes for pointing this out. > > >> On Fri, 13 Mar 2015, Juergen Schmidhuber wrote: >> >>> Ali, >>> >>> thanks! Of course, Fukushima had deep learning nets in the 1970s, and Ivakhnenko had them in the 1960s. But they did not use the term ?deep learning.? >>> >>> Dechter (1986) used the term all over the place, writing not only about ?deep learning?, but also ?deep first-order learning? and ?second-order deep learning.? Dechter?s paper, however, is not really about NNs. >>> >>> My own team started to use such terms only in the new millennium (the GECCO 2005 paper with Faustino Gomez had the word combination ?learn deep? in the title, and was about deep learning in the modern sense). But apparently Aizenberg et al (2000) were really the first to use ?deep learning? in an NN context. >>> >>> Again: my question was not about who invented deep learning half a century ago, only about which publication introduced the terminology to NNs :-) >>> >>> Juergen >>> >>> http://people.idsia.ch/~juergen/deep-learning-overview.html >>> >>> >>> >>>> On 13 Mar 2015, at 05:17, Ali Minai wrote: >>>> >>>> Juergen, >>>> >>>> I would say that the instances you point out are not really examples of "deep learning" in the sense the term is being used today. The way we use it now, it refers really to "learning in deep networks", whereas "deep learning" (as opposed to "shallow learning") would mean learning something in a deep sense, e.g., at a conceptual, relational or causal level, rather than in a shallow sense, e.g., at a purely correlational level. This latter sense of "deep learning" may also be implicit in some "deep learning" models, but I don't think the "deep" today refers to this aspect of depth. >>>> >>>> Any discussion of early "deep networks" must surely also refer to Fukushima's Neocognitron. >>>> >>>> Ali >>> >>> >>>> >>>> On Thu, Mar 12, 2015 at 5:35 PM, Juergen Schmidhuber wrote: >>> >>>> Thanks. Hm, sure, ?deep neural nets? are old, and Ivakhnenko?s deep nets worked well even in the 1960s. But what I?d like to know is: who was the first to use the term ?deep learning? in an NN publication? >>>> >>>> Aizenberg et al (2000) wrote about ?deep learning of the features of threshold Boolean functions, one of the most important objects considered in the theory of perceptrons ?? >>>> >>>> Brian Mingus, however, pointed me to a paper by Rina Dechter (1986). Brian wrote: "Deep learning as compared to shallow learning is terminology used in the study of constraint satisfaction. Constraint satisfaction networks then became RBMs. I would argue this is a good basis for the origin of the modern usage. I like this paper for provenance: http://www.aaai.org/Papers/AAAI/1986/AAAI86-029.pdf " >>>> >>>> But perhaps the term occurred even earlier in the NN literature? >>>> >>>> Juergen >>> >>> >>> >>>>> On 12 Mar 2015, at 21:16, Geoffrey Hinton wrote: >>>>> >>>>> I think the current popularity of the term started with the paper by >>>>> Hinton Osindero and Teh in 2006 called "A fast learning algorithm for >>>>> deep belief nets". After this paper there was a lot of talk about >>>>> deep belief nets. In about 2007 the term "deep belief net" started >>>>> changing its meaning and was used (rather sloppily) to refer to deep >>>>> neural nets that were pre-trained as deep belief nets. The term gained >>>>> a lot of popularity because these nets were used to make good acoustic >>>>> models and that triggered the re-introduction of neural nets into >>>>> mainline speech recognizers. People eventually made a clear >>>>> terminological distinction between deep belief nets (DBNs) and deep >>>>> neural nets that were initialized as deep belief nets (DNNs or >>>>> DBN-DNNs). Then they discovered that with large datasets and sensible >>>>> initial scales for the weights the pre-training was not needed and >>>>> they generalized DNNs to any old deep neural net. >>>>> >>>>> Its clearly true that people had previously used the term deep neural >>>>> net but that was not the origin of the resurgence of the term in about >>>>> 2007. >>>>> >>>>> Its pretty obvious by now that deep neural networks of the type that >>>>> people were using in the 1980's work very well when they have enough >>>>> data and enough computation, and its pretty obvious that the deep >>>>> convnets that Yann has been using since about 1987 are deep neural >>>>> nets, so what does it matter where the name came from? Deep neural >>>>> nets are finally living up to their promise so lets all enjoy it. >>>>> >>>>> Geoff >>> >>> >>> >>>>> On Thu, Mar 12, 2015 at 1:58 PM, Schmidhuber Juergen wrote: >>> >>>>>> Dear connectionists, >>>>>> >>>>>> to my knowledge, the ancient term "Deep Learning" was introduced to the NN field by Aizenberg & Aizenberg & Vandewalle's book (2000): "Multi-Valued and Universal Binary Neurons: Theory, Learning and Applications." >>>>>> >>>>>> Is anyone aware of older NN papers using it? >>>>>> >>>>>> (Of course, the field itself is much older - Ivakhnenko started his work on deep learning networks in the mid 1960s.) >>>>>> >>>>>> Thanks! >>>>>> >>>>>> Juergen >>>>>> >>>>>> http://people.idsia.ch/~juergen/whatsnew.html >>>> >>> >>> >>> >>> > > > From v.steuber at herts.ac.uk Fri Mar 13 13:36:23 2015 From: v.steuber at herts.ac.uk (Steuber, Volker) Date: Fri, 13 Mar 2015 17:36:23 +0000 Subject: Connectionists: Senior lectureship in computer science (machine learning / biocomputation) In-Reply-To: <18EF08266D889C41A14D1099C7102CE2BDFC6EC5F0@UH-MAILSTOR.herts.ac.uk> References: <18EF08266D889C41A14D1099C7102CE2BDFC6EC5F0@UH-MAILSTOR.herts.ac.uk> Message-ID: <18EF08266D889C41A14D1099C7102CE2C9C4D860D6@UH-MAILSTOR.herts.ac.uk> Senior Lecturer in Computer Science School of Computer Science University of Hertfordshire Hatfield, Hertfordshire UK Salary: ?37,394 to ?47,328 per annum depending on skills and experience FTE: Full time position Duration of contract: Permanent Closing date: 26 March 2015 Applications are invited for two posts of Senior Lecturer in the School of Computer Science at the University of Hertfordshire. The successful candidate will be expected to contribute to the School's teaching and curriculum development activities, and to strengthen its research activities. We are looking to recruit specifically computer scientists with specialist interests in machine learning related to biocomputation (including computational neuroscience), with the flexibility to teach across mainstream topics in computer science. The School has an international reputation for teaching and research, with 58 academic staff, 20 adjunct lecturer staff, and 65 research students and postdoctoral research staff. With a history going back to 1958, the School teaches one of the largest cohorts of undergraduate students in the UK, and also delivers a thriving online computer science degree programme. The University of Hertfordshire is situated in Hatfield, in the green belt just north of London. The person appointed will be expected to contribute to learning and teaching relevant to core computer science topics, participate in curriculum review and development, design and develop new modules, and supervise student projects at all levels. The appointee will strengthen the research culture in the School by pursuing research as part of a larger research team, seeking external funding, publishing papers, supervising research students, and participating in commercial activity as appropriate. Preference will be given to candidates who can contribute to teaching and research in databases or machine learning. You must hold a PhD (or equivalent) in a relevant subject, possess excellent communication skills in English and the ability to teach at undergraduate and postgraduate level. It is desirable that candidates have a track record of publication, external research funding, collaboration across disciplines, experience of different types of assessment and higher education quality assurance. They should also have the ability to play a role in the routine running of the School of Computer Science. The University is required to meet UKVI visa regulations. Applicants who do not currently have the right to work in the UK will have to satisfy UKVI regulations before they can be appointed. Application should be made through http://www.herts.ac.uk/contact-us/jobs-and-vacancies/academic-vacancies (reference 012476). For informal enquiries contact Prof William Clocksin (Dean of School, w.clocksin at herts.ac.uk) or Dr Volker Steuber (Head of the Biocomputation Research Group, v.steuber at herts.ac.uk). From l.s.smith at cs.stir.ac.uk Sat Mar 14 06:07:46 2015 From: l.s.smith at cs.stir.ac.uk (Leslie Smith) Date: Sat, 14 Mar 2015 10:07:46 +0000 Subject: Connectionists: Who introduced the term "Deep Learning" to NNs? In-Reply-To: <4C4DEB03-76E5-4D75-BA3A-342C871B9D9A@idsia.ch> References: <7F460A0F-E239-4EC7-B3E7-EFA0CBCC9D9C@idsia.ch> <0A2132A5-CEF5-47DE-9FF2-8EE2A5ED8F3B@idsia.ch> <3B04D873-4D7C-48B4-9EC0-78A36AA84470@idsia.ch> <4C4DEB03-76E5-4D75-BA3A-342C871B9D9A@idsia.ch> Message-ID: <23AD645A-6432-4D45-A771-2536334D3839@cs.stir.ac.uk> Dear all: Though it doesn?t quite go back to the fishermen of Northern Spain, it?s worth noting that multi-layer (and hence deep) nets are discussed in some detail by Rosenblatt in his ?Principles of Neurodynamics? (1962 Spartan Books), specifically section 15, page 313 et seq, Clearly, he did not use the term ?deep learning?: he talks about ?adaptive pre terminal networks? when referring to alterations of weights in earlier layers. ?Leslie Smith On 13 Mar 2015, at 16:53, Schmidhuber Juergen wrote: > Sorry, but the ?semantics of what researchers nowadays call deep learning" are much older. In RNNs, the deepest of all NNs, your "strictly unsupervised followed by supervised finetuning? goes back to Schmidhuber's hierarchical deep RNN stacks of 1991 (the neural history compressors). They were largely replaced (still in the 1990s) by deep supervised LSTM RNNs. History repeated itself between 2006 and 2010, when deep unsupervised FNN stacks (kudos to Hinton et al) were replaced by deep standard supervised FNNs, as you pointed out. (It's hardly clear, however, that the re-popularization of supervised NNs wouldn't have occurred without the work on unsupervised NNs.) > > Antoine Bordes' Google-generated graph seems to indicate that the usage of the term went up right after Aizenberg et al.?s book came out (2000). As Yoshua Bengio pointed out, however, it includes all kinds of ancient usages of ?Deep Learning,? and is not limited to NN-specific usage in the sense of this thread. > > Again, I am just trying locate the introduction of the term. It's an interesting question in its own right, outside of when the principles of deep learning came into being. > > Juergen Leslie Smith l.s.smith at cs.stir.ac.uk Professor of Computing, Computing Science and Mathematics, University of Stirling Stirling FK9 4LA, Scotland, UK +44 (0) 1786 467435 -- The University of Stirling has been ranked in the top 12 of UK universities for graduate employment*. 94% of our 2012 graduates were in work and/or further study within six months of graduation. *The Telegraph The University of Stirling is a charity registered in Scotland, number SC 011159. -------------- next part -------------- An HTML attachment was scrubbed... URL: From juergen at idsia.ch Sat Mar 14 11:14:17 2015 From: juergen at idsia.ch (Juergen Schmidhuber) Date: Sat, 14 Mar 2015 16:14:17 +0100 Subject: Connectionists: Who introduced the term "Deep Learning" to NNs? In-Reply-To: <23AD645A-6432-4D45-A771-2536334D3839@cs.stir.ac.uk> References: <7F460A0F-E239-4EC7-B3E7-EFA0CBCC9D9C@idsia.ch> <0A2132A5-CEF5-47DE-9FF2-8EE2A5ED8F3B@idsia.ch> <3B04D873-4D7C-48B4-9EC0-78A36AA84470@idsia.ch> <4C4DEB03-76E5-4D75-BA3A-342C871B9D9A@idsia.ch> <23AD645A-6432-4D45-A771-2536334D3839@cs.stir.ac.uk> Message-ID: <9D705531-C23B-4828-8CEE-08A41E14D533@idsia.ch> Thanks, Leslie! The title of this thread is about syntax, but everybody wants to talk about semantics ? You mention Rosenblatt (1962), who heavily refers to Joseph?s even earlier work. His pre-terminal connections in section 15 use a simple type of unsupervised learning. To my knowledge, however, the first working, general, deep learning algorithms for multilayer perceptrons are due to Ivakhnenko et al (1965-). Still in use even in the new millennium! Lots of references to deep learning networks of the 1960s and 1970s can be found in the survey, especially in Sec. 5.3, 5.4, 5.5. (Shallow learning networks since 1795 are mentioned in Sec. 5.1.) http://people.idsia.ch/~juergen/deep-learning-overview.html The nets of Spanish fishers are deep, but they don?t learn, otherwise I?d have cited them :-) Juergen > On 14 Mar 2015, at 11:07, Leslie Smith wrote: > > Dear all: > > Though it doesn?t quite go back to the fishermen of Northern Spain, it?s worth noting that multi-layer (and hence deep) nets are discussed in some detail by Rosenblatt in his ?Principles of Neurodynamics? (1962 Spartan Books), specifically section 15, page 313 et seq, > > Clearly, he did not use the term ?deep learning?: he talks about ?adaptive pre terminal networks? when referring to alterations of weights in earlier layers. > > ?Leslie Smith From sml at essex.ac.uk Sun Mar 15 14:22:29 2015 From: sml at essex.ac.uk (Lucas, Simon M) Date: Sun, 15 Mar 2015 18:22:29 +0000 Subject: Connectionists: Who introduced the term "Deep Learning" to NNs? In-Reply-To: <4C4DEB03-76E5-4D75-BA3A-342C871B9D9A@idsia.ch> References: <7F460A0F-E239-4EC7-B3E7-EFA0CBCC9D9C@idsia.ch> <0A2132A5-CEF5-47DE-9FF2-8EE2A5ED8F3B@idsia.ch> <3B04D873-4D7C-48B4-9EC0-78A36AA84470@idsia.ch> <4C4DEB03-76E5-4D75-BA3A-342C871B9D9A@idsia.ch> Message-ID: Hi Juergen, In your excellent survey there is one type of deep learning that you've missed out, but I'd argue should be included for completeness: work on Grammar-Based Neural Networks. Baker (1979) showed how the Forward / Backward algorithm used to train HMMs could be generalised to train stochastic context free grammars (representing structures of arbitrary depth). He called this the Inside / Outside algorithm. Problem: the algorithm scaled O(n^3 m^3) where n = length of input, m = number of non-terminals. (Lorraine Dodd had a nice paper in Speech '88 showing how the I/O algorithm could be used to learn the spelling structure of English words) What's this got to do with Deep NNs? Lucas (PhD Thesis, 1991) and Lucas and Damper, Connection Science, 1990 showed how these grammars could be mapped on to multi-layered neural nets, and the training / recognition algorithms could be made more efficient by specialising the structure in particular ways. This area would be worth another look given the massively more powerful machines we have now, and also using different activation functions. Simon M. Lucas, Connectionist Architectures for Syntactic Pattern Recognition", PhD Thesis, University of Southampton (1991). Simon M. Lucas and Robert I. Damper, Syntactic neural networks, Connection Science (1990), volume 2, pages: 199 -- 225. Lorraine Dodd, Grammatical inference for automatic speech recognition, an application of the inside/outside algorithm to the spelling of English words, Proceedings of Speech '88, pages 1061 - 1068, Institute of Acoustics, Edinburgh. Baker's I/O algorithm: http://en.wikipedia.org/wiki/Inside%E2%80%93outside_algorithm Best wishes, Simon Lucas Professor Simon Lucas Head of School Computer Science and Electronic Engineering University of Essex, UK -----Original Message----- From: Connectionists [mailto:connectionists-bounces at mailman.srv.cs.cmu.edu] On Behalf Of Schmidhuber Juergen Sent: 13 March 2015 16:53 To: Connectionists List Subject: Re: Connectionists: Who introduced the term "Deep Learning" to NNs? Sorry, but the ?semantics of what researchers nowadays call deep learning" are much older. In RNNs, the deepest of all NNs, your "strictly unsupervised followed by supervised finetuning? goes back to Schmidhuber's hierarchical deep RNN stacks of 1991 (the neural history compressors). They were largely replaced (still in the 1990s) by deep supervised LSTM RNNs. History repeated itself between 2006 and 2010, when deep unsupervised FNN stacks (kudos to Hinton et al) were replaced by deep standard supervised FNNs, as you pointed out. (It's hardly clear, however, that the re-popularization of supervised NNs wouldn't have occurred without the work on unsupervised NNs.) Antoine Bordes' Google-generated graph seems to indicate that the usage of the term went up right after Aizenberg et al.?s book came out (2000). As Yoshua Bengio pointed out, however, it includes all kinds of ancient usages of ?Deep Learning,? and is not limited to NN-specific usage in the sense of this thread. Again, I am just trying locate the introduction of the term. It's an interesting question in its own right, outside of when the principles of deep learning came into being. Juergen http://people.idsia.ch/~juergen/deep-learning-overview.html > On 13 Mar 2015, at 15:23, Marc'Aurelio Ranzato wrote: > > Although the term has been used before, the semantics of what researchers nowadays call "deep learning" really comes from the Hinton Osindero and Teh 2006 paper. By semantics I mean: 1) types of network considered, 2) interpretation of feature hierarchy and 3) training procedure (which was strictly unsupervised followed by supervised finetuning until 2010 or so, and then just simply supervised backprop as in the older literature). > > It's a re-discovery but it was anything but obvious at that time, and it seems reasoanble to me to give credit to those people who initiated this process/scientific "revolution". > > Marc?Aurelio > On 13 Mar 2015, at 15:15, Yoshua Bengio wrote: > > There has been many many uses of the term 'deep learning' even before (even since 1840), but of course they are mostly not relevant the current use of the term in the machine learning community. See how many in this Google-generated graph (from Google books): > > -- Yoshua Bengio > > P.S. Thanks Antoine Bordes for pointing this out. > On Fri, 13 Mar 2015, Juergen Schmidhuber wrote: > >> Ali, >> >> thanks! Of course, Fukushima had deep learning nets in the 1970s, and Ivakhnenko had them in the 1960s. But they did not use the term ?deep learning.? >> >> Dechter (1986) used the term all over the place, writing not only about ?deep learning?, but also ?deep first-order learning? and ?second-order deep learning.? Dechter?s paper, however, is not really about NNs. >> >> My own team started to use such terms only in the new millennium (the GECCO 2005 paper with Faustino Gomez had the word combination ?learn deep? in the title, and was about deep learning in the modern sense). But apparently Aizenberg et al (2000) were really the first to use ?deep learning? in an NN context. >> >> Again: my question was not about who invented deep learning half a >> century ago, only about which publication introduced the terminology >> to NNs :-) >> >> Juergen >> >> http://people.idsia.ch/~juergen/deep-learning-overview.html >> >> >> >>> On 13 Mar 2015, at 05:17, Ali Minai wrote: >>> >>> Juergen, >>> >>> I would say that the instances you point out are not really examples of "deep learning" in the sense the term is being used today. The way we use it now, it refers really to "learning in deep networks", whereas "deep learning" (as opposed to "shallow learning") would mean learning something in a deep sense, e.g., at a conceptual, relational or causal level, rather than in a shallow sense, e.g., at a purely correlational level. This latter sense of "deep learning" may also be implicit in some "deep learning" models, but I don't think the "deep" today refers to this aspect of depth. >>> >>> Any discussion of early "deep networks" must surely also refer to Fukushima's Neocognitron. >>> >>> Ali >> >> >>> >>> On Thu, Mar 12, 2015 at 5:35 PM, Juergen Schmidhuber wrote: >> >>> Thanks. Hm, sure, ?deep neural nets? are old, and Ivakhnenko?s deep nets worked well even in the 1960s. But what I?d like to know is: who was the first to use the term ?deep learning? in an NN publication? >>> >>> Aizenberg et al (2000) wrote about ?deep learning of the features of threshold Boolean functions, one of the most important objects considered in the theory of perceptrons ?? >>> >>> Brian Mingus, however, pointed me to a paper by Rina Dechter (1986). Brian wrote: "Deep learning as compared to shallow learning is terminology used in the study of constraint satisfaction. Constraint satisfaction networks then became RBMs. I would argue this is a good basis for the origin of the modern usage. I like this paper for provenance: http://www.aaai.org/Papers/AAAI/1986/AAAI86-029.pdf " >>> >>> But perhaps the term occurred even earlier in the NN literature? >>> >>> Juergen >> >> >> >>>> On 12 Mar 2015, at 21:16, Geoffrey Hinton wrote: >>>> >>>> I think the current popularity of the term started with the paper >>>> by Hinton Osindero and Teh in 2006 called "A fast learning >>>> algorithm for deep belief nets". After this paper there was a lot >>>> of talk about deep belief nets. In about 2007 the term "deep >>>> belief net" started changing its meaning and was used (rather >>>> sloppily) to refer to deep neural nets that were pre-trained as >>>> deep belief nets. The term gained a lot of popularity because these >>>> nets were used to make good acoustic models and that triggered the >>>> re-introduction of neural nets into mainline speech recognizers. >>>> People eventually made a clear terminological distinction between >>>> deep belief nets (DBNs) and deep neural nets that were initialized >>>> as deep belief nets (DNNs or DBN-DNNs). Then they discovered that >>>> with large datasets and sensible initial scales for the weights the >>>> pre-training was not needed and they generalized DNNs to any old deep neural net. >>>> >>>> Its clearly true that people had previously used the term deep >>>> neural net but that was not the origin of the resurgence of the >>>> term in about 2007. >>>> >>>> Its pretty obvious by now that deep neural networks of the type >>>> that people were using in the 1980's work very well when they have >>>> enough data and enough computation, and its pretty obvious that the >>>> deep convnets that Yann has been using since about 1987 are deep >>>> neural nets, so what does it matter where the name came from? Deep >>>> neural nets are finally living up to their promise so lets all enjoy it. >>>> >>>> Geoff >> >> >> >>>> On Thu, Mar 12, 2015 at 1:58 PM, Schmidhuber Juergen wrote: >> >>>>> Dear connectionists, >>>>> >>>>> to my knowledge, the ancient term "Deep Learning" was introduced to the NN field by Aizenberg & Aizenberg & Vandewalle's book (2000): "Multi-Valued and Universal Binary Neurons: Theory, Learning and Applications." >>>>> >>>>> Is anyone aware of older NN papers using it? >>>>> >>>>> (Of course, the field itself is much older - Ivakhnenko started >>>>> his work on deep learning networks in the mid 1960s.) >>>>> >>>>> Thanks! >>>>> >>>>> Juergen >>>>> >>>>> http://people.idsia.ch/~juergen/whatsnew.html >>> >> >> >> >> From juergen at idsia.ch Sun Mar 15 19:17:30 2015 From: juergen at idsia.ch (Juergen Schmidhuber) Date: Mon, 16 Mar 2015 00:17:30 +0100 Subject: Connectionists: Who introduced the term "Deep Learning" to NNs? In-Reply-To: References: <7F460A0F-E239-4EC7-B3E7-EFA0CBCC9D9C@idsia.ch> <0A2132A5-CEF5-47DE-9FF2-8EE2A5ED8F3B@idsia.ch> <3B04D873-4D7C-48B4-9EC0-78A36AA84470@idsia.ch> <4C4DEB03-76E5-4D75-BA3A-342C871B9D9A@idsia.ch> Message-ID: <52F7ADD8-95E5-4610-A6DB-DDEFB0EE802C@idsia.ch> Thanks a lot, Simon! This is relevant indeed. You should have told me last year when I had a series of drafts under massive open online peer review here on the connectionists mailing list :-) Of course, I?ll keep it in mind for future updates. Sec. 4.3 and 6.5 of the survey, however, do mention the famous earlier grammar-based work: Multiple levels of more and more abstract data representations can be learned by methods of syntactic pattern recognition (Fu, 1977) such as grammar induction, which discovers hierarchies of formal rules to model observations. Fu, K. S. (1977). Syntactic Pattern Recognition and Applications. Berlin, Springer. Best wishes, Juergen > On 15 Mar 2015, at 19:22, Lucas, Simon M wrote: > > Hi Juergen, > > In your excellent survey there is one type of deep > learning that you've missed out, but I'd argue should > be included for completeness: work on Grammar-Based > Neural Networks. > > Baker (1979) showed how the Forward / Backward > algorithm used to train HMMs could be generalised > to train stochastic context free grammars (representing > structures of arbitrary depth). He called this the Inside / Outside > algorithm. Problem: the algorithm scaled O(n^3 m^3) > where n = length of input, m = number of non-terminals. > > (Lorraine Dodd had a nice paper in Speech '88 showing > how the I/O algorithm could be used to learn the spelling > structure of English words) > > What's this got to do with Deep NNs? > > Lucas (PhD Thesis, 1991) and Lucas and Damper, Connection Science, 1990 > showed how these grammars could be mapped on to multi-layered neural > nets, and the training / recognition algorithms could be made more efficient > by specialising the structure in particular ways. > > This area would be worth another look given the massively more > powerful machines we have now, and also using different activation > functions. > > Simon M. Lucas, Connectionist Architectures for Syntactic Pattern Recognition", PhD Thesis, University of Southampton (1991). > Simon M. Lucas and Robert I. Damper, Syntactic neural networks, Connection Science (1990), volume 2, pages: 199 -- 225. > Lorraine Dodd, Grammatical inference for automatic speech recognition, an application of the inside/outside > algorithm to the spelling of English words, Proceedings of Speech '88, pages 1061 - 1068, Institute of Acoustics, Edinburgh. > > Baker's I/O algorithm: http://en.wikipedia.org/wiki/Inside%E2%80%93outside_algorithm > > > Best wishes, > > Simon Lucas > > > Professor Simon Lucas > Head of School > Computer Science and Electronic Engineering > University of Essex, UK > > > > > -----Original Message----- > From: Connectionists [mailto:connectionists-bounces at mailman.srv.cs.cmu.edu] On Behalf Of Schmidhuber Juergen > Sent: 13 March 2015 16:53 > To: Connectionists List > Subject: Re: Connectionists: Who introduced the term "Deep Learning" to NNs? > > Sorry, but the ?semantics of what researchers nowadays call deep learning" are much older. In RNNs, the deepest of all NNs, your "strictly unsupervised followed by supervised finetuning? goes back to Schmidhuber's hierarchical deep RNN stacks of 1991 (the neural history compressors). They were largely replaced (still in the 1990s) by deep supervised LSTM RNNs. History repeated itself between 2006 and 2010, when deep unsupervised FNN stacks (kudos to Hinton et al) were replaced by deep standard supervised FNNs, as you pointed out. (It's hardly clear, however, that the re-popularization of supervised NNs wouldn't have occurred without the work on unsupervised NNs.) > > Antoine Bordes' Google-generated graph seems to indicate that the usage of the term went up right after Aizenberg et al.?s book came out (2000). As Yoshua Bengio pointed out, however, it includes all kinds of ancient usages of ?Deep Learning,? and is not limited to NN-specific usage in the sense of this thread. > > Again, I am just trying locate the introduction of the term. It's an interesting question in its own right, outside of when the principles of deep learning came into being. > > Juergen > > http://people.idsia.ch/~juergen/deep-learning-overview.html > > >> On 13 Mar 2015, at 15:23, Marc'Aurelio Ranzato wrote: >> >> Although the term has been used before, the semantics of what researchers nowadays call "deep learning" really comes from the Hinton Osindero and Teh 2006 paper. By semantics I mean: 1) types of network considered, 2) interpretation of feature hierarchy and 3) training procedure (which was strictly unsupervised followed by supervised finetuning until 2010 or so, and then just simply supervised backprop as in the older literature). >> >> It's a re-discovery but it was anything but obvious at that time, and it seems reasoanble to me to give credit to those people who initiated this process/scientific "revolution". >> >> Marc?Aurelio > > >> On 13 Mar 2015, at 15:15, Yoshua Bengio wrote: >> >> There has been many many uses of the term 'deep learning' even before (even since 1840), but of course they are mostly not relevant the current use of the term in the machine learning community. See how many in this Google-generated graph (from Google books): >> >> -- Yoshua Bengio >> >> P.S. Thanks Antoine Bordes for pointing this out. > > >> On Fri, 13 Mar 2015, Juergen Schmidhuber wrote: >> >>> Ali, >>> >>> thanks! Of course, Fukushima had deep learning nets in the 1970s, and Ivakhnenko had them in the 1960s. But they did not use the term ?deep learning.? >>> >>> Dechter (1986) used the term all over the place, writing not only about ?deep learning?, but also ?deep first-order learning? and ?second-order deep learning.? Dechter?s paper, however, is not really about NNs. >>> >>> My own team started to use such terms only in the new millennium (the GECCO 2005 paper with Faustino Gomez had the word combination ?learn deep? in the title, and was about deep learning in the modern sense). But apparently Aizenberg et al (2000) were really the first to use ?deep learning? in an NN context. >>> >>> Again: my question was not about who invented deep learning half a >>> century ago, only about which publication introduced the terminology >>> to NNs :-) >>> >>> Juergen >>> >>> http://people.idsia.ch/~juergen/deep-learning-overview.html >>> >>> >>> >>>> On 13 Mar 2015, at 05:17, Ali Minai wrote: >>>> >>>> Juergen, >>>> >>>> I would say that the instances you point out are not really examples of "deep learning" in the sense the term is being used today. The way we use it now, it refers really to "learning in deep networks", whereas "deep learning" (as opposed to "shallow learning") would mean learning something in a deep sense, e.g., at a conceptual, relational or causal level, rather than in a shallow sense, e.g., at a purely correlational level. This latter sense of "deep learning" may also be implicit in some "deep learning" models, but I don't think the "deep" today refers to this aspect of depth. >>>> >>>> Any discussion of early "deep networks" must surely also refer to Fukushima's Neocognitron. >>>> >>>> Ali >>> >>> >>>> >>>> On Thu, Mar 12, 2015 at 5:35 PM, Juergen Schmidhuber wrote: >>> >>>> Thanks. Hm, sure, ?deep neural nets? are old, and Ivakhnenko?s deep nets worked well even in the 1960s. But what I?d like to know is: who was the first to use the term ?deep learning? in an NN publication? >>>> >>>> Aizenberg et al (2000) wrote about ?deep learning of the features of threshold Boolean functions, one of the most important objects considered in the theory of perceptrons ?? >>>> >>>> Brian Mingus, however, pointed me to a paper by Rina Dechter (1986). Brian wrote: "Deep learning as compared to shallow learning is terminology used in the study of constraint satisfaction. Constraint satisfaction networks then became RBMs. I would argue this is a good basis for the origin of the modern usage. I like this paper for provenance: http://www.aaai.org/Papers/AAAI/1986/AAAI86-029.pdf " >>>> >>>> But perhaps the term occurred even earlier in the NN literature? >>>> >>>> Juergen >>> >>> >>> >>>>> On 12 Mar 2015, at 21:16, Geoffrey Hinton wrote: >>>>> >>>>> I think the current popularity of the term started with the paper >>>>> by Hinton Osindero and Teh in 2006 called "A fast learning >>>>> algorithm for deep belief nets". After this paper there was a lot >>>>> of talk about deep belief nets. In about 2007 the term "deep >>>>> belief net" started changing its meaning and was used (rather >>>>> sloppily) to refer to deep neural nets that were pre-trained as >>>>> deep belief nets. The term gained a lot of popularity because these >>>>> nets were used to make good acoustic models and that triggered the >>>>> re-introduction of neural nets into mainline speech recognizers. >>>>> People eventually made a clear terminological distinction between >>>>> deep belief nets (DBNs) and deep neural nets that were initialized >>>>> as deep belief nets (DNNs or DBN-DNNs). Then they discovered that >>>>> with large datasets and sensible initial scales for the weights the >>>>> pre-training was not needed and they generalized DNNs to any old deep neural net. >>>>> >>>>> Its clearly true that people had previously used the term deep >>>>> neural net but that was not the origin of the resurgence of the >>>>> term in about 2007. >>>>> >>>>> Its pretty obvious by now that deep neural networks of the type >>>>> that people were using in the 1980's work very well when they have >>>>> enough data and enough computation, and its pretty obvious that the >>>>> deep convnets that Yann has been using since about 1987 are deep >>>>> neural nets, so what does it matter where the name came from? Deep >>>>> neural nets are finally living up to their promise so lets all enjoy it. >>>>> >>>>> Geoff >>> >>> >>> >>>>> On Thu, Mar 12, 2015 at 1:58 PM, Schmidhuber Juergen wrote: >>> >>>>>> Dear connectionists, >>>>>> >>>>>> to my knowledge, the ancient term "Deep Learning" was introduced to the NN field by Aizenberg & Aizenberg & Vandewalle's book (2000): "Multi-Valued and Universal Binary Neurons: Theory, Learning and Applications." >>>>>> >>>>>> Is anyone aware of older NN papers using it? >>>>>> >>>>>> (Of course, the field itself is much older - Ivakhnenko started >>>>>> his work on deep learning networks in the mid 1960s.) >>>>>> >>>>>> Thanks! >>>>>> >>>>>> Juergen >>>>>> >>>>>> http://people.idsia.ch/~juergen/whatsnew.html >>>> >>> >>> >>> >>> > > From juergen at idsia.ch Mon Mar 16 04:10:58 2015 From: juergen at idsia.ch (Juergen Schmidhuber) Date: Mon, 16 Mar 2015 09:10:58 +0100 Subject: Connectionists: Who introduced the term "Deep Learning" to NNs? In-Reply-To: <55064839.7070906@icsi.berkeley.edu> References: <7F460A0F-E239-4EC7-B3E7-EFA0CBCC9D9C@idsia.ch> <0A2132A5-CEF5-47DE-9FF2-8EE2A5ED8F3B@idsia.ch> <3B04D873-4D7C-48B4-9EC0-78A36AA84470@idsia.ch> <4C4DEB03-76E5-4D75-BA3A-342C871B9D9A@idsia.ch> <55064839.7070906@icsi.berkeley.edu> Message-ID: Thanks, Andreas, for this important pointer! Even earlier related work on grammars and NNs is mentioned in Sec. 6.7 of the survey: Instead of evolving large neural networks (NNs) directly (Sec. 6.6), one can sometimes greatly reduce the search space by evolving compact encodings of deep NNs, e.g., through Lindenmeyer Systems (Lindenmayer, 1968; Jacob et al., 1994), graph rewriting (Kitano, 1990), ... Lindenmayer, A. (1968). Mathematical models for cellular interaction in development. J. Theoret. Biology, 18:280?315. Jacob, C., Lindenmayer, A., and Rozenberg, G. (1994). Genetic L-System Programming. In Parallel Problem Solving from Nature III, Lecture Notes in Computer Science. Kitano, H. (1990). Designing neural networks using genetic algorithms with graph generation system. Complex Systems, 4:461?476. BTW, at the current AMA (Ask Me Anything) at reddit I have a brief summary of the insights related to the original title of this thread: http://www.reddit.com/r/MachineLearning/comments/2xcyrl/i_am_j%C3%BCrgen_schmidhuber_ama/cpfrrnr Cheers, Juergen > On 16 Mar 2015, at 04:04, Andreas Stolcke wrote: > > > For more work from the early 1990s that aims to bridge the gap between symbolic grammars and neurally-inspired models see > Syntactic category formation with vector space grammars (Cogsci conference, 1991). Since grammars potentially generate deep structures I suppose you can say that what you get is a case of "deep nets". > > Cheers, > > Andreas > > On 3/15/2015 11:22 AM, Lucas, Simon M wrote: >> Hi Juergen, >> >> In your excellent survey there is one type of deep >> learning that you've missed out, but I'd argue should >> be included for completeness: work on Grammar-Based >> Neural Networks. >> >> Baker (1979) showed how the Forward / Backward >> algorithm used to train HMMs could be generalised >> to train stochastic context free grammars (representing >> structures of arbitrary depth). He called this the Inside / Outside >> algorithm. Problem: the algorithm scaled O(n^3 m^3) >> where n = length of input, m = number of non-terminals. >> >> (Lorraine Dodd had a nice paper in Speech '88 showing >> how the I/O algorithm could be used to learn the spelling >> structure of English words) >> >> What's this got to do with Deep NNs? >> >> Lucas (PhD Thesis, 1991) and Lucas and Damper, Connection Science, 1990 >> showed how these grammars could be mapped on to multi-layered neural >> nets, and the training / recognition algorithms could be made more efficient >> by specialising the structure in particular ways. >> >> This area would be worth another look given the massively more >> powerful machines we have now, and also using different activation >> functions. >> >> Simon M. Lucas, Connectionist Architectures for Syntactic Pattern Recognition", PhD Thesis, University of Southampton (1991). >> Simon M. Lucas and Robert I. Damper, Syntactic neural networks, Connection Science (1990), volume 2, pages: 199 -- 225. >> Lorraine Dodd, Grammatical inference for automatic speech recognition, an application of the inside/outside >> algorithm to the spelling of English words, Proceedings of Speech '88, pages 1061 - 1068, Institute of Acoustics, Edinburgh. >> >> Baker's I/O algorithm: >> http://en.wikipedia.org/wiki/Inside%E2%80%93outside_algorithm >> >> >> >> Best wishes, >> >> Simon Lucas >> >> >> Professor Simon Lucas >> Head of School >> Computer Science and Electronic Engineering >> University of Essex, UK >> >> >> >> >> -----Original Message----- >> From: Connectionists [ >> mailto:connectionists-bounces at mailman.srv.cs.cmu.edu >> ] On Behalf Of Schmidhuber Juergen >> Sent: 13 March 2015 16:53 >> To: Connectionists List >> Subject: Re: Connectionists: Who introduced the term "Deep Learning" to NNs? >> >> Sorry, but the ?semantics of what researchers nowadays call deep learning" are much older. In RNNs, the deepest of all NNs, your "strictly unsupervised followed by supervised finetuning? goes back to Schmidhuber's hierarchical deep RNN stacks of 1991 (the neural history compressors). They were largely replaced (still in the 1990s) by deep supervised LSTM RNNs. History repeated itself between 2006 and 2010, when deep unsupervised FNN stacks (kudos to Hinton et al) were replaced by deep standard supervised FNNs, as you pointed out. (It's hardly clear, however, that the re-popularization of supervised NNs wouldn't have occurred without the work on unsupervised NNs.) >> >> Antoine Bordes' Google-generated graph seems to indicate that the usage of the term went up right after Aizenberg et al.?s book came out (2000). As Yoshua Bengio pointed out, however, it includes all kinds of ancient usages of ?Deep Learning,? and is not limited to NN-specific usage in the sense of this thread. >> >> Again, I am just trying locate the introduction of the term. It's an interesting question in its own right, outside of when the principles of deep learning came into being. >> >> Juergen >> >> >> http://people.idsia.ch/~juergen/deep-learning-overview.html >> >> >> >> >>> On 13 Mar 2015, at 15:23, Marc'Aurelio Ranzato >>> wrote: >>> >>> Although the term has been used before, the semantics of what researchers nowadays call "deep learning" really comes from the Hinton Osindero and Teh 2006 paper. By semantics I mean: 1) types of network considered, 2) interpretation of feature hierarchy and 3) training procedure (which was strictly unsupervised followed by supervised finetuning until 2010 or so, and then just simply supervised backprop as in the older literature). >>> >>> It's a re-discovery but it was anything but obvious at that time, and it seems reasoanble to me to give credit to those people who initiated this process/scientific "revolution". >>> >>> Marc?Aurelio >>> >> >>> On 13 Mar 2015, at 15:15, Yoshua Bengio >>> wrote: >>> >>> There has been many many uses of the term 'deep learning' even before (even since 1840), but of course they are mostly not relevant the current use of the term in the machine learning community. See how many in this Google-generated graph (from Google books): >>> >>> -- Yoshua Bengio >>> >>> P.S. Thanks Antoine Bordes for pointing this out. >>> >> >>> On Fri, 13 Mar 2015, Juergen Schmidhuber wrote: >>> >>> >>>> Ali, >>>> >>>> thanks! Of course, Fukushima had deep learning nets in the 1970s, and Ivakhnenko had them in the 1960s. But they did not use the term ?deep learning.? >>>> >>>> Dechter (1986) used the term all over the place, writing not only about ?deep learning?, but also ?deep first-order learning? and ?second-order deep learning.? Dechter?s paper, however, is not really about NNs. >>>> >>>> My own team started to use such terms only in the new millennium (the GECCO 2005 paper with Faustino Gomez had the word combination ?learn deep? in the title, and was about deep learning in the modern sense). But apparently Aizenberg et al (2000) were really the first to use ?deep learning? in an NN context. >>>> >>>> Again: my question was not about who invented deep learning half a >>>> century ago, only about which publication introduced the terminology >>>> to NNs :-) >>>> >>>> Juergen >>>> >>>> >>>> http://people.idsia.ch/~juergen/deep-learning-overview.html >>>> >>>> >>>> >>>> >>>> >>>>> On 13 Mar 2015, at 05:17, Ali Minai >>>>> wrote: >>>>> >>>>> Juergen, >>>>> >>>>> I would say that the instances you point out are not really examples of "deep learning" in the sense the term is being used today. The way we use it now, it refers really to "learning in deep networks", whereas "deep learning" (as opposed to "shallow learning") would mean learning something in a deep sense, e.g., at a conceptual, relational or causal level, rather than in a shallow sense, e.g., at a purely correlational level. This latter sense of "deep learning" may also be implicit in some "deep learning" models, but I don't think the "deep" today refers to this aspect of depth. >>>>> >>>>> Any discussion of early "deep networks" must surely also refer to Fukushima's Neocognitron. >>>>> >>>>> Ali >>>>> >>>> >>>>> On Thu, Mar 12, 2015 at 5:35 PM, Juergen Schmidhuber >>>>> wrote: >>>>> >>>>> Thanks. Hm, sure, ?deep neural nets? are old, and Ivakhnenko?s deep nets worked well even in the 1960s. But what I?d like to know is: who was the first to use the term ?deep learning? in an NN publication? >>>>> >>>>> Aizenberg et al (2000) wrote about ?deep learning of the features of threshold Boolean functions, one of the most important objects considered in the theory of perceptrons ?? >>>>> >>>>> Brian Mingus, however, pointed me to a paper by Rina Dechter (1986). Brian wrote: "Deep learning as compared to shallow learning is terminology used in the study of constraint satisfaction. Constraint satisfaction networks then became RBMs. I would argue this is a good basis for the origin of the modern usage. I like this paper for provenance: >>>>> http://www.aaai.org/Papers/AAAI/1986/AAAI86-029.pdf >>>>> " >>>>> >>>>> But perhaps the term occurred even earlier in the NN literature? >>>>> >>>>> Juergen >>>>> >>>> >>>> >>>> >>>>>> On 12 Mar 2015, at 21:16, Geoffrey Hinton >>>>>> wrote: >>>>>> >>>>>> I think the current popularity of the term started with the paper >>>>>> by Hinton Osindero and Teh in 2006 called "A fast learning >>>>>> algorithm for deep belief nets". After this paper there was a lot >>>>>> of talk about deep belief nets. In about 2007 the term "deep >>>>>> belief net" started changing its meaning and was used (rather >>>>>> sloppily) to refer to deep neural nets that were pre-trained as >>>>>> deep belief nets. The term gained a lot of popularity because these >>>>>> nets were used to make good acoustic models and that triggered the >>>>>> re-introduction of neural nets into mainline speech recognizers. >>>>>> People eventually made a clear terminological distinction between >>>>>> deep belief nets (DBNs) and deep neural nets that were initialized >>>>>> as deep belief nets (DNNs or DBN-DNNs). Then they discovered that >>>>>> with large datasets and sensible initial scales for the weights the >>>>>> pre-training was not needed and they generalized DNNs to any old deep neural net. >>>>>> >>>>>> Its clearly true that people had previously used the term deep >>>>>> neural net but that was not the origin of the resurgence of the >>>>>> term in about 2007. >>>>>> >>>>>> Its pretty obvious by now that deep neural networks of the type >>>>>> that people were using in the 1980's work very well when they have >>>>>> enough data and enough computation, and its pretty obvious that the >>>>>> deep convnets that Yann has been using since about 1987 are deep >>>>>> neural nets, so what does it matter where the name came from? Deep >>>>>> neural nets are finally living up to their promise so lets all enjoy it. >>>>>> >>>>>> Geoff >>>>>> >>>> >>>> >>>> >>>>>> On Thu, Mar 12, 2015 at 1:58 PM, Schmidhuber Juergen >>>>>> wrote: >>>>>> >>>>>>> Dear connectionists, >>>>>>> >>>>>>> to my knowledge, the ancient term "Deep Learning" was introduced to the NN field by Aizenberg & Aizenberg & Vandewalle's book (2000): "Multi-Valued and Universal Binary Neurons: Theory, Learning and Applications." >>>>>>> >>>>>>> Is anyone aware of older NN papers using it? >>>>>>> >>>>>>> (Of course, the field itself is much older - Ivakhnenko started >>>>>>> his work on deep learning networks in the mid 1960s.) >>>>>>> >>>>>>> Thanks! >>>>>>> >>>>>>> Juergen >>>>>>> >>>>>>> >>>>>>> http://people.idsia.ch/~juergen/whatsnew.html >>>> >>>> >>>> >>>> >> >> >> > From stolcke at icsi.berkeley.edu Sun Mar 15 23:04:25 2015 From: stolcke at icsi.berkeley.edu (Andreas Stolcke) Date: Sun, 15 Mar 2015 20:04:25 -0700 Subject: Connectionists: Who introduced the term "Deep Learning" to NNs? In-Reply-To: References: <7F460A0F-E239-4EC7-B3E7-EFA0CBCC9D9C@idsia.ch> <0A2132A5-CEF5-47DE-9FF2-8EE2A5ED8F3B@idsia.ch> <3B04D873-4D7C-48B4-9EC0-78A36AA84470@idsia.ch> <4C4DEB03-76E5-4D75-BA3A-342C871B9D9A@idsia.ch> Message-ID: <55064839.7070906@icsi.berkeley.edu> For more work from the early 1990s that aims to bridge the gap between symbolic grammars and neurally-inspired models see Syntactic category formation with vector space grammars (Cogsci conference, 1991). Since grammars potentially generate deep structures I suppose you can say that what you get is a case of "deep nets". Cheers, Andreas On 3/15/2015 11:22 AM, Lucas, Simon M wrote: > Hi Juergen, > > In your excellent survey there is one type of deep > learning that you've missed out, but I'd argue should > be included for completeness: work on Grammar-Based > Neural Networks. > > Baker (1979) showed how the Forward / Backward > algorithm used to train HMMs could be generalised > to train stochastic context free grammars (representing > structures of arbitrary depth). He called this the Inside / Outside > algorithm. Problem: the algorithm scaled O(n^3 m^3) > where n = length of input, m = number of non-terminals. > > (Lorraine Dodd had a nice paper in Speech '88 showing > how the I/O algorithm could be used to learn the spelling > structure of English words) > > What's this got to do with Deep NNs? > > Lucas (PhD Thesis, 1991) and Lucas and Damper, Connection Science, 1990 > showed how these grammars could be mapped on to multi-layered neural > nets, and the training / recognition algorithms could be made more efficient > by specialising the structure in particular ways. > > This area would be worth another look given the massively more > powerful machines we have now, and also using different activation > functions. > > Simon M. Lucas, Connectionist Architectures for Syntactic Pattern Recognition", PhD Thesis, University of Southampton (1991). > Simon M. Lucas and Robert I. Damper, Syntactic neural networks, Connection Science (1990), volume 2, pages: 199 -- 225. > Lorraine Dodd, Grammatical inference for automatic speech recognition, an application of the inside/outside > algorithm to the spelling of English words, Proceedings of Speech '88, pages 1061 - 1068, Institute of Acoustics, Edinburgh. > > Baker's I/O algorithm: http://en.wikipedia.org/wiki/Inside%E2%80%93outside_algorithm > > > Best wishes, > > Simon Lucas > > > Professor Simon Lucas > Head of School > Computer Science and Electronic Engineering > University of Essex, UK > > > > > -----Original Message----- > From: Connectionists [mailto:connectionists-bounces at mailman.srv.cs.cmu.edu] On Behalf Of Schmidhuber Juergen > Sent: 13 March 2015 16:53 > To: Connectionists List > Subject: Re: Connectionists: Who introduced the term "Deep Learning" to NNs? > > Sorry, but the ?semantics of what researchers nowadays call deep learning" are much older. In RNNs, the deepest of all NNs, your "strictly unsupervised followed by supervised finetuning? goes back to Schmidhuber's hierarchical deep RNN stacks of 1991 (the neural history compressors). They were largely replaced (still in the 1990s) by deep supervised LSTM RNNs. History repeated itself between 2006 and 2010, when deep unsupervised FNN stacks (kudos to Hinton et al) were replaced by deep standard supervised FNNs, as you pointed out. (It's hardly clear, however, that the re-popularization of supervised NNs wouldn't have occurred without the work on unsupervised NNs.) > > Antoine Bordes' Google-generated graph seems to indicate that the usage of the term went up right after Aizenberg et al.?s book came out (2000). As Yoshua Bengio pointed out, however, it includes all kinds of ancient usages of ?Deep Learning,? and is not limited to NN-specific usage in the sense of this thread. > > Again, I am just trying locate the introduction of the term. It's an interesting question in its own right, outside of when the principles of deep learning came into being. > > Juergen > > http://people.idsia.ch/~juergen/deep-learning-overview.html > > >> On 13 Mar 2015, at 15:23, Marc'Aurelio Ranzato wrote: >> >> Although the term has been used before, the semantics of what researchers nowadays call "deep learning" really comes from the Hinton Osindero and Teh 2006 paper. By semantics I mean: 1) types of network considered, 2) interpretation of feature hierarchy and 3) training procedure (which was strictly unsupervised followed by supervised finetuning until 2010 or so, and then just simply supervised backprop as in the older literature). >> >> It's a re-discovery but it was anything but obvious at that time, and it seems reasoanble to me to give credit to those people who initiated this process/scientific "revolution". >> >> Marc?Aurelio > >> On 13 Mar 2015, at 15:15, Yoshua Bengio wrote: >> >> There has been many many uses of the term 'deep learning' even before (even since 1840), but of course they are mostly not relevant the current use of the term in the machine learning community. See how many in this Google-generated graph (from Google books): >> >> -- Yoshua Bengio >> >> P.S. Thanks Antoine Bordes for pointing this out. > >> On Fri, 13 Mar 2015, Juergen Schmidhuber wrote: >> >>> Ali, >>> >>> thanks! Of course, Fukushima had deep learning nets in the 1970s, and Ivakhnenko had them in the 1960s. But they did not use the term ?deep learning.? >>> >>> Dechter (1986) used the term all over the place, writing not only about ?deep learning?, but also ?deep first-order learning? and ?second-order deep learning.? Dechter?s paper, however, is not really about NNs. >>> >>> My own team started to use such terms only in the new millennium (the GECCO 2005 paper with Faustino Gomez had the word combination ?learn deep? in the title, and was about deep learning in the modern sense). But apparently Aizenberg et al (2000) were really the first to use ?deep learning? in an NN context. >>> >>> Again: my question was not about who invented deep learning half a >>> century ago, only about which publication introduced the terminology >>> to NNs :-) >>> >>> Juergen >>> >>> http://people.idsia.ch/~juergen/deep-learning-overview.html >>> >>> >>> >>>> On 13 Mar 2015, at 05:17, Ali Minai wrote: >>>> >>>> Juergen, >>>> >>>> I would say that the instances you point out are not really examples of "deep learning" in the sense the term is being used today. The way we use it now, it refers really to "learning in deep networks", whereas "deep learning" (as opposed to "shallow learning") would mean learning something in a deep sense, e.g., at a conceptual, relational or causal level, rather than in a shallow sense, e.g., at a purely correlational level. This latter sense of "deep learning" may also be implicit in some "deep learning" models, but I don't think the "deep" today refers to this aspect of depth. >>>> >>>> Any discussion of early "deep networks" must surely also refer to Fukushima's Neocognitron. >>>> >>>> Ali >>> >>>> On Thu, Mar 12, 2015 at 5:35 PM, Juergen Schmidhuber wrote: >>>> Thanks. Hm, sure, ?deep neural nets? are old, and Ivakhnenko?s deep nets worked well even in the 1960s. But what I?d like to know is: who was the first to use the term ?deep learning? in an NN publication? >>>> >>>> Aizenberg et al (2000) wrote about ?deep learning of the features of threshold Boolean functions, one of the most important objects considered in the theory of perceptrons ?? >>>> >>>> Brian Mingus, however, pointed me to a paper by Rina Dechter (1986). Brian wrote: "Deep learning as compared to shallow learning is terminology used in the study of constraint satisfaction. Constraint satisfaction networks then became RBMs. I would argue this is a good basis for the origin of the modern usage. I like this paper for provenance: http://www.aaai.org/Papers/AAAI/1986/AAAI86-029.pdf " >>>> >>>> But perhaps the term occurred even earlier in the NN literature? >>>> >>>> Juergen >>> >>> >>>>> On 12 Mar 2015, at 21:16, Geoffrey Hinton wrote: >>>>> >>>>> I think the current popularity of the term started with the paper >>>>> by Hinton Osindero and Teh in 2006 called "A fast learning >>>>> algorithm for deep belief nets". After this paper there was a lot >>>>> of talk about deep belief nets. In about 2007 the term "deep >>>>> belief net" started changing its meaning and was used (rather >>>>> sloppily) to refer to deep neural nets that were pre-trained as >>>>> deep belief nets. The term gained a lot of popularity because these >>>>> nets were used to make good acoustic models and that triggered the >>>>> re-introduction of neural nets into mainline speech recognizers. >>>>> People eventually made a clear terminological distinction between >>>>> deep belief nets (DBNs) and deep neural nets that were initialized >>>>> as deep belief nets (DNNs or DBN-DNNs). Then they discovered that >>>>> with large datasets and sensible initial scales for the weights the >>>>> pre-training was not needed and they generalized DNNs to any old deep neural net. >>>>> >>>>> Its clearly true that people had previously used the term deep >>>>> neural net but that was not the origin of the resurgence of the >>>>> term in about 2007. >>>>> >>>>> Its pretty obvious by now that deep neural networks of the type >>>>> that people were using in the 1980's work very well when they have >>>>> enough data and enough computation, and its pretty obvious that the >>>>> deep convnets that Yann has been using since about 1987 are deep >>>>> neural nets, so what does it matter where the name came from? Deep >>>>> neural nets are finally living up to their promise so lets all enjoy it. >>>>> >>>>> Geoff >>> >>> >>>>> On Thu, Mar 12, 2015 at 1:58 PM, Schmidhuber Juergen wrote: >>>>>> Dear connectionists, >>>>>> >>>>>> to my knowledge, the ancient term "Deep Learning" was introduced to the NN field by Aizenberg & Aizenberg & Vandewalle's book (2000): "Multi-Valued and Universal Binary Neurons: Theory, Learning and Applications." >>>>>> >>>>>> Is anyone aware of older NN papers using it? >>>>>> >>>>>> (Of course, the field itself is much older - Ivakhnenko started >>>>>> his work on deep learning networks in the mid 1960s.) >>>>>> >>>>>> Thanks! >>>>>> >>>>>> Juergen >>>>>> >>>>>> http://people.idsia.ch/~juergen/whatsnew.html >>> >>> >>> > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From ASIM.ROY at asu.edu Mon Mar 16 04:50:33 2015 From: ASIM.ROY at asu.edu (Asim Roy) Date: Mon, 16 Mar 2015 08:50:33 +0000 Subject: Connectionists: Who introduced the term "Deep Learning" to NNs? In-Reply-To: References: <7F460A0F-E239-4EC7-B3E7-EFA0CBCC9D9C@idsia.ch> <0A2132A5-CEF5-47DE-9FF2-8EE2A5ED8F3B@idsia.ch> <3B04D873-4D7C-48B4-9EC0-78A36AA84470@idsia.ch> <4C4DEB03-76E5-4D75-BA3A-342C871B9D9A@idsia.ch> <55064839.7070906@icsi.berkeley.edu> Message-ID: <4AD8F84F0AA4E1448BD8131BA7E55EB423D050EF@exmbw02.asurite.ad.asu.edu> All, Juergen Schmidhuber is doing a tutorial and a workshop on deep learning, in addition to a plenary talk, at the INNS Big Data conference in San Francisco, August 8-10, 2015. There will be presentations by researchers from Google and Microsoft at the deep learning workshop and it should be a big day to get more insights into deep learning. Hope to see many of you at the conference. Here's the website for further info: www.innsbigdata.org . The paper submission deadline is March 22. Asim Roy Arizona State University Tempe, AZ 85287, USA www.lifeboat.com/ex/bios.asim.roy INNS Big Data Section: http://www.inns.org/big-data-section -----Original Message----- From: Connectionists [mailto:connectionists-bounces at mailman.srv.cs.cmu.edu] On Behalf Of Juergen Schmidhuber Sent: Monday, March 16, 2015 1:11 AM To: Connectionists List Subject: Re: Connectionists: Who introduced the term "Deep Learning" to NNs? Thanks, Andreas, for this important pointer! Even earlier related work on grammars and NNs is mentioned in Sec. 6.7 of the survey: Instead of evolving large neural networks (NNs) directly (Sec. 6.6), one can sometimes greatly reduce the search space by evolving compact encodings of deep NNs, e.g., through Lindenmeyer Systems (Lindenmayer, 1968; Jacob et al., 1994), graph rewriting (Kitano, 1990), ... Lindenmayer, A. (1968). Mathematical models for cellular interaction in development. J. Theoret. Biology, 18:280?315. Jacob, C., Lindenmayer, A., and Rozenberg, G. (1994). Genetic L-System Programming. In Parallel Problem Solving from Nature III, Lecture Notes in Computer Science. Kitano, H. (1990). Designing neural networks using genetic algorithms with graph generation system. Complex Systems, 4:461?476. BTW, at the current AMA (Ask Me Anything) at reddit I have a brief summary of the insights related to the original title of this thread: http://www.reddit.com/r/MachineLearning/comments/2xcyrl/i_am_j%C3%BCrgen_schmidhuber_ama/cpfrrnr Cheers, Juergen > On 16 Mar 2015, at 04:04, Andreas Stolcke wrote: > > > For more work from the early 1990s that aims to bridge the gap between > symbolic grammars and neurally-inspired models see Syntactic category formation with vector space grammars (Cogsci conference, 1991). Since grammars potentially generate deep structures I suppose you can say that what you get is a case of "deep nets". > > Cheers, > > Andreas > > On 3/15/2015 11:22 AM, Lucas, Simon M wrote: >> Hi Juergen, >> >> In your excellent survey there is one type of deep learning that >> you've missed out, but I'd argue should be included for completeness: >> work on Grammar-Based Neural Networks. >> >> Baker (1979) showed how the Forward / Backward algorithm used to >> train HMMs could be generalised to train stochastic context free >> grammars (representing structures of arbitrary depth). He called >> this the Inside / Outside algorithm. Problem: the algorithm scaled >> O(n^3 m^3) where n = length of input, m = number of non-terminals. >> >> (Lorraine Dodd had a nice paper in Speech '88 showing how the I/O >> algorithm could be used to learn the spelling structure of English >> words) >> >> What's this got to do with Deep NNs? >> >> Lucas (PhD Thesis, 1991) and Lucas and Damper, Connection Science, >> 1990 showed how these grammars could be mapped on to multi-layered >> neural nets, and the training / recognition algorithms could be made more efficient >> by specialising the structure in particular ways. >> >> This area would be worth another look given the massively more >> powerful machines we have now, and also using different activation >> functions. >> >> Simon M. Lucas, Connectionist Architectures for Syntactic Pattern Recognition", PhD Thesis, University of Southampton (1991). >> Simon M. Lucas and Robert I. Damper, Syntactic neural networks, Connection Science (1990), volume 2, pages: 199 -- 225. >> Lorraine Dodd, Grammatical inference for automatic speech >> recognition, an application of the inside/outside algorithm to the spelling of English words, Proceedings of Speech '88, pages 1061 - 1068, Institute of Acoustics, Edinburgh. >> >> Baker's I/O algorithm: >> http://en.wikipedia.org/wiki/Inside%E2%80%93outside_algorithm >> >> >> >> Best wishes, >> >> Simon Lucas >> >> >> Professor Simon Lucas >> Head of School >> Computer Science and Electronic Engineering University of Essex, UK >> >> >> >> >> -----Original Message----- >> From: Connectionists [ >> mailto:connectionists-bounces at mailman.srv.cs.cmu.edu >> ] On Behalf Of Schmidhuber Juergen >> Sent: 13 March 2015 16:53 >> To: Connectionists List >> Subject: Re: Connectionists: Who introduced the term "Deep Learning" to NNs? >> >> Sorry, but the ?semantics of what researchers nowadays call deep >> learning" are much older. In RNNs, the deepest of all NNs, your >> "strictly unsupervised followed by supervised finetuning? goes back >> to Schmidhuber's hierarchical deep RNN stacks of 1991 (the neural >> history compressors). They were largely replaced (still in the 1990s) >> by deep supervised LSTM RNNs. History repeated itself between 2006 >> and 2010, when deep unsupervised FNN stacks (kudos to Hinton et al) >> were replaced by deep standard supervised FNNs, as you pointed out. >> (It's hardly clear, however, that the re-popularization of supervised >> NNs wouldn't have occurred without the work on unsupervised NNs.) >> >> Antoine Bordes' Google-generated graph seems to indicate that the usage of the term went up right after Aizenberg et al.?s book came out (2000). As Yoshua Bengio pointed out, however, it includes all kinds of ancient usages of ?Deep Learning,? and is not limited to NN-specific usage in the sense of this thread. >> >> Again, I am just trying locate the introduction of the term. It's an interesting question in its own right, outside of when the principles of deep learning came into being. >> >> Juergen >> >> >> http://people.idsia.ch/~juergen/deep-learning-overview.html >> >> >> >> >>> On 13 Mar 2015, at 15:23, Marc'Aurelio Ranzato >>> >>> wrote: >>> >>> Although the term has been used before, the semantics of what researchers nowadays call "deep learning" really comes from the Hinton Osindero and Teh 2006 paper. By semantics I mean: 1) types of network considered, 2) interpretation of feature hierarchy and 3) training procedure (which was strictly unsupervised followed by supervised finetuning until 2010 or so, and then just simply supervised backprop as in the older literature). >>> >>> It's a re-discovery but it was anything but obvious at that time, and it seems reasoanble to me to give credit to those people who initiated this process/scientific "revolution". >>> >>> Marc?Aurelio >>> >> >>> On 13 Mar 2015, at 15:15, Yoshua Bengio >>> wrote: >>> >>> There has been many many uses of the term 'deep learning' even before (even since 1840), but of course they are mostly not relevant the current use of the term in the machine learning community. See how many in this Google-generated graph (from Google books): >>> >>> -- Yoshua Bengio >>> >>> P.S. Thanks Antoine Bordes for pointing this out. >>> >> >>> On Fri, 13 Mar 2015, Juergen Schmidhuber wrote: >>> >>> >>>> Ali, >>>> >>>> thanks! Of course, Fukushima had deep learning nets in the 1970s, and Ivakhnenko had them in the 1960s. But they did not use the term ?deep learning.? >>>> >>>> Dechter (1986) used the term all over the place, writing not only about ?deep learning?, but also ?deep first-order learning? and ?second-order deep learning.? Dechter?s paper, however, is not really about NNs. >>>> >>>> My own team started to use such terms only in the new millennium (the GECCO 2005 paper with Faustino Gomez had the word combination ?learn deep? in the title, and was about deep learning in the modern sense). But apparently Aizenberg et al (2000) were really the first to use ?deep learning? in an NN context. >>>> >>>> Again: my question was not about who invented deep learning half a >>>> century ago, only about which publication introduced the >>>> terminology to NNs :-) >>>> >>>> Juergen >>>> >>>> >>>> http://people.idsia.ch/~juergen/deep-learning-overview.html >>>> >>>> >>>> >>>> >>>> >>>>> On 13 Mar 2015, at 05:17, Ali Minai >>>>> wrote: >>>>> >>>>> Juergen, >>>>> >>>>> I would say that the instances you point out are not really examples of "deep learning" in the sense the term is being used today. The way we use it now, it refers really to "learning in deep networks", whereas "deep learning" (as opposed to "shallow learning") would mean learning something in a deep sense, e.g., at a conceptual, relational or causal level, rather than in a shallow sense, e.g., at a purely correlational level. This latter sense of "deep learning" may also be implicit in some "deep learning" models, but I don't think the "deep" today refers to this aspect of depth. >>>>> >>>>> Any discussion of early "deep networks" must surely also refer to Fukushima's Neocognitron. >>>>> >>>>> Ali >>>>> >>>> >>>>> On Thu, Mar 12, 2015 at 5:35 PM, Juergen Schmidhuber >>>>> >>>>> wrote: >>>>> >>>>> Thanks. Hm, sure, ?deep neural nets? are old, and Ivakhnenko?s deep nets worked well even in the 1960s. But what I?d like to know is: who was the first to use the term ?deep learning? in an NN publication? >>>>> >>>>> Aizenberg et al (2000) wrote about ?deep learning of the features of threshold Boolean functions, one of the most important objects considered in the theory of perceptrons ?? >>>>> >>>>> Brian Mingus, however, pointed me to a paper by Rina Dechter (1986). Brian wrote: "Deep learning as compared to shallow learning is terminology used in the study of constraint satisfaction. Constraint satisfaction networks then became RBMs. I would argue this is a good basis for the origin of the modern usage. I like this paper for provenance: >>>>> http://www.aaai.org/Papers/AAAI/1986/AAAI86-029.pdf >>>>> " >>>>> >>>>> But perhaps the term occurred even earlier in the NN literature? >>>>> >>>>> Juergen >>>>> >>>> >>>> >>>> >>>>>> On 12 Mar 2015, at 21:16, Geoffrey Hinton >>>>>> >>>>>> wrote: >>>>>> >>>>>> I think the current popularity of the term started with the paper >>>>>> by Hinton Osindero and Teh in 2006 called "A fast learning >>>>>> algorithm for deep belief nets". After this paper there was a >>>>>> lot of talk about deep belief nets. In about 2007 the term "deep >>>>>> belief net" started changing its meaning and was used (rather >>>>>> sloppily) to refer to deep neural nets that were pre-trained as >>>>>> deep belief nets. The term gained a lot of popularity because >>>>>> these nets were used to make good acoustic models and that >>>>>> triggered the re-introduction of neural nets into mainline speech recognizers. >>>>>> People eventually made a clear terminological distinction between >>>>>> deep belief nets (DBNs) and deep neural nets that were >>>>>> initialized as deep belief nets (DNNs or DBN-DNNs). Then they >>>>>> discovered that with large datasets and sensible initial scales >>>>>> for the weights the pre-training was not needed and they generalized DNNs to any old deep neural net. >>>>>> >>>>>> Its clearly true that people had previously used the term deep >>>>>> neural net but that was not the origin of the resurgence of the >>>>>> term in about 2007. >>>>>> >>>>>> Its pretty obvious by now that deep neural networks of the type >>>>>> that people were using in the 1980's work very well when they >>>>>> have enough data and enough computation, and its pretty obvious >>>>>> that the deep convnets that Yann has been using since about 1987 >>>>>> are deep neural nets, so what does it matter where the name came >>>>>> from? Deep neural nets are finally living up to their promise so lets all enjoy it. >>>>>> >>>>>> Geoff >>>>>> >>>> >>>> >>>> >>>>>> On Thu, Mar 12, 2015 at 1:58 PM, Schmidhuber Juergen >>>>>> >>>>>> wrote: >>>>>> >>>>>>> Dear connectionists, >>>>>>> >>>>>>> to my knowledge, the ancient term "Deep Learning" was introduced to the NN field by Aizenberg & Aizenberg & Vandewalle's book (2000): "Multi-Valued and Universal Binary Neurons: Theory, Learning and Applications." >>>>>>> >>>>>>> Is anyone aware of older NN papers using it? >>>>>>> >>>>>>> (Of course, the field itself is much older - Ivakhnenko started >>>>>>> his work on deep learning networks in the mid 1960s.) >>>>>>> >>>>>>> Thanks! >>>>>>> >>>>>>> Juergen >>>>>>> >>>>>>> >>>>>>> http://people.idsia.ch/~juergen/whatsnew.html >>>> >>>> >>>> >>>> >> >> >> > From ralph.etiennecummings at gmail.com Mon Mar 16 09:53:36 2015 From: ralph.etiennecummings at gmail.com (Ralph Etienne-Cummings) Date: Mon, 16 Mar 2015 09:53:36 -0400 Subject: Connectionists: Deadline Approaching: 2015 Telluride Neuromorphic Cognition Engineering Workshop- Call For Applicants Message-ID: > > > *-------------------------------------------------------------------------------------- > **Telluride Neuromorphic Cognition Engineering Workshop* > > > > *2015 Neuromorphic Cognition Engineering Workshop* > > *Telluride, Colorado, June 28th - July 18th, 2015* > > > > CALL FOR APPLICATIONS: Deadline is April 2nd, 2015 > > NEUROMORPHIC COGNITION ENGINEERING WORKSHOP > > www.ine-web.org > > > > Sunday June 28th - Saturday July 18th, 2015, Telluride, Colorado > > > > ine-web.org/workshops/workshops-overview/index.html and the workshop wiki > is at https://neuromorphs.net/ > > > > GOALS: > > Neuromorphic engineers design and fabricate artificial neural systems > whose organizing principles are based on those of biological nervous > systems. Over the past 18 years, this research community has focused on the > understanding of low-level sensory processing and systems infrastructure; > efforts are now expanding to apply this knowledge and infrastructure to > addressing higher-level problems in perception, cognition, and learning. In > this 3-week intensive workshop and through the Institute for Neuromorphic > Engineering (INE), the mission is to promote interaction between senior and > junior researchers; to educate new members of the community; to introduce > new enabling fields and applications to the community; to promote on-going > collaborative activities emerging from the Workshop, and to promote a > self-sustaining research field. > > > > FORMAT: > > The three week summer workshop will include background lectures on systems > and cognitive neuroscience (in particular sensory processing, learning and > memory, motor systems and attention), practical tutorials on emerging > hardware design, mobile robots, hands-on projects, and special interest > groups. Participants are required to take part and possibly complete at > least one of the projects proposed. They are furthermore encouraged to > become involved in as many of the other activities proposed as interest and > time allow. There will be two lectures in the morning that cover issues > that are important to the community in general. Because of the diverse > range of backgrounds among the participants, some of these lectures will be > tutorials, rather than detailed reports of current research. These lectures > will be given by invited speakers. Projects and interest groups meet in the > late afternoons, and after dinner. In the early afternoon there will be > tutorials on a wide spectrum of topics, including analog VLSI, mobile > robotics, vision and auditory systems, central-pattern-generators, > selective attention mechanisms, cognitive systems, etc. > > > > *2015 TOPIC AREAS:* > > > > *Human Auditory Cognition: Communicating with EEG and Virtual Reality > Links (The Matrix)*: Shihab Shamma (UM-College Park), Malcolm Slaney > (Microsoft), Edward Lalor (Trinity College, Dublin), and Alain de Cheveigne > (UPMC, France) > > > > *Manipulation Actions: Movements, Forces and Affordances: *Cornelia > Ferm?ller (UMCP), Michael Pfeiffer (INI-UZH), Ryad Benosman (UPMC, Paris), > and Andreas Andreou (JHU) > > > > *Neuromorphic Natural Language Processing:* John Harris (UFL, > Gainesville) and Chris Huyck (Middlesex University) > > > > *Spike-Based Cognitive Computing: Seeing, Hearing, and Thinking with > Spikes: *Arindam Basu (NTU, Singapore) and John Arthur (IBM Research > Almaden) > > > > *Computational Neuroscience (invitational mini-workshop)* : Terry > Sejnowski (Salk Institute) > > > > LOCATION AND ARRANGEMENTS: > > The summer school will take place in the small town of Telluride, 9000 > feet high in southwest Colorado, about 6 hours drive away from Denver (350 > miles). Great Lakes Aviation and America West Express airlines provide > daily flights directly into Telluride. All facilities within the > beautifully renovated public school building are fully accessible to > participants with disabilities. Participants will be housed in ski > condominiums, within walking distance of the school. Participants are > expected to share condominiums. > > > > The workshop is intended to be very informal and hands-on. Participants > are not required to have had previous experience in analog VLSI circuit > design, computational or machine vision, systems level neurophysiology or > modeling the brain at the systems level. However, we strongly encourage > active researchers with relevant backgrounds from academia, industry and > national laboratories to apply, in particular if they are prepared to work > on specific projects, talk about their own work or bring demonstrations to > Telluride (e.g. robots, chips, software). Wireless internet access will be > provided. Technical staff present throughout the workshops will assist with > software and hardware issues. We will have a network of PCs running LINUX > and Microsoft Windows for the workshop projects. We encourage participants > to bring along their personal laptop. > > > > No cars are required. Given the small size of the town, we recommend that > you do not rent a car. Bring hiking boots, warm clothes, rain gear, and a > backpack, since Telluride is surrounded by beautiful mountains. > > > > Unless otherwise arranged with one of the organizers, we expect > participants to stay for the entire duration of this three week workshop. > > > > FINANCIAL ARRANGEMENTS: > > Notification of acceptances will be mailed out around the April 15th, > 2015. The Workshop covers all your accommodations and facilities costs for > the 3 weeks duration. You are responsible for your own travel to the > Workshop, however, sponsored fellowships will be available as described > below to further subsidize your cost. > > > > Registration Fees: For expenses not covered by federal funds, a Workshop > registration fee is required. The fee is TBD per participant for the 3-week > Workshop. This is expected from all participants at the time of acceptance. > > Accommodations: The cost of a shared condominium, typically a bedroom in a > shared condo for senior participants or a shared room for students, will be > covered for all academic participants. Upgrades to a private rooms or > condos will cost extra. Participants from National Laboratories and > Industry are expected to pay for these condominiums. > > > > Fellowships: This year we will offer one Fellowship program to subsidize > your costs: > > The EU-CSNII Fellowship (http://csnetwork.eu/) which is funded by the 7th > Research Framework Program FP7-ICT-CSNII-601167. The top 8 EU applicants > will be reimbursed for their registration fees ($1250), subsistence/travel > subsidy (up to Euro 2000) and accommodations cost ($1500). The registration > and accommodation costs will go directly to the INE (the INE will reimburse > them). > > > > We invite applications for a three-week summer workshop that will be held > in Telluride, Colorado. Sunday June 28th - Saturday July 18th, 2015. The > application deadline is Wednesday, April 2nd and application instructions > are described at the bottom of this document. > > > > The 2015 Workshop and Summer School on Neuromorphic Engineering is > sponsored by the National Science Foundation, Institute of Neuromorphic > Engineering, DARPA, Office of Naval Research, The EU-Collaborative > Convergent Science Network (CNS-II), University of Maryland - College Park, > Institute for Neuroinformatics ? University of Zurich and ETH Zurich, > Georgia Institute of Technology, Johns Hopkins University, Boston > University, University of Western Sydney and the Salk Institute. > > > > Directors: > > Cornelia Fermuller, University of Maryland, College Park > > Ralph Etienne-Cummings, Johns Hopkins University > > Shih-Chii Liu, Institute of Neuroinformatics, UNI/ETH Zurich, Switzerland > > Timothy Horiuchi, University of Maryland, College Park > > > > Workshop Advisory Board: > > Andreas Andreou, Johns Hopkins University > > Andre van Schaik, University Western Sydney, Australia > > Avis Cohen, University of Maryland > > Barbara Shinn-Cunningham, Boston University > > Giacomo Indiveri, Institute of Neuroinformatics, Uni/Eth Zurich, > Switzerland > > Jonathan Tapson, University Western Sydney, Australia > > Malcolm Slaney, Microsoft Research > > Jennifer Hasler, Georgia Institute of Technology > > Rodney Douglas, Institute of Neuroinformatics, Uni/Eth Zurich, Switzerland > > Shihab Shamma, University of Maryland > > Tobi Delbruck, Institute of Neuroinformatics, Uni/Eth Zurich, Switzerland > > > > Previous year workshop can be found at: > participant?s > registration fees after receipt from CSNII), while the subsistence/travel > reimbursement will be provided directly to the participants by the CSNII at > the University of Pompeu Fabra, Barcelona, Spain. > > HOW TO APPLY: > > Applicants should be at the level of graduate students or above (i.e. > postdoctoral fellows, faculty, research and engineering staff and the > equivalent positions in industry and national laboratories). We actively > encourage women and minority candidates to apply. > > > > Anyone interested in proposing or discussing specific projects should > contact the appropriate topic leaders directly. > > > > The application website is (after February 23rd, 2015): > > ine-web.org/telluride-conference-2015/apply-info > > > > Application information needed: > > Contact email address. > > First name, Last name, Affiliation, valid e-mail address. > > Curriculum Vitae (a short version, please). > > One page summary of background and interests relevant to the workshop, > including possible ideas for workshop projects. Please indicate which topic > areas you would most likely join. > > Two letters of recommendation (uploaded directly by references). > > Applicants will be notified by e-mail. > > 23rd February, 2015 - Applications accepted on website > > 2nd April, 2015 - Applications Due > > 15th April, 2015 - Notification of Acceptance > > > > -- > Ralph Etienne-Cummings, PhD, FIEEE > Professor and Chairman > Department of Electrical and Computer Engineering > Computational Sensor Motor Systems Lab > Laboratory for Computational Sensing and Robotics > The Johns Hopkins University > Baltimore, MD > [image: cid:image001.png at 01CFC064.B58B46A0] > > -- Ralph Etienne-Cummings, PhD, FIEEE Professor and Chairman Department of Electrical and Computer Engineering Computational Sensor Motor Systems Lab Laboratory for Computational Sensing and Robotics The Johns Hopkins University Baltimore, MD [image: cid:image001.png at 01CFC064.B58B46A0] -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image001.png Type: image/png Size: 20171 bytes Desc: not available URL: From gunnar.blohm at gmail.com Mon Mar 16 12:47:12 2015 From: gunnar.blohm at gmail.com (Gunnar Blohm) Date: Mon, 16 Mar 2015 12:47:12 -0400 Subject: Connectionists: CoSMo 2015 - application deadline extended: Mar 20, 2015! Message-ID: <55070910.7040206@queensu.ca> Due to continued interest, we have decided to extend the application deadline for CoSMo 2015! This is a tremendous opportunity for students and posdocs to get hands-on training in computational neuroscience. *Extended deadline: March 20, 2015* http://www.compneurosci.com/CoSMo/ Best Gunnar Blohm, Paul Schrater, Konrad K?rding, John van Opstal, Pieter Medendorp -- ------------------------------------------------------- Dr. Gunnar BLOHM Associate Professor in Computational Neuroscience Association for Canadian Neuroinformatics and Computational Neuroscience (CNCN) Centre for Neuroscience Studies, Departments of Biomedical and Molecular Sciences, Mathematics & Statistics, and Psychology, School of Computing, and Canadian Action and Perception Network (CAPnet) Queen?s University 18, Stuart Street Kingston, Ontario, Canada, K7L 3N6 Tel: (613) 533-3385 Fax: (613) 533-6840 Email: Gunnar.Blohm at QueensU.ca Web: http://www.compneurosci.com/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From sophie.deneve at ens.fr Tue Mar 17 11:13:42 2015 From: sophie.deneve at ens.fr (Sophie Deneve) Date: Tue, 17 Mar 2015 16:13:42 +0100 Subject: Connectionists: Postdoctoral positions available in group for neural theory, Paris Message-ID: Two postdoctoral positions are available in the group of Sophie Deneve, Ecole Normale sup?rieure, Paris. Positions are for two years, and comes with competitive salary and generous equipment and travel funds. The team is part of the ?Group for neural theory? ( http://iec-lnc.ens.fr/group-for-neural-theory/) and surrounded by top-level theoretical and experimental labs. Candidates are expected to have a solid training in the field of computational neuroscience, proven quantitative and programming skills and a strong interest in integrative neuroscience. Starting dates are flexible, but should preferentially occur before September 2015. Candidates should send their application to sophie.deneve at ens.fr by *March 31, 2015*. Please mention ?postdoctoral candidate? in the subject of the email. Application should take the form of a single PDF file, containing a CV, motivation letter, names and email addresses of 2 to 3 referees. No official letter of recommendations are required, as the referees will be contacted directly. Main research directions in the lab are: Efficient coding in spiking networks (theory and data analyses). Probabilistic approaches to sensory processing (theory and data analyses). Hierarchical inference and learning in neural networks, application to schizophrenia (psychophysics experiment and theory) Candidates should send their application to sophie.deneve at ens.fr by *March 31, 2015*. Please mention ?postdoctoral candidate? in the subject of the email. Application should take the form of a single PDF file, containing a CV, motivation letter, names and email addresses of 2 to 3 referees. No official letter of recommendations are required, as the referee will be contacted directly. -- Dr Sophie Deneve Group for Neural Theory Laboratoire de Neurosciences cognitives ENS-INSERM 29, rue d'Ulm, 75005 Paris, France Tel. (+33) (0)1 44 32 26 35 -------------- next part -------------- An HTML attachment was scrubbed... URL: From pascal.fua at epfl.ch Tue Mar 17 10:15:54 2015 From: pascal.fua at epfl.ch (Pascal Fua) Date: Tue, 17 Mar 2015 15:15:54 +0100 Subject: Connectionists: Post-doctoral Position in Computer Vision at EPFL Message-ID: <5508371A.9000405@epfl.ch> EPFL's Computer Vision Laboratory (http://cvlab.epfl.ch/) has two openings for post-doctoral fellow in the field of Computer Vision and Augmented Reality. The positions are initially offered for 1 year and can be extended for up to 4 years total. Description: In one case the work will involve 3D tracking of a small robot on a tablet for Augmented Reality purposes and with a view to developing educational tools. In the other, the work will involve developing new techniques for multi-camera people tracking. Position: The Computer Vision Laboratory offers a creative international environment, a possibility to conduct competitive research on a global scale and involvement in teaching. There will be ample opportunities to cooperate with some of the best groups in Europe and elsewhere. EPFL is located next to Lake Geneva in a beautiful setting 60 kilometers away from the city of Geneva. Salaries are in the order CHF 80,000 per year, the precise amount to be determined by EPFL's department of human resources. Education: Applicants are expected to have finished, or be about to finish their Ph.D. degrees, to have a strong background in Computer Vision and 3D Tracking, and to have a track record of publications in top conferences and journals. Strong programming skills (C or C++) are a plus. French language skills are not required, English is mandatory. Application: Applications must be sent by email to Ms. Gisclon (josiane.gisclon at epfl.ch). They must contain a statement of interest, a CV, a list of publications, and the names of three references. From chathach at gmail.com Tue Mar 17 12:02:06 2015 From: chathach at gmail.com (Christopher Chatham) Date: Tue, 17 Mar 2015 12:02:06 -0400 Subject: Connectionists: Cognitive Neuroscientist wanted for Drug Discovery Message-ID: Dear Connectionists, I appreciate this list reaches a much wider audience than just cognitive neuroscientists, so please forgive the intrusion. We are looking for a cognitive neuroscientist to join our growing team in the Neurocognition and Functional Imaging group at Pfizer (Cambridge, MA); those with experience in connectionist modeling would be a welcome addition to our team. *Please feel free to forward this listing to any other interested parties or lists.* See the full job posting or apply via https://www.linkedin.com/jobs2/view/38609110 Excerpts from the full job posting: *Role Description * *To provide expertise in clinical cognitive neuroscience, and its application to neuropsychiatric / neurodegenerative disorders, in combination with functional neuroimaging techniques (including e.g. fMRI, ERP, MEG and/or TMS) to support the development of medicines from target identification through Proof-of-Concept. *Provide expertise on data analytic methods as applied to functional imaging and cognitive data *Responsibility for the delivery of the portfolio by supporiting clinical neurocognitive and functional neuroimaging projects to support needs of the Therapeutic Area divisions. Primary responsibility to the Neuroscience Research unit in preclinical and early phase clinical development. *Provide support to key projects in the Business Units that require the knowledge of neurocognitive and functional neuroimaging for late phase application. *Member of a team of imaging scientists (both preclinical and clinical) in support of the needs of neurosciences and aligned with the overall imaging stategy of the organization. *Maintain cutting edge knowledge of the clinical neurocognitive and functional neuroimaging field; be aware of major advances and emerging trends, and; maintain excellent links with academic groups worldwide. *Responsibilities * *Responsible for scientific quality, experimental design and interpretation of projects involving cognitive asssessments, particularly in combination with functional neuroimaging. *Where relevant, provides expertise in neurocognition and functional neuroimaging to support review committees and major decision points in the drug development process *Provides a point of contact for data analysis expertise, to support cutting edge analytical procedures *Responsible for establishing and maintaining external collaborations (academic and industrial) to specified timelines and milestones. *Contributes to the development of strategies that integrate knowledge of neurocognitive and functional neuroimaging with other biological data (proteomics, metabolomics, genetics, imaging etc?) that underpin the development of systems biology/systems medicine *Provides prime input to the Imaging group in terms of a particular technique being fit for purpose and seeks support for all aspects of image analysis. *Qualifications * Qualifications: Education: *PhD in a relevant discipline (experimental psychology preferred; strong background in cognition essential) Technical Ability: *Expert in neurocognition in humans; strong and broad theoretical knowledge across cognitive domains, demonstrated practical application of wide variety of cognitive techniques *Expert in the combination of cognitive assessment in conjunction with functional neuroimaging. *Direct experience operationalizing studies in clinical neurocognition, in conjunction with the application of functional neuroimaging techniques (fMRI, ERP, MET, TMS), ideally with experience in neuropsychiatric/neurodegenerative disease populations *Direct experience of clinical imaging study design, including protocol develop and data analysis *Knowledge of disease area pathophysiology, and use of cognitive imaging to explore circuit-based mechanisms *Knowledge and experience in the application of neurocognition and functional neuroimaging to drug discovery and development. *Ability to provide scientific critique on ideas, interpretation of results and direction on multiple projects. *Publication record in the field of neurocognition and/or functional neuroimaging. *Strong background in data analysis and computational modelling of behavioural and/or imaging data Desirable: *Direct experience in the preclinical to clinical translation of novel functional neuroimaging techniques. *Strong background in the technical acquisition of MRI data Essential Attributes: *Identifying and championing new initiatives. *Strong quantitative skills. *Scientific leadership combined with research project delivery. *Successful track record of effectively working in multi- disciplinary teams. *Ability to problem solve and influence in complex experimental designs. *Broad impact in scientific community externally through e.g. steering committee, conference organizing committee or editorial board memberships. *Track record of publications in neurocognition and/or functional neuroimaging and invited external presentations of research activities. *International research reputation via productive research collaborations. Desirable Attributes: *Experience in the application of neurocognition and/or functional neuroimaging to drug disciovery and development. *Proven track record of leading and delivering multiple programs in parallel. Competencies: *Excellent communication skills. *Ability to communicate ideas and opinions confidently, clearly and honestly in both group and 1:1 situations. (Proactive, robust without being confrontational) *Excellent team skills with the ability to motivate teams *Promotes the use of novel experimental approaches and routinely investigates/creates innovative processes and methodologies. *Self awareness and ability to proactively consult others to ensure quality of judgment. *Flexible, embraces new ideas and thinking. *Must be proactive and highly motivated to apply functional and structural neuroimaging in a drug discovery setting. Circumstances: *Willing to relocate to Cambridge, MA See the full job posting or apply via https://www.linkedin.com/jobs2/view/38609110 -------------- next part -------------- An HTML attachment was scrubbed... URL: From emmanuel.vincent at inria.fr Tue Mar 17 18:47:27 2015 From: emmanuel.vincent at inria.fr (Emmanuel Vincent) Date: Tue, 17 Mar 2015 23:47:27 +0100 Subject: Connectionists: Deadline extended: LVA 2015 (12th International Conference on Latent Variable Analysis and Signal Separation) Message-ID: <5508AEFF.1040505@inria.fr> ---------------------------------------------- LVA 2015 - 12th International Conference on Latent Variable Analysis and Signal Separation August 25-28, 2015, Liberec, Czech Republic Paper submission deadline: April 10, 2015 PDF upload deadline: April 17, 2015 http://amca.cz/lva2015/ ---------------------------------------------- *News* The paper submission deadline has been postponed to April 10, 2015. The PDF can be modified until April 17, 2015, but not the list of authors, the title, or the abstract. There will be no further deadline extension. http://amca.cz/lva2015/index.php/paper The conference will be preceded by a Summer School on Latent Variable Analysis and Signal Separation http://amca.cz/lva2015/index.php/summer-school It will also feature the much-awaited results of the 5th Signal Separation Evaluation Campaign (SiSEC 2015) https://sisec.inria.fr/ The best audio paper will receive an award sponsored by Conexant. *About LVA* LVA 2015 will be the 12th in a series of international conferences which attracted hundreds of researchers and practitioners over the years. Since its start in 1999 under the banner of Independent Component Analysis and Blind Source Separation (ICA), the conference has continuously broadened its horizons. It encompasses today a host of additional forms and models of general mixtures of latent variables. Theories and tools borrowing from the fields of signal processing, applied statistics, machine learning, linear and multilinear algebra, numerical analysis and optimization, and numerous application fields offer exciting interdisciplinary interactions. *Highlights* Keynote talks will be given by three leading researchers: - T?lay Adali (University of Maryland, Baltimore County, USA) - R?mi Gribonval (Inria, France) - DeLiang Wang (Ohio State University, USA) The conference will also feature 5 special sessions: - Advances in nonlinear blind source separation (Y. Deville) - Deep neural networks for supervised speech separation/enhancement (D. Wang) - Joint analysis of multiple datasets, data fusion, and related topics (D. Lahat & C. Jutten) - Sparse and low-rank modeling for acoustic signal processing (A. Asaei & S. Gannot) - Tensor-based methods for blind signal separation (L. De Lathauwer) *Call for Papers* The proceedings will be published in Springer-Verlag's Lecture Notes in Computer Science Series (LNCS). Prospective authors are invited to submit original papers (up to 8 pages in LNCS format) in areas related to latent variable analysis and signal separation, including but not limited to: - Theory: sparse coding, dictionary learning; statistical and probabilistic modeling; detection, estimation and performance criteria and bounds; causality measures; learning theory; convex/nonconvex optimization tools - Models: general linear or nonlinear models of signals and data; discrete, continuous, flat, or hierarchical models; multilinear models; time-varying, instantaneous, convolutive, noiseless, noisy, over-complete, or under-complete mixtures - Algorithms: estimation, separation, identification, detection, blind and semi-blind methods, non-negative matrix factorization, tensor decomposition, adaptive and recursive estimation; feature selection; time-frequency and wavelet based analysis; complexity analysis - Applications: speech and audio separation, recognition, dereverberation and denoising; auditory scene analysis; image segmentation, separation, fusion, classification, texture analysis; biomedical signal analysis, imaging, genomic data analysis, brain-computer interface - Emerging related topics: sparse learning; deep learning; social networks; data mining; artificial intelligence; objective and subjective performance evaluation. *Important Dates* Apr 10, 2015: Paper submission deadline Apr 17, 2015: PDF upload deadline May 22, 2015: Notification of acceptance Jun 12, 2015: Submission of camera-ready papers Aug 25-28, 2015: Conference dates *Organizing Committee* General chairs: Zbynek Koldovsky (Technical University of Liberec, Czech Republic) Petr Tichavsky (Academy of Sciences, Czech Republic) Program chairs: Arie Yeredor (Tel-Aviv University, Israel) Emmanuel Vincent (Inria, France) Special sessions: Shoji Makino (University of Tsukuba, Japana) SiSEC chair: Nobutaka Ono (NII, Japan) Overseas liaison: Andrzej Cichocki (RIKEN, Japan) *Sponsors* Technicolor Technical University of Liberec Conexant Systems, Inc. Jablotron Sony From alessandro.torcini at cnr.it Wed Mar 18 04:38:07 2015 From: alessandro.torcini at cnr.it (Alessandro Torcini) Date: Wed, 18 Mar 2015 09:38:07 +0100 Subject: Connectionists: Workshop on Nonlinear Dynamics in Computational Neuroscience: from Physics and Biology to ICT Message-ID: Here is the First Announcement of the 10th SICC International Tutorial Workshop on "Topics in nonlinear dynamics" <> to be held on September 07-09, 2015 in Turin, Italy Organizers: Fernando Corinto (Politecnico di Torino, Turin, Italy) Alessandro Torcini (ISC-CNR, Florence, Italy) This workshop "Nonlinear Dynamics in Computational Neuroscience: from Physics and Biology to ICT? offers an unique opportunity to meet researchers working across (and between) disciplines linked to Computational Neuroscience. In particular, computational neuroscients, neurophysiologists and neural engineers will have the opportunity to present their most recent results to a young audience, constituted mainly by PhD students, and to interact directly among them. The program ranges from nonlinear dynamical approaches to the understanding of neural computation to physiology, from the simulations of brain circuits to the development of engineering devices and platforms for neuromorphic computation. The speakers will be specifically advised to perform didactic presentations of their results in order to allow the active participation to the discussion of young PhD students from different disciplines as well as to researchers interested in the field of Computational Neuroscience. Specific poster sessions will be organized with the purpose on one side to allow the young participants to present their latest results and on the other side to increase the opportunity of networking among the participants and renowed experts of the discipline. This workshop represents the 10th of a series of tutorial workshops annually organized by the Italian Society of Chaos and Complexity (SICC) to explore the emergence of new research fields, where nonlinear dynamics and control theory can play a relevant role. These workshops have been traditionally devoted to an audience mainly constituted by PhD students or young researchers working in complex systems. A poster session will be running during all the event and aimed to let all the participants to present their recent results. More information on the workshop can be found in the web page: http://www.neuro-eng-comp.polito.it/workshop/ Confirmed invited speakers include Cristina Becchio (University of Turin, Italy) Ruben Moreno Bote (CIBERSAM - Barcelona, Spain) George Bourianov (Intel/University of Texas at Austin, USA) Emilio Carbone (University of Turin, Italy) Stephen Coombes (University of Nottingham, UK) Steve Furber (The University of Manchester, UK) Julius Georgiou (University of Cyprus, Cyprus) Viktor Jirsa (INSERM - Marseille, France) Luke P. Lee (UC Berkeley, USA) Stefano Luccioli (ISC CNR - Florence, Italy) Maurizio Mattia (ISS - Roma, Italy) Benedetto Sacchetti (University of Turin, Italy) Maria Sanchez-Vives (IDIBAPS - Barcelona, Spain) Ronald Tetzlaff (TU Dresden, Germany) The workshop is kindly supported by the: SICC - Italian Society for Chaos and Complexity, IEEE Circuits and Systems Society - CASS Surplus Funds CRT Foundation, Marie Curie Initial Training project NETT - Neural Engineering Transformative Technologies, Ministry of Foreign Affairs (Italy) From boris.gutkin at ens.fr Wed Mar 18 05:49:14 2015 From: boris.gutkin at ens.fr (Boris) Date: Wed, 18 Mar 2015 10:49:14 +0100 Subject: Connectionists: Postdoctoral Fellowships in Theoretical Neuroscience @ the Higher School of Economics, Moscow Russia Message-ID: <86ABE2F5-E8EC-4A6A-A380-20F2FC039B14@ens.fr> Theoretical Neuroscience Group Postdoctoral research positions. Deadline: April 1, 2015 Theoretical Neuroscience ? computational and mathematical approaches to understanding neural function and cognition. Research interests of the Theoretical Neuroscience Group at the Centre for Cognition and Decision Making are wide ranging, carried out in collaboration with the experimental labs at the research center and the faculty of applied mathematics. Research themes include models of social decision-making, computational neuroeconomics, information processing in neurons and circuits as well as computational approaches to drug addiction and role of oscillations in cognition. The group is linked with the Group for Neural Theory at the Ecole Normale Superior in Paris, where research internships and visiting positions can be made available. We are seeking highly qualified and motivated candidate with backgrounds in quantitative disciplines: applied mathematics, physics, computer science or engineering. Programming skills and ability to carry put interdisciplinary projects are required. Ability to work with data is recommended. Candidates will be trained in model building, analysis and will be offered advanced training in neuroscience and cognitive psychology. Candidates will be expected to develop independent research projects and collaborations under the direction of the group leading scientists. Publications in international peers reviewed venues are expected as tangible out outcomes of the research. Group leader ? Boris Gutkin . General conditions for Post-Doctoral Research positions can be found here . Appointments will be normally made for one year. Please apply via online application form and attach you CV and research statement. Two letters of recommendations should be sent directly to fellowship at hse.ru by April 1, 2015. The HSE is a young, dynamic, fast-growing Russian research university providing unique research opportunities. -------------- next part -------------- An HTML attachment was scrubbed... URL: From yael at Princeton.EDU Wed Mar 18 21:38:41 2015 From: yael at Princeton.EDU (Yael Niv) Date: Thu, 19 Mar 2015 01:38:41 +0000 Subject: Connectionists: registration for RLDM2015 is now open (early registration deadline: April 21st) In-Reply-To: <02AA476C-7FFE-4F4B-8B84-8B3909CA04E3@Princeton.EDU> References: <02AA476C-7FFE-4F4B-8B84-8B3909CA04E3@Princeton.EDU> Message-ID: <7420D9E2-7528-4DBF-9B5C-BCE806CF25AD@princeton.edu> The 2nd Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM2015) www.rldm.org June 7-10, The University of Alberta, Edmonton, Alberta, Canada ====================================================== Registration for RLDM2015 is now open at http://rldm.org/rldm2015/registration/ Early registration fees for the meeting and tutorials are $250 CAD for predoc/postdoc, $480 CAD for regular registration, and $590 CAD for industry. Main meeting only is somewhat cheaper, but you miss out on the wonderful tutorials (http://rldm.org/rldm2015/tutorials/) Registration fees include three light breakfasts, all coffee breaks, two lunches, and one banquet dinner. ** Early registration ends April 21st ** We are excited to announce that RLDM2015 attracted 127 submissions. Accept/reject notifications will be sent by March 28. The list of invites speakers is already available at http://rldm.org/rldm2015/invited-speakers2015/ We look forward to seeing you in Alberta! The RLDM2015 organizing committee -------- To ensure that you receive future announcements about RLDM2015 please join our mailing list at http://tinyurl.com/RLDMlist (you must log in to google to see the "join list" button, and choose 'all emails' in the options). From publicity at ecmlpkdd2015.org Thu Mar 19 11:33:46 2015 From: publicity at ecmlpkdd2015.org (ECMLPKDD 2015) Date: Thu, 19 Mar 2015 15:33:46 -0000 Subject: Connectionists: ECMLPKDD 2015 : Call for Papers Message-ID: <018a01d0625a$18eedb70$4acc9250$@ecmlpkdd2015.org> The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD) will take place in Porto, Portugal, from September 7th to 11th, 2015 (http://www.ecmlpkdd2015.org). This event is the leading European scientific event on machine learning and data mining and builds upon a very successful series of 25 ECML and 18 PKDD conferences, which have been jointly organized for the past 14 years. ECMLPKDD 2015 will host three tracks, tutorials and a set of workshops. Therefore, we invite all researchers and practitioners from different communities to submit papers. ************************* CALL FOR PAPERS ************************* JOURNAL TRACK ********************* Articles for this track are submitted all year long directly to either Machine Learning or Data Mining and Knowledge Discovery, and are reviewed like regular journal articles. Accepted articles appear in full in the journal and the authors are given a presentation slot at the conference. Articles deemed insufficiently mature for journal publication may be accepted for inclusion in the proceedings. Submissions to the journal track will be managed by the Guest Editorial Board. Paper Submission: Cut-off dates for the bi-weekly batches are 29 Mar, 12 Apr, 26 Apr of 2015 Web Page: http://www.ecmlpkdd2015.org/submission/journal-track RESEARCH PROCEEDINGS TRACK ******************************************* The research proceedings track, which is organized in the traditional way. Accepted papers will be published in the Lecture Notes in Artificial Intelligence (LNCS/LNAI) of Springer, after reviewing by the programme committee. Abstract Submission Deadline: March 26, 2015 Paper Submission Deadline: April 2, 2015 Paper Acceptance Notification: June 1, 2015 Paper Camera Ready Submission: June 15, 2015 Web Page: http://www.ecmlpkdd2015.org/submission/research-proceedings-track INDUSTRIAL, GOVERNMENTAL & NON-GOVERNMENTAL PROCEEDINGS TRACK **************************************************************************** ************************** The NEW industrial, governmental & non-governmental (NGO) proceedings track is independent and distinct from the Research Track. Submissions to this track should solve real-world problems and focus on engineering systems, applications, and challenges. Accepted papers will be published in the Lecture Notes in Artificial Intelligence (LNCS/LNAI) of Springer, after reviewing by the programme committee. Abstract Submission Deadline: March 26, 2015 Paper Submission Deadline: April 2, 2015 Paper Acceptance Notification: June 1, 2015 Paper Camera Ready Submission: June 15, 2015 Web Page: http://www.ecmlpkdd2015.org/submission/industrial-proceedings-track Hope to see you all soon in Porto, Portugal!!! The publicity chairs of the ECMLPKDD 2015, Carlos Abreu Ferreira Ricardo Campos -------------- next part -------------- An HTML attachment was scrubbed... URL: From terry at salk.edu Thu Mar 19 15:44:03 2015 From: terry at salk.edu (Terry Sejnowski) Date: Thu, 19 Mar 2015 12:44:03 -0700 Subject: Connectionists: NEURAL COMPUTATION - April 1, 2015 In-Reply-To: Message-ID: Neural Computation - Volume 27, Number 4 - April 1, 2015 Available online for download now: http://www.mitpressjournals.org/toc/neco/27/4 ----- Articles Spontaneous Action Potentials and Neural Coding in Un-myelinated Axons Cian O'Donnell, Mark C.W. van Rossum Accurate Connection Strength Estimation Based on Variational Bayes for Detecting Synaptic Plasticity Takuya Isomura, Yutaro Ogawa, Kiyoshi Kotani, and Yasuhiko Jimbo Letters Hardware-Amenable Structural Learning for Spike-based Pattern Classification Using a Simple Model of Active Dendrites Shaista Hussain, Shih-Chii Liu, and Arindam Basu Neuronal Calcium Wave Propagation Varies With Changes in Endoplasmic Reticulum Parameters: A Computer Model Samuel A Neymotin, Robert A McDougal, Mohamed A Sherif, Christopher P Fall, Michael L. Hines, and William W Lytton Visual Tracking Using Neuromorphic Asynchronous Event-based Cameras Zhenjiang Ni, Sio-Hoi Ieng, Christoph Posch, Stephane Regnier, and Ryad Benosman The Benefits of Modelling Slack Variables in SVMs Fengzhen Tang, Peter Tino, Pedro Antonio Gutierrez, and Huanhuan Chen A Study on the Optimal Double-Parameters for Steepest Descent With Momentum Naimin Zhang ------------ ON-LINE -- http://www.mitpressjournals.org/neuralcomp SUBSCRIPTIONS - 2015 - VOLUME 27 - 12 ISSUES Student/Retired $75 Individual $134 Institution $1,075 MIT Press Journals, One Rogers Street, Cambridge, MA 02142-1209 Tel: (617) 253-2889 FAX: (617) 577-1545 journals-cs at mit.edu ------------ From erzsebet at rice.edu Thu Mar 19 15:14:19 2015 From: erzsebet at rice.edu (Erzsebet Merenyi) Date: Thu, 19 Mar 2015 14:14:19 -0500 Subject: Connectionists: =?windows-1252?q?=9311th_Workshop_on_Self-Organiz?= =?windows-1252?q?ing_Maps=94=2C_WSOM_2016=2C__Houston_Texas=2C_United_Sta?= =?windows-1252?q?tes=2C_January_6-8=2C_2016?= Message-ID: <550B200B.6030808@rice.edu> Dear Colleagues, The international conference ?11th Workshop on Self-Organizing Maps?, WSOM 2016, will be held at Rice University, Houston Texas, United States, January 6-8, 2016. Please check http://wsom2016.rice.edu/ for call for papers, information on important dates, paper submission, venue. Paper submission will be due May 15, 2015. We are so pleased to invite you to Houston and to Rice University. You will find a very welcoming, rich and vibrant environment here. Travel is easy and the weather is especially pleasant in January. If you want to be on the WSOM 2016 mailing list please send a request to Erzs?bet Mer?nyi, WSOM 2016 general chair, at erzsebet at rice.edu . With best wishes, WSOM 2016 organizers -------------- next part -------------- An HTML attachment was scrubbed... URL: From emmanuel.vincent at inria.fr Fri Mar 20 09:08:01 2015 From: emmanuel.vincent at inria.fr (Emmanuel Vincent) Date: Fri, 20 Mar 2015 14:08:01 +0100 Subject: Connectionists: LVA 2015 Summer School on Latent Variable Analysis and Signal Separation Message-ID: <550C1BB1.1090908@inria.fr> ---------------------------------------------- LVA 2015 Summer School on Latent Variable Analysis and Signal Separation August 24-25, 2015, Liberec, Czech Republic http://amca.cz/lva2015/index.php/summer-school ---------------------------------------------- The LVA 2015 Summer School is the first summer school in the field of Latent Variable Analysis and Signal Separation. It will provide four half-day lectures on hot topics that will cover both basic and advanced material. As such, it will please both students and senior researchers from academia and industry. The summer school will be followed by the 12th LVA conference on Latent Variable Analysis and Signal Separation http://amca.cz/lva2015/ *Preliminary program* The summer school will feature the following four half-day lectures: Vicente Zarzoso (University of Nice Sophia Antipolis, France) & Arie Yeredor (Tel-Aviv Univeristy, Israel) *From Independent Component Analysis to Latent Variable Analysis* Martin Haardt (Ilmenau University of Technology, Germany) & Taylan Cemgil (Bogazici University, Turkey) *Matrix and Tensor Decompositions* Emmanuel Vincent (Inria, France) & Emanu?l Habets (International Audio Laboratories, Germany) *Advanced Spatial Processing* Mikkel N. Schmidt (Technical University of Denmark) & Antoine Deleforge (University of Erlangen, Germany) *When Signal Processing Meets Machine Learning* More information about each lecture will be provided soon. *Registration* The registration fee will be 80 euros, including lunches and coffee breaks. Cheap student accomodation for less than 15 euros per night is available at http://letniubytovani.tul.cz/. Registration will open soon on the summer school website http://amca.cz/lva2015/index.php/summer-school *Organizing Committee* General chairs: Zbynek Koldovsky (Technical University of Liberec, Czech Republic) Petr Tichavsky (Academy of Sciences, Czech Republic) Program chairs: Arie Yeredor (Tel-Aviv University, Israel) Emmanuel Vincent (Inria, France) Overseas liaison: Andrzej Cichocki (RIKEN, Japan) *Sponsors* Technicolor Technical University of Liberec Conexant Systems, Inc. Jablotron Sony From friedhelm.schwenker at uni-ulm.de Fri Mar 20 10:04:49 2015 From: friedhelm.schwenker at uni-ulm.de (Dr. Schwenker) Date: Fri, 20 Mar 2015 15:04:49 +0100 Subject: Connectionists: Open PhD / Postdoc position at Ulm University Message-ID: <550C2901.9020209@uni-ulm.de> In the *Institute of Neural Information Processing at Ulm University, Germany,* we can offer a *PhD-student or postdoc position* from June or July 2015 until the end of 2016 with some potential of prolongation. We are working on artificial neural networks and learning systems for pattern recognition, in particular on the use of affective information in human-computer-interaction and companion systems. The particular research focus of this position is on the combination of methods and observations from sensor-based pattern recognition with methods and information from relational knowledge representation and/or the handling of uncertainty in this kind of neuro-symbolic integration. The research topic is part of a collaborative interdisciplinary research project (SFB-TR 62) on ?A companion technology for cognitive technical systems?, see http://www.uni-ulm.de/en/in/sfb-transregio-62.html?no_cache=1 If you are interested and already have some experience in some of these areas, please send us your CV, a statement of your current research interest and a list of your publications. For further information, please contact me by email or phone (see below). --------------------- Prof. Dr. Guenther Palm Director of the Institute of Neural Information Processing University of Ulm 89069 Ulm Germany phone: ++49 731 50 24150 fax: ++49 731 50 24156 email: guenther.palm at uni-ulm.de -------------- next part -------------- An HTML attachment was scrubbed... URL: From birgit.ahrens at bcf.uni-freiburg.de Fri Mar 20 10:40:39 2015 From: birgit.ahrens at bcf.uni-freiburg.de (Birgit Ahrens) Date: Fri, 20 Mar 2015 15:40:39 +0100 Subject: Connectionists: Fwd: BCF/NWG Course "Analysis and Models in Neurophysiology" 2015 at the Bernstein Center Freiburg, Germany In-Reply-To: <5508435D.5@bcf.uni-freiburg.de> References: <5508435D.5@bcf.uni-freiburg.de> Message-ID: <550C3167.8050908@bcf.uni-freiburg.de> *BCF/NWG Course*** *"Analysis and Models in Neurophysiology"*** /Sunday, October 4 - Friday, October 9, 2015 / /Bernstein Center Freiburg, Hansastra?e 9a, 79104 Freiburg, Germany/ *Aim of the course:* The course is intended to provide advanced Diploma/Masters and PhD students, as well as young researchers from the neurosciences with approaches for the analysis of electrophysiological data and the theoretical concepts behind them. *The course includes various topics such as*: * Neuron Models and Point Processes (Prof. Stefan Rotter) * Local field potentials (Prof. Ulrich Egert) * Neural Coding (Dr. Robert Schmidt) * Neural Decoding (Prof. Carsten Mehring) The course will consist of lectures in the morning and matching exercises using Matlab and Mathematica in the afternoon. The participants should have a basic understanding of scientific programming. This course is designated especially for advanced diploma/master students and PhD students (preferentially in their first year). *Application:* Please apply by sending *one pdf document* containing your CV and a meaningful letter of motivation to nwg-course at bcf.uni-freiburg.de . The letter of motivation should refer to the following points: * Reasons for wanting to take this course * Background in mathematics * Background in scientific programming * Experience in using Matlab and Mathematica * Background in neuroscience The course is limited to 20 participants. *Course fees:*NWG members - 50?, others - 125? *Application deadline: *June 30, 2015 *More information: *http://www.bcf.uni-freiburg.de/events/conferences-workshops/20151004-nwgcourse *-- Dr. Birgit Ahrens --* Teaching & Training Coordinator Bernstein Center Freiburg University of Freiburg Hansastr. 9a D - 79104 Freiburg Germany Phone: +49 (0) 761 203-9575 Fax: +49 (0) 761 203-9559 -------------- next part -------------- An HTML attachment was scrubbed... URL: From neville at cs.purdue.edu Fri Mar 20 12:51:13 2015 From: neville at cs.purdue.edu (Jennifer Neville) Date: Fri, 20 Mar 2015 12:51:13 -0400 Subject: Connectionists: Call for Proposals: WSDM 2016 Cup Message-ID: Hi-- Can you forward this CFP to the connectionists list? Thanks, ?Jen Neville ----------------------------------------------------------------- WSDM 2016: Ninth ACM International Conference on Web Search and Data Mining, San Francisco Bay Area, February 2016 CALL FOR PROPOSALS: WSDM Cup (Proposal deadline: Apr 17, 2015; Notification: mid May, 2105) ----------------------------------------------------------------- We invite proposals for a WSDM 2016 data mining competition. The WSDM- 2016 conference will be held in the Bay Area in late February 2016. To align with the goals of WSDM, we encourage proposals to include both a search task and a prediction/mining task. The format of the competition will involve publishing one or more datasets for search/mining tasks and having WSDM participants develop algorithms to solve the task(s) and then submit their results for evaluation. Preference will be given to proposals that involve data of general interest, and with data/tasks that are available by July 2015. A good competition task is one that is scientifically or technically challenging, can be done without extensive application domain knowledge, and can be evaluated objectively. The winners of the competition should be notified by end of November. The winners will be announced in the WSDM?2016 conference, with an invited conference talk for the winners to present their solutions. There will also be a workshop for all participants to present and discuss their approaches. The workshop, and competition more broadly, will be jointly co-chaired by the proposing team and a WSDM organizer (TBD). The proposal description should include a short paragraph for each proposed task covering the following items: -- Description of the search/mining task(s), with general background information on the application domain. -- Description of the available data, guarantee of availability, guarantee of confidentiality of the "ground truth" that will be used for evaluation, and size. -- Description of the evaluation procedures and established baselines. The evaluation metrics should be both meaningful for the application and statistically sound for objective performance comparison. -- Description of logistics of how data will be published and how evaluation will be conducted (e.g., via Kaggle). -- Names, affiliations, postal addresses, phone numbers, and short biographies of the organizers. Please send your proposals to Filip.Radlinski at microsoft.com by 17 April 2015. Notification will be sent mid May. WSDM 2016 PC Chairs Jennifer Neville, Purdue University Filip Radlinski, Microsoft From francisco.pereira at gmail.com Fri Mar 20 14:55:53 2015 From: francisco.pereira at gmail.com (Francisco Pereira) Date: Fri, 20 Mar 2015 14:55:53 -0400 Subject: Connectionists: summer internship at Siemens Corporate Technology (Princeton, NJ) Message-ID: Our team in the Imaging and Computer Vision department at Siemens Corporate Technology, in Princeton NJ, has a summer intern position, working in a project investigating the representation of semantic information in the brain, and how it is used during sentence comprehension. Our goal is to build a computational model of the process of language comprehension at the sentence level, using text corpora and other linguistic resources, and validate it with behavioral and brain imaging data. The main role of the intern will be to help in developing and implementing methods to extract information from text corpora, as well as models for emulating human performance on a variety of benchmark psychological tests. Examples of tasks you might be asked to do: - prepare and process text corpora (parse, convert to other formats, etc) - generate distributed semantic representations for words and sentences - extract structured information from text corpora - combine information from text corpora and resources such as WordNet and FrameNet - implement evaluation tasks to benchmark the models developed It is an unusual position in that you would be doing machine learning tasks to further cognitive neuroscience goals, gaining experience in both areas. In addition to the core research goals, we will also be delivering a concrete system to the funding agency; hence, this is a fast-paced project with multiple opportunities for publication. This work is being carried out in collaboration with researchers at MIT and Princeton University and funded by the IARPA Knowledge Representation in Neural Systems program ( http://www.iarpa.gov/index.php/research-programs/krns ). Requirements: - current student in a graduate program in Computer Science/Electrical Engineering/Machine Learning - experience developing software in MATLAB, Python or Perl - experience carrying out NLP tasks and using frameworks such as CoreNLP or NLTK. If interested, please send your resume to francisco-pereira at siemens.com. From erdi.peter at wigner.mta.hu Thu Mar 19 21:48:28 2015 From: erdi.peter at wigner.mta.hu (=?ISO-8859-2?Q?=C9rdi_P=E9ter?=) Date: Fri, 20 Mar 2015 02:48:28 +0100 (CET) Subject: Connectionists: available grants: Systems Neuroscience - a study abroad summer program in Budapest Message-ID: BSCS grants are available for our Systems Neuroscience: a study abroad summer program in Budapest. For students with European passports we are proud to announce a limited number of grants by E?tv?s University is available! The tuition fee AND accommodation is a dramatically reduced 1000 euro. Program start/end dates June 8th- Aug 7th, 2015 The BSCS Systems Neuroscience Program takes place at and academically supervised by the Department of Anatomy, Histology and Embryology, Semmelweis University Medical School, Budapest **************************************** Applications should be sent to ALL of these addresses by April 15th. However, they will be reviewed on rolling base! P?ter ?rdi (SysNeuro Director; BSCS Co-Director), perdi at kzoo.edu L?szl? N?gyessy SysNeuro Co-Director bscs at bscs-us.org From bcbt at upf.edu Fri Mar 20 09:13:10 2015 From: bcbt at upf.edu (=?UTF-8?Q?BCBT=2C_B=C3=BAstia_Compartida?=) Date: Fri, 20 Mar 2015 14:13:10 +0100 Subject: Connectionists: CfP : Barcelona Cognition, Brain and Technology Summer School 2015 Message-ID: *Barcelona Cognition, Brain and Technology Summer School (BCBT2015)* University Pompeu Fabra, Barcelona, Spain. August 31st to September 11th, 2015 http://bcbt.upf.edu/bcbt15 Join us for the annual *"Barcelona Cognition, Brain and Technology summer school - BCBT2015 *" (see* http://bcbt.upf.edu/bcbt15/home *) to be held from August 31st to September 11th, 2015 in Barcelona Spain. The BCBT summer school is part of a series of events organized by the Convergent Science Network of Biomimetics and Neurotechnology ( http://csnetwork.eu/) and is positioned at the interface between biology and future and emerging technologies with an emphasis on the principles underlying brains and their translation to avant-garde technologies. BCBT promotes a shared systems-level understanding of the functional architecture of the brain and its possible emulation in artificial systems. This is the 8th year of BCBT, which has ran with great success in previous years thanks to an excellent line-up of outstanding speakers (see bcbt.upf.edu for previous editions of the school). BCBT lectures are available online (see http://csnetwork.eu/) as well as the CSN *Podcast interviews *with many of the BCBT speakers. BCBT caters to students and researchers involved in projects that are in the ambit of ?BIO-ICT convergence?, "Brain Inspired ICT", ?Cognitive systems-robotics?. BCBT will offer up to 30 student slots for the practical workshops while as many researchers can register to attend the presentations and discussion sessions, as they are interested. The atmosphere of the BCBT summer school is informal with the goal to stimulate in-depth discussion. There are presentations in the morning, usually 2, with the afternoons reserved for tutorials and projects for student participants and road-mapping workshops or further discussion for senior scientists. For the 2015 edition we plan a *1st week* of the school addressing *Evolutionary and Developmental aspects of nervous systems and behavior *while the *2nd week* will include presentations aimed at the investigation of *Decision making*. Friday 11 is reserved for the presentation of the student projects to which everybody is invited. *Application deadline: July 27th, 2015* For more information on to apply, please go to http://bcbt.upf.edu/bcbt15/participate BCBT2015 is supported by the Convergent Science Network of Biomimetics and Neurotechnology (http://csnetwork.eu/). and is co-organized by Paul Verschure (BCBT Chair), ICREA and University Pompeu Fabra Barcelona, ES Tony Prescott (BCBT Co-Chair) University of Sheffield, UK Anna Mura (BCBT Co-Chair), University Pompeu Fabra Barcelona, ES In collaboration with Leah Krubizer (BCBT Co-Chair) UC Davis, CA, USA Gustavo Deco (BCBT Co-Chair), ICREA and University Pompeu Fabra Barcelona, ES -------------- next part -------------- An HTML attachment was scrubbed... URL: From neville at cs.purdue.edu Sat Mar 21 10:29:09 2015 From: neville at cs.purdue.edu (Jennifer Neville) Date: Sat, 21 Mar 2015 10:29:09 -0400 Subject: Connectionists: Postdoctoral Research Fellow: NSF Center for Science of Information Message-ID: <1CB7242F-270B-4B04-AC6F-FE9DDC0220CD@cs.purdue.edu> CENTER FOR SCIENCE OF INFORMATION NSF SCIENCE & TECHNOLOGY CENTER Postdoctoral Research Fellow - Science of Information https://www.soihub.org/news-events.php?id=644 Position Description: The Center for Science of Information (CSoI) invites nominations and applications for its CSoI Research Fellows program. The Fellows program seeks to identify and groom intellectual leaders to shape the emerging field of Science of Information and its diverse applications. The program provides opportunities for dynamic individuals to interact with premier research groups and individuals worldwide. Researchers in the Center for Science on Information have received the top awards in their fields (Rolf Nevanlinna Prize, Nobel Prize, Claude Shannon Award, and the Alan Turing Award). Research fellows will have opportunities to work in an enriching interdisciplinary environment, with significant potential for broad impact in terms of technology development, industry involvement, and educational initiatives. Successful candidates are expected to work with Center Researchers at two or more of the participating institutions and serve a leadership roles with respect to education and mentoring of graduate students. Fellows are appointed for an initial term of one year, and may be extended contingent on satisfactory performance. This position is contingent on funding from the NSF and its cooperative agreement with Purdue University. Qualifications: ? Candidate must have received a Ph.D. degree in a field related to the Science of Information within the past five years from an accredited college or university. ? Candidate must have a track record of research contributions in information theory and/or associated areas related to the research agenda of the Center (e.g., statistics, machine learning). ? Excellent oral and written communication skills. How to Apply: Applications should include: ? A complete CV including education, employment history, and publications; ? Statement of research interests, along with a short list of possible CSoI faculty they would be interested in working with; and ? Three letters of recommendation Please upload applications to: https://www.soihub.org/postdoctoral-research-fellow-2015.php Applications will be accepted until Fellows have been selected. Review of applications will begin April 1, 2015. About the Center for Science of Information: CSoI is a NSF-funded Science and Technology Center (STC) whose mission is to advance science and technology through a new quantitative understanding of the representation, communication, and processing of information in biological, physical, social, and engineered systems. The Center is a collaboration among computer scientists, mathematicians, engineers, biologists, and economists at several institutions including: Bryn Mawr, Howard, MIT, Princeton, Purdue, Stanford, Texas A&M, UC-Berkeley, UC-San Diego, and UIUC. Please visit the CSoI website for more information about the Center and current research activities: http://www.soihub.org Questions? Please contact Kelly Andronicos, Director of Diversity, at kandroni at purdue.edu. The Center for Science of Information (CSoI) is committed to diversity and equality of opportunity. Applications from women, minorities, and persons with disabilities are especially encouraged. From grlmc at urv.cat Sat Mar 21 17:01:02 2015 From: grlmc at urv.cat (GRLMC) Date: Sat, 21 Mar 2015 22:01:02 +0100 Subject: Connectionists: InfoSec 2015: registration deadline 3 April Message-ID: *To be removed from our mailing list, please respond to this message with UNSUBSCRIBE in the subject line* ********************************************************************** INTERNATIONAL SUMMER SCHOOL ON INFORMATION SECURITY InfoSec 2015 Bilbao, Spain July 6-10, 2015 Organized by Deusto University Rovira i Virgili University http://grammars.grlmc.com/InfoSec2015/ ********************************************************************** --- 4th registration deadline: April 3, 2015 --- ********************************************************************** AIM: InfoSec 2015 will be a major research training event addressed to graduates and postgraduates in the first steps of their academic career. With a global scope, it aims at updating them about the most recent advances in the critical and fast developing area of information security, which covers a large spectrum of current exciting academic research and industrial innovation. It refers to procedures to defend information from unauthorized access, use, modification, recording or destruction, with a critical role to play in order to avoid or minimize risks in the digital world. Renowned academics and industry pioneers will lecture and share their views with the audience. Most information security subareas will be displayed, namely: computer security, cryptography, privacy, cyber security, mobile security, network security, world wide web security, fraud prevention, data protection, etc. Main challenges of information security will be identified through 4 keynote lectures, 31 six-hour courses, and 1 round table, which will tackle the most active and promising topics. The organizers believe outstanding speakers will attract the brightest and most motivated students. Interaction will be a main component of the event. ADDRESSED TO: Graduates and postgraduates from around the world. There are no formal pre-requisites in terms of academic degrees. However, since there will be differences in the course levels, specific background knowledge may be required for some of them. InfoSec 2015 is also appropriate for more senior people who want to keep themselves updated on recent developments and future trends. They will surely find it fruitful to listen and discuss with major researchers, industry leaders and innovators. REGIME: In addition to keynotes, 4 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they will be willing to attend as well as to move from one to another. VENUE: InfoSec 2015 will take place in Bilbao, the capital of the Basque Country region, famous for its gastronomy and the seat of the Guggenheim Museum. The venue will be: DeustoTech, School of Engineering Deusto University Avda. Universidades, 24 48014 Bilbao KEYNOTE SPEAKERS: Jan Camenisch (IBM Research, Zurich), Privacy in a Digital World: a Lost Cause? Hao Chen (University of California, Davis), (In)security of Mobile Apps in Untrusted Networks Jennifer Seberry (University of Wollongong), The Global Village: the Beginning of the Need for Computer Security [via videoconference] Gene Tsudik (University of California, Irvine), Off-line Proximity-based Social Networking PROFESSORS AND COURSES: N. Asokan (Aalto University), [intermediate] Mobile Security: Overview of Hardware Platform Security and Considerations of Usability Jan Camenisch (IBM Research, Zurich), [introductory/intermediate] Technologies to Protect Online Privacy Hao Chen (University of California, Davis), [intermediate/advanced] Security of the Mobile App Ecosystem Nicolas T. Courtois (University College London), [introductory/intermediate] Security of ECDSA in Bitcoin and Crypto Currency Claude Cr?peau (McGill University, Montr?al), [introductory/intermediate] Quantum Computation, Cryptography and Cryptanalysis Joan Daemen (ST Microelectronics Belgium, Diegem), [introductory/intermediate] Sponge Functions, Keccak and SHA-3 Sajal K. Das (Missouri University of Science and Technology, Rolla), [intermediate/advanced] Securing Cyber-Physical Systems: Challenges and Opportunities Sabrina De Capitani di Vimercati (University of Milan), [introductory/intermediate] Security and Privacy in the Cloud Herv? Debar (T?l?com SudParis), [introductory/intermediate] Detection and Reaction to Attacks: from Intrusion Detection to Cyber-Defense Rosario Gennaro (City University of New York), [intermediate/advanced] A Survey of Verifiable Delegation of Computation Trent Jaeger (Pennsylvania State University, University Park), [intermediate/advanced] How to Add Security Enforcement to Legacy Programs Somesh Jha (University of Wisconsin, Madison), [intermediate/advanced] Analysis Techniques in Information Security Antoine Joux (Pierre et Marie Curie University, Paris), [introductory/intermediate] Discrete Logarithms in Finite Fields Marc Joye (Technicolor R&I, Los Altos), [introductory/intermediate] Secure Public-Key Cryptosystems Lars R. Knudsen (Technical University of Denmark, Lyngby), [introductory/intermediate] Block Ciphers: the Workhorses in Cryptography Songwu Lu (University of California, Los Angeles), [introductory/intermediate] Cellular Network Security: Issues and Defenses Catherine Meadows (Naval Research Laboratory, Washington DC), [introductory/intermediate] Formal Analysis of Cryptographic Protocols Nasir Memon (New York University), [introductory/intermediate] User Authentication Ethan L. Miller (University of California, Santa Cruz), [intermediate/advanced] Securing Stored Data in a Connected World Stefano Paraboschi (University of Bergamo), [introductory/intermediate] Data Protection in Network-enabled Systems Bart Preneel (KU Leuven), [introductory/intermediate] Cryptology: State of the Art and Research Challenges Jean-Jacques Quisquater (Catholic University of Louvain), [introductory/intermediate] The History of RSA: from Babylon to Smart Cards Shantanu Rane (Palo Alto Research Center), [introductory/intermediate] Privacy-preserving Data Analytics: Problems, Solutions and Challenges Mark Ryan (University of Birmingham), [introductory/intermediate] Designing Security Protocols: Electronic Voting, and Electronic Mail Rei Safavi-Naini (University of Calgary), [introductory/intermediate] Information-theoretically Secure Communication Stefan Saroiu (Microsoft Research, Redmond), [advanced] Protecting Data on Smartphones and Tablets Using Trusted Computing Milind Tambe (University of Southern California, Los Angeles), [introductory/intermediate] Introduction to the Emerging Science of Security Games Gene Tsudik (University of California, Irvine), [intermediate/advanced] Security and Privacy in Candidate Future Internet Architectures Yang Xiao (University of Alabama, Tuscaloosa), [introductory/advanced] Security in Smart Grids Wenyuan Xu (University of South Carolina, Columbia), [intermediate] Security and Privacy Analysis of Embedded Systems Yuliang Zheng (University of North Carolina, Charlotte), [introductory] Cryptography and the Future of Money ORGANIZING COMMITTEE: Adrian Horia Dediu Carlos Mart?n-Vide (co-chair) Borja Sanz (co-chair) Florentina Lilica Voicu REGISTRATION: The registration form can be found at: http://grammars.grlmc.com/InfoSec2015/registration.php The selection of up to 8 courses requested in the registration template is only tentative and non-binding. For the sake of organization, it will be helpful to have an approximation of the respective demand for each course. Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration facility disabled when the capacity of the venue will be complete. It is much recommended to register prior to the event. FEES: Fees are a flat rate covering the attendance to all courses during the week. There are several early registration deadlines. Fees depend on the registration deadline. ACCOMMODATION: Accommodation for participants is available at the Colegio Mayor Deusto (student hostel). Since there may exist problems to find accommodation in Bilbao at a reasonable price during the week of the event, the organizers' advice is to book as soon as possible, and anyway by 27 May. To do it, write to Carlson Wagonlit Travel at estudiantesud at carlsonwagonlit.es CERTIFICATE: Participants will be delivered a certificate of attendance. QUESTIONS AND FURTHER INFORMATION: florentinalilica.voicu at urv.cat ACKNOWLEDGEMENTS: Deusto University Rovira i Virgili University --- Este mensaje no contiene virus ni malware porque la protecci?n de avast! Antivirus est? activa. http://www.avast.com From thomaskreuz at gmail.com Sun Mar 22 19:44:09 2015 From: thomaskreuz at gmail.com (Thomas Kreuz) Date: Mon, 23 Mar 2015 00:44:09 +0100 Subject: Connectionists: =?utf-8?q?15_PhD_Fellowships_-_=E2=80=9CComplex_O?= =?utf-8?q?scillatory_Systems=3A_Modeling_and_Analysis_=28COSMOS=29?= =?utf-8?b?4oCd?= Message-ID: European Joint Doctorates Programme ?Complex Oscillatory Systems: Modeling and Analysis(COSMOS) ? announces 15 PhD Fellowships. COSMOS is a Marie Sk?odowska-Curie Action Innovative Training Network (MSCA-ITN-2014-EJD 642563) aiming at an understanding of the general properties of collective dynamics and synchronization of complex systems composed of oscillatory elements. It includes both theoretical projects where such systems are studied with the methods of nonlinear dynamics and statistical physics, as well as applied ones related to the analysis of experimental multivariate time series, such as physiological and neural data. The COSMOS network is highly interdisciplinary, and fellows will benefit from interactions with world-leading researchers in a broad range of disciplines. ESR positions are available at following universities: University of Potsdam, University of Aberdeen, Lancaster University, University of Florence, University Pompeu Fabra (Barcelona), VU University Amsterdam, Faculty of Information studies in Novo Mesto (Slovenia), and Medical University of Graz. All fellows will be jointly supervised by two partner universities and will receive a PhD degree from each of them. Most of the fellows are expected to be hired in July 2015, but later starting dates can potentially be accepted. Marie Sk?odowska-Curie 36-months PhD fellowships offer an attractive remuneration package including salary, mobility, and family allowances, and are subject to eligibility and mobility conditions. For further information, an overview of the projects, and a detailed description of open positions visit www.cosmos-itn.org Positions will be filled starting May 1st, 2015. Applications prior to April 15 will be given full consideration. -- Thomas Kreuz Institute for complex systems, CNR Via Madonna del Piano 10 50119 Sesto Fiorentino (Italy) Tel: +39-349-0748506 Email: thomas.kreuz at cnr.it Webpage: http://www.fi.isc.cnr.it/users/thomas.kreuz/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From erik at oist.jp Mon Mar 23 04:55:56 2015 From: erik at oist.jp (Erik De Schutter) Date: Mon, 23 Mar 2015 17:55:56 +0900 Subject: Connectionists: Postdoctoral position in network modeling Message-ID: <43E5273E-953D-49DD-87CB-666537BD2353@oist.jp> A postdoctoral researcher position to model (cerebellar) networks is available in the Computational Neuroscience Unit (https://groups.oist.jp/cnu) of Prof. Erik De Schutter at the Okinawa Institute of Science and Technology Graduate University. Depending on previous experience research emphasis can be on analyzing population activity in network models of the olivocerebellum or on further development of XML-based methods for network model description and simulation, or a combination of both. Candidates should have experience in network modeling, preferentially using the parallel NEURON environment or NEST. Prior knowledge of cerebellar anatomy and physiology is a plus but not required. The postdoc will interact with other researchers and students in the lab who are working on cerebellar modeling projects or analyzing cerebellar recordings. We offer attractive financial and working conditions in an English language graduate university that emphasizes interdisciplinary research, located on the beautiful subtropical island Okinawa. Send curriculum vitae, a summary of research interests and experience, and the names of three referees to Prof. Erik De Schutter at erik at oist.jp From frederic.armetta at univ-lyon1.fr Mon Mar 23 07:03:13 2015 From: frederic.armetta at univ-lyon1.fr (=?UTF-8?B?RnLDqWTDqXJpYyBBcm1ldHRh?=) Date: Mon, 23 Mar 2015 12:03:13 +0100 Subject: Connectionists: [SASO'2015] Call for workshops, tutorials, posters, demos, PhD symposium - 21-25 September 2015 - Boston Massachusetts In-Reply-To: <550FF261.2000005@univ-lyon1.fr> References: <550FF261.2000005@univ-lyon1.fr> Message-ID: <550FF2F1.8080605@univ-lyon1.fr> (Please accept our apologies if you receive multiple copies of this call) ######################################################### Please find detailed SASO'2015 calls on the Website: ######################################################### - Call for Workshops : http://saso2015.mit.edu/call-workshops - Call for Tutorials : http://saso2015.mit.edu/call-tutorials - Call for Posters : http://saso2015.mit.edu/call-posters - Call for Demos : http://saso2015.mit.edu/call-demos - Call for Doctoral Consortium : http://saso2015.mit.edu/call-doctoral-consortium ------------------------------------------ Date reminder - the main SASO Conference ------------------------------------------ Abstract submission: May 8, 2015 Paper submission: May 22, 2015 (There will be no extensions of this deadline) Notification: June 30, 2015 Camera ready copy due: July 17, 2015 Conference: September 21-25, 2015 ##################################################### Please find below a synthetic overview of the calls : ##################################################### ****************************************************************************************** CALL FOR WORKSHOPS ****************************************************************************************** The SASO 2015 Steering Committee invites proposals for the Workshop Program to be held along with the technical conference. SASO 2015 workshops will provide a meeting for presenting novel ideas in a less formal and possibly more focused way than the conference itself. Its aim is to stimulate and facilitate active exchange, interaction, and comparison of approaches, methods, and ideas related to specific topics, both theoretical and applied, in the general area of Self-Adaptive and Self-Organizing Systems. To motivate the discussion and participation of all the workshop attendants, we encourage organizers to get away of the typical "mini-conference" format of a workshop, and include more discussion sessions, panels, etc. Members from all areas of the SASO community are invited to submit workshop proposals for review. Workshops on global challenges, applications or on new and emerging topics are particularly encouraged. Workshops can vary in length, but most will be one full day in duration. Optionally, if desired by the organizers, workshop proceedings can be published through IEEE. Attendance of workshops will be included in the registration fee for the main SASO conference. ----------------- Important Dates ----------------- Proposal Submission Deadline: April 20, 2015 Acceptance Notification: April 27, 2015 CFP Submission Deadline: May 4, 2015 Paper Submission Deadline: July 11, 2015 Paper Acceptance Notification: July 31, 2015 Early Registration Deadline: TBD Camera-Ready Papers due: August 10, 2015 Workshop notes submission to WS chairs: August 17, 2015 Workshops dates: September 21 & 25, 2015 ****************************************************************************************** CALL FOR TUTORIALS ****************************************************************************************** FAS* - Foundation and Applications of Self* Computing Conferences 2015 will host a joint tutorial program for the 9th IEEE International Conference on Self-Adaptive and Self-Organizing System (SASO 2015), The International Conference on Cloud and Autonomic Computing (CAC 2015) and The 15th IEEE Peer-to-Peer Computing Conference. The goal of the tutorial program of FAS* 2015 is to provide an instructional offer to scholars, practitioners and students attending the conference, on a range of topics related to self* computing systems. We plan to accommodate either half-day tutorials (approx. 3.0 hours, plus one 30-minutes break) and full-day tutorials (approx 6.0 hours, plus two 30-minutes breaks, and a lunch break). The topic of a tutorial may range from practical techniques and technologies, to methodologies, guidelines over standards, to theoretical aspects related to self* systems (software, networks or services). The topic areas that fall into the general scope of FAS* conferences, as well as the focus of this year's conferences, are listed in the Call for Papers that is available on the FAS* conferences? web site. Please note that no marketing or product specific tutorials will be accepted. Tutorial levels may be introductory, intermediate, or advanced. Topics that can capture the interest of a broad audience of scholars, practitioners or students are preferred. ----------------- Important Dates ----------------- Proposal Submission Deadline: April 20, 2015 Presenter Notification: April 27, 2015 Extended Abstract and Presentation Handouts due: August 17, 2015 Tutorial presentation: September 21-25, 2015 ****************************************************************************************** CALL FOR POSTERS ****************************************************************************************** The ninth SASO conference continues its tradition of offering poster sessions, a great opportunity for interactive presentation of emerging ideas, late-breaking results, experiences, and challenges on SASO topics. Poster sessions are informal and highly interactive, and allow authors and participants to engage in in-depth discussions about the presented work from which new collaborations, ideas, and solutions can emerge. Posters should cover the same key areas as Research Papers and should contain original cutting-edge ideas, as well as speculative/provocative ones. Proposals of new research directions and innovative interdisciplinary approaches are also welcome. Please find areas particularly encouraged in the detailed call. ----------------- Important Dates ----------------- Deadline for submission: May 22, 2015 Notification: June 30, 2015 Camera ready copy due: July 17, 2015 Conference: September 21-25, 2015 ****************************************************************************************** CALL FOR DEMOS ****************************************************************************************** The demonstration track at SASO 2015 aims at providing an opportunity to participants from academia and industry to present their latest applications and systems to fellow researchers and practitioners in the field. Submissions will be evaluated based on their overall self-* characteristics, originality and maturity. The committee will particularly consider system robustness, resilience and scaling abilities in addition to the self-* functions of the contributions. Interactivity of the demos will be considered a further asset. Demonstrations may target: - virtual systems, such as software applications; - physical systems, such as robots or sensor networks; - cyber-physical systems, combining the above; where physical systems might be presented either with real equipment, by simulation, or hybrid demos using both simulations and real platforms. We particularly solicit authors to highlight the utility and general applicability of their contributions, whether for the short, medium or long term. This call is open to the full range of conference topics, however we encourage authors to also consider socio-inspired and normative systems as focus issue. These comprise self-adaptive and self-organizing algorithms, platforms and coordination mechanisms which are influenced by the design or modeling of social and normative systems. ----------------- Important Dates ----------------- Deadline for demo submission : June 15, 2015 Notification: July 17, 2015 Conference: September 21-25, 2015 ****************************************************************************************** CALL FOR DOCTORAL CONSORTIUM ****************************************************************************************** FAS* - Foundation and Applications of Self* Computing Conferences 2015 will host a joint tutorial program for the 9th IEEE International Conference on Self-Adaptive and Self-Organizing System (SASO 2015), The International Conference on Cloud and Autonomic Computing (CAC 2015) and The 15th IEEE Peer-to-Peer Computing Conference. The aim of FAS* Doctoral Symposium is to provide an international forum for PhD Students working in any of the areas addressed by FAS*. PhD students have the opportunity to discuss their research in an international forum, and with a panel of well-known experts in the field. PhD students working in any area addressed by the FAS* conferences can submit a paper describing the core problem of their PhD research and its relevance by providing a clear statement of the problem they intend to address, the motivation of the interest and novelty of the underlying research challenges, the explanation of the main ideas by examples, and a description of the proposed research plan and expected results. The topics of interest include, but are not limited to: - Self-* systems theory; - Self-* systems engineering; - Self-* system properties; - Self-* cyber-physical and socio-technical systems; - Applications and experiences of self-* systems; - Autonomic Cloud Computing; - Autonomics for Extreme Scales; - Autonomic Computing Foundations and Design Methods; - Autonomic Computing Systems, Tools and Applications; - P2P techniques and algorithms; - Experience with widely-deployed and commercial systems and applications; - Measurement and modeling of P2P systems, cloud systems, and large-scale distributed systems; - P2P applications and systems running in the Internet, in clouds, and in mobile systems; - Semantic overlay networks and semantic query routing; - Information retrieval and query support; - Security, privacy, anonymity, and anti-censorship; - P2P economics, participation incentives, trust, reputation, incentives, fairness, policy enforcement; - Overlay architectures and technologies; - Performance, availability, robustness, and scalability; - New applications of P2P technologies; ----------------- Important Dates ----------------- Abstract Submission Deadline: June 1, 2015 Paper Submission Deadline: June 15, 2015 Notifications of Acceptance: July 3, 2015 Camera ready copy due: July 17, 2015 Conference: September 21-25, 2015 CallForDemos.txt ========================================================================= SASO 2015 Call for Demos ========================================================================= ------------------------------------------------------------------------- Overview ------------------------------------------------------------------------- The demonstration track at SASO 2015 aims at providing an opportunity to participants from academia and industry to present their latest applications and systems to fellow researchers and practitioners in the field. Submissions will be evaluated based on their overall self-* characteristics, originality and maturity. The committee will particularly consider system robustness, resilience and scaling abilities in addition to the self-* functions of the contributions. Interactivity of the demos will be considered a further asset. ------------------------------------------------------------------------- Demonstrations may target: ------------------------------------------------------------------------- - virtual systems, such as software applications; - physical systems, such as robots or sensor networks; - cyber-physical systems, combining the above; where physical systems might be presented either with real equipment, by simulation, or hybrid demos using both simulations and real platforms. We particularly solicit authors to highlight the utility and general applicability of their contributions, whether for the short, medium or long term. This call is open to the full range of conference topics, however we encourage authors to also consider socio-inspired and normative systems as focus issue. These comprise self-adaptive and self-organizing algorithms, platforms and coordination mechanisms which are influenced by the design or modeling of social and normative systems. ------------------------------------------------------------------------- Submission ------------------------------------------------------------------------- Demonstration submissions must include: a short paper (2 pages, conference format) describing the system and its self-* capabilities; if accepted, papers will be published in the official proceedings; a URL of a website providing a self-explanatory video showing the system at work; and (optionally) allowing viewers to interact with the real system or with an emulator. Electronic submission: Not available yet. At the conference, software applications will be presented on computers. For cyber-physical systems, if possible, authors are invited to bring their equipment (smart devices, sensors, actuators, robots, et cetera). Software simulations or video recordings can be accepted as an alternative. Additionally, authors must bring a poster summarizing their system and demo. ------------------------------------------------------------------------- Important Dates ------------------------------------------------------------------------- Deadline for demo submission : June 15, 2015 Notification: July 17, 2015 Conference: September 21-25, 2015 ------------------------------------------------------------------------- Evaluation and Awards ------------------------------------------------------------------------- Submitted demos will undergo a selection process based to equal parts on the quality of the short paper (novelty and impact, technical soundness and presentation) and the online demo system (design, degree of innovation, technical solution, applicability, clarity of the contribution and potential of reuse). At least one author of accepted demos is required to register to the conference and to do an on-site presentation and demonstration of the contributions to the evaluation committee, as well as the other conference attendees. The evaluation committee, consisting of the Demo Program Committee members attending the conference, will award a prize for the best demo in each system category, with cyber-physical systems classifying for both. ------------------------------------------------------------------------- For More Information ------------------------------------------------------------------------- Please contact the chairs for any questions regarding the Demonstration session. ------------------------------------------------------------------------- Demonstration Chair ------------------------------------------------------------------------- Sokratis Kartakis, Imperial College London, UK CallForDoctoralConsortium.txt ========================================================================= Call for Doctoral Consortium ========================================================================= The aim of FAS* Doctoral Symposium is to provide an international forum for PhD Students working in any of the areas addressed by FAS*. PhD students have the opportunity to discuss their research in an international forum, and with a panel of well-known experts in the field. PhD students working in any area addressed by the FAS* conferences can submit a paper describing the core problem of their PhD research and its relevance by providing a clear statement of the problem they intend to address, the motivation of the interest and novelty of the underlying research challenges, the explanation of the main ideas by examples, and a description of the proposed research plan and expected results. The topics of interest include, but are not limited to: - Self-* systems theory; - Self-* systems engineering; - Self-* system properties; - Self-* cyber-physical and socio-technical systems; - Applications and experiences of self-* systems; - Autonomic Cloud Computing; - Autonomics for Extreme Scales; - Autonomic Computing Foundations and Design Methods; - Autonomic Computing Systems, Tools and Applications; - P2P techniques and algorithms; - Experience with widely-deployed and commercial systems and applications; - Measurement and modeling of P2P systems, cloud systems, and large-scale distributed systems; - P2P applications and systems running in the Internet, in clouds, and in mobile systems; - Semantic overlay networks and semantic query routing; - Information retrieval and query support; - Security, privacy, anonymity, and anti-censorship; - P2P economics, participation incentives, trust, reputation, incentives, fairness, policy enforcement; - Overlay architectures and technologies; - Performance, availability, robustness, and scalability; - New applications of P2P technologies; ------------------------------------------------------------------------- SUBMISSION INSTRUCTIONS ------------------------------------------------------------------------- All submissions should be 6 pages and formatted according to the IEEE Computer Society Press proceedings style guide and submitted electronically in PDF format. Please register as authors and submit your papers using the FAS* 2015 PhD Symposium management system, which is located at: https://easychair.org/conferences/?conf=fasphd2015 Submissions must be single-author, on the topic of the doctoral work. The name of the supervisor must be clearly marked (? supervised by ? ?) on the paper, under the author?s name. Submissions should be written using the following structure: - Problem: describe the problem that must be solved by the PhD student and motivate its relevance. - Motivating Scenario and Research Challenges: present a simple scenario in a specific application domain to motivate the research and highlight its challenges. - State of the art: position the work with respects to relevant related work. - Methodology: present the methodology that will be adopted. - Current Status: describe the current status of the work and the preliminary results that have been already reached. - Research Plan: conclude specifying the plan for the overall PhD. ------------------------------------------------------------------------- IMPORTANT DATES ------------------------------------------------------------------------- - Abstract Submission Deadline: June 1, 2015 - Paper Submission Deadline: June 15, 2015 - Notifications of Acceptance: July 3, 2015 - Camera ready copy due: July 17, 2015 - Conference: September 21-25, 2015 ------------------------------------------------------------------------- REVIEW PROCESS, FORMAT OF THE SYMPOSIUM, and AWARD ------------------------------------------------------------------------- Each submission will be reviewed by at least two experts of the PhD Symposium organization and will be evaluated in terms of their relevance to the FAS* topics, motivation and research challenges, soundness of the methodology proposed and feasibility of the research plan. Each accepted paper will have two different opportunities to be presented. Besides the full presentation during the PhD Symposium session, during the main conference, a ?PhD Elevator Pitch Session? will be organized where each PhD student will showcase his/her research shortly. The Best Doctoral Symposium paper will be selected and the award will be presented during the main conference. ------------------------------------------------------------------------- INVITED TALK ------------------------------------------------------------------------- Dr. Jeremy Pitt (Imperial College London) ? Title: ?How To Get a PhD in Self-Organizing Systems?. ------------------------------------------------------------------------- PhD SYMPOSIUM EXPERTS ------------------------------------------------------------------------- - Luciano Baresi, DEIB - Politecnico di Milano ? Italy - Geoffrey Fox - Indiana University Bloomington, USA - Kurt Geihs ? Universitaet Kassel - Salim Hariri University of Arizona, USA - Pedro Garcia Lopez, Universitat Rovira i Virgili, Spain - Julie McCann - Imperial College, UK - Alberto Montresor, University of Trento ? Italy - Manish Parashar - Rutgers University, USA - Jeremy Pitt ? Imperial College London ? UK ------------------------------------------------------------------------- CONTACT INFORMATION ------------------------------------------------------------------------- Doctoral Symposium Chair: Antonio Bucchiarone (FBK-DAS, Trento, Italy) For information, email tobucchiarone at fbk.eu CallForPosters.txt ========================================================================= SASO 2015 Call for Tutorials Call for Posters ========================================================================= ------------------------------------------------------------------------- Overview ------------------------------------------------------------------------- The ninth SASO conference continues its tradition of offering poster sessions, a great opportunity for interactive presentation of emerging ideas, late-breaking results, experiences, and challenges on SASO topics. Poster sessions are informal and highly interactive, and allow authors and participants to engage in in-depth discussions about the presented work from which new collaborations, ideas, and solutions can emerge. Posters should cover the same key areas as Research Papers and should contain original cutting-edge ideas, as well as speculative/provocative ones. Proposals of new research directions and innovative interdisciplinary approaches are also welcome. Submissions in the following areas are particularly encouraged: - Self-* systems theories, frameworks, models, and paradigms, including the ones inspired by the biological, social, and physical worlds. - Self-* systems engineering: goals and requirements, hardware and software design, deployment, management and control, validation. - Properties of self-* systems: self-organisation and emergent behaviour, self- adaptation, self-management, self-monitoring, self-tuning, self-repair, self- configuration, etc. - Evaluation of self-* systems: methods for performance, robustness, and dependability assessment and analysis. - Social self-* systems: emergent human behaviour, crowdsourcing, collective awareness, gamification and serious games. - Applications and experiences with self-* systems: cyber security, transportation, computational sustainability, power systems, large networks, large data centers, and cloud computing. ------------------------------------------------------------------------- Submission Process ------------------------------------------------------------------------- For evaluation and selection, authors should submit a two-page extended abstract of their poster. The format of this extended abstract must comply with the IEEE Computer Society Press proceedings style guide and it shall be submitted electronically in PDF format. Templates for Word and LaTeX are available here. Electronic submission: Not available yet. ------------------------------------------------------------------------- Important Dates ------------------------------------------------------------------------- Deadline for submission: May 22, 2015 Notification: June 30, 2015 Camera ready copy due: July 17, 2015 Conference: September 21-25, 2015 ------------------------------------------------------------------------- Accepted Posters ------------------------------------------------------------------------- If selected, authors shall prepare a final, camera ready version of the extended abstract, taking into account all feedback from reviewers, and formatted according to the IEEE Computer Society Press proceedings style guide. Posters will be advertised in the final program, and authors' two-page extended abstracts will be submitted to IEEE Xplore as part of the conference proceedings. Abstracts will also be available as part of the IEEE Digital Library. ------------------------------------------------------------------------- Poster Content ------------------------------------------------------------------------- Authors shall prepare their poster for presentation in the reserved poster session, taking into consideration that all posters should include the following information: The purpose and goals of the work. Any background and motivation needed to understand the work. Any critical hypotheses and assumptions that underlie the work. A clear summary of the contribution and/or results, in sufficient detail for a (re)viewer to understand the work and its relevance. If the work is at an initial stage, it is especially important to state clearly the anticipated contributions and any early results towards them. The relationship to other related efforts, where appropriate. Authors of accepted posters may be asked to point out relationships to work represented by other accepted posters. Where to find additional information. This should include but is not restricted to: a web site where viewers can go to find additional information about the work how to contact the authors, including email addresses citations for any papers, books, or other materials that provide additional information. ------------------------------------------------------------------------- Poster Layout Guidelines ------------------------------------------------------------------------- The format of posters and the nature of poster sessions require authors to capture the viewers' attention effectively, and present core concepts so as to clearly position the context of their research work. For this reason, graphic representations, figures, and screen shots are typically the main medium of communication in successful posters. Few attendees will stop to read a large poster with dense text. If screen shots are used, please ensure that they print legibly and that the fonts are large enough to be read easily once printed. The recommended size for the poster is A0 and all poster authors are required to print and bring their posters at the conference. Attendance At least one of the poster authors is required to register at the conference and will be required to give a brief presentation of the poster in the interactive poster session, as well as staying with the poster to discuss the work with conference attendees for the duration of the scheduled poster sessions. ------------------------------------------------------------------------- For More Information ------------------------------------------------------------------------- For additional information, clarification, or questions, please contact the Poster Chair. ------------------------------------------------------------------------- Poster Chair ------------------------------------------------------------------------- Sokratis Kartakis, Imperial College London, UK CallForTutorials.txt ========================================================================= Call for Tutorials FAS* - Foundation and Applications of Self* Computing Conferences 9th IEEE International Conference on Self-Adaptive and Self-Organizing System (SASO 2015) The International Conference on Cloud and Autonomic Computing (CAC 2015) The 15th IEEE Peer-to-Peer Computing Conference ========================================================================= ------------------------------------------------------------------------- Important Dates ------------------------------------------------------------------------- The exact deadlines are at 11:59 PM ET (Eastern Time Zone). - Proposal Submission Deadline: April 20, 2015 - Presenter Notification: April 27, 2015 - Extended Abstract and Presentation Handouts due: August 17, 2015 - Tutorial presentation: September 21-25, 2015 FAS* - Foundation and Applications of Self* Computing Conferences 2015 will host a joint tutorial program, hosted by MIT, Cambridge, Massachusetts, in the week of September 21-25, 2015. FAS* federates the 9th IEEE International Conference on Self-Adaptive and Self-Organizing System (SASO 2015), The International Conference on Cloud and Autonomic Computing (CAC 2015) and The 15th IEEE Peer-to-Peer Computing Conference. For detailed information about SASO 2015, CAC 2015 and P2P 2015 please visit their respective conference websites. ------------------------------------------------------------------------- Goal and Scope ------------------------------------------------------------------------- The goal of the tutorial program of FAS* 2015 is to provide an instructional offer to scholars, practitioners and students attending the conference, on a range of topics related to self* computing systems. We plan to accommodate either half-day tutorials (approx. 3.0 hours, plus one 30-minutes break) and full-day tutorials (approx 6.0 hours, plus two 30-minutes breaks, and a lunch break). The topic of a tutorial may range from practical techniques and technologies, to methodologies, guidelines over standards, to theoretical aspects related to self* systems (software, networks or services). The topic areas that fall into the general scope of FAS* conferences, as well as the focus of this year's conferences, are listed in the Call for Papers that is available on the FAS* conferences? web site. Please note that no marketing or product specific tutorials will be accepted. Tutorial levels may be introductory, intermediate, or advanced. Topics that can capture the interest of a broad audience of scholars, practitioners or students are preferred. ------------------------------------------------------------------------- Review Process ------------------------------------------------------------------------- Each tutorial proposal will be evaluated by the FAS* organizing committee according to relevance and to FAS* conferences and their communities, attractiveness and novelty of the topic, consistency with the focus of the conference, general fit within the overall tutorial program, and previous teaching experience of the proposers. ------------------------------------------------------------------------- Submission Guidelines ------------------------------------------------------------------------- Tutorial proposals must not be longer than three pages, in the same format of the FAS* research papers, that is, compliant with the IEEE Computer Society Press proceedings style. Please make sure the submission includes the following elements: - title of the tutorial; - preferred duration (half-day or full-day); - intended level (introductory, intermediate, or advanced) and prerequisites; - contact information for all presenters, including full name, affiliation, email address, full postal address, phone and fax number, URL of personal homepage; - short bio of all presenters including prior teaching and tutorial experiences; - description of the material covered by the tutorial, not exceeding two pages (approx. 1500 words): must include a proposed structure of the content to be presented; - identification of the target audience (e.g., researchers, teachers, practitioners, students); - references of publications (books, papers etc.) the tutorial builds on; - indication of whether the submission of a tutorial paper (see below) is planned. All proposals should be submitted as a PDF document via EasyChair athttps://easychair.org/conferences/?conf=fas2015 ------------------------------------------------------------------------- Accepted Proposals ------------------------------------------------------------------------- Once notified that the tutorial has been accepted, tutorial proposers should prepare a two-page extended abstract - compliant with the IEEE Computer Society Press proceedings style - describing the content of the tutorial, in addition to the handout material that is going to be distributed to the participants to their tutorial. Both the extended abstract and the handout material must be ready and submitted to the Tutorial Chair by the deadline noted above. ------------------------------------------------------------------------- Tutorials Chair ------------------------------------------------------------------------- Ivan Rodero, Rutgers, The State University of New Jersey, USA (irodero AT rutgers.edu) CallForWorkshops.txt ========================================================================= SASO 2015 Call For Workshops at the Ninth IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2015) Cambridge, MA September 21 & 25, 2015 http://saso2015.mit.edu ========================================================================= The SASO 2015 Steering Committee invites proposals for the Workshop Program to be held along with the technical conference. SASO 2015 workshops will provide a meeting for presenting novel ideas in a less formal and possibly more focused way than the conference itself. Its aim is to stimulate and facilitate active exchange, interaction, and comparison of approaches, methods, and ideas related to specific topics, both theoretical and applied, in the general area of Self-Adaptive and Self-Organizing Systems. To motivate the discussion and participation of all the workshop attendants, we encourage organizers to get away of the typical "mini-conference" format of a workshop, and include more discussion sessions, panels, etc. Members from all areas of the SASO community are invited to submit workshop proposals for review. Workshops on global challenges, applications or on new and emerging topics are particularly encouraged. Workshops can vary in length, but most will be one full day in dura tion. Optionally, if desired by the organizers, workshop proceedings can be published through IEEE. Attendance of workshops will be included in the registration fee for the main SASO conference. ------------------------------------------------------------------------- Important Dates ------------------------------------------------------------------------- - Proposal Submission Deadline: April 20, 2015 - Acceptance Notification: April 27, 2015 - CFP Submission Deadline: May 4, 2015 - Paper Submission Deadline: July 11, 2015 - Paper Acceptance Notification: July 31, 2015 - Early Registration Deadline: TBD - Camera-Ready Papers due: August 10, 2015 - Workshop notes submission to WS chairs: August 17, 2015 - Workshops dates: September 21 & 25, 2015 ------------------------------------------------------------------------- SASO 2015 Workshops - Requirements for Submission ------------------------------------------------------------------------- Proposals for workshops should be separated in two parts. The first part should be organized as preliminary call for papers or call for participation, depending on the intended format of the workshop with a maximum of two pages and contain the following information: - Title of the workshop. - A brief technical description of the workshop, specifying the workshop goals, the technical issues that it will address, and the relevance of the workshop to the main conference. - Description of paper review process (if any) and acceptance standards in order to keep the workshop high in quality. Note that papers must be in the same format as the conference proceedings and may not be more than 6 pages in length. - The names, affiliations, postal addresses, phone numbers, and email addresses of the proposed workshop organizing committee. This committee should consist of three or four people knowledgeable about the technical issues to be addressed. The organizing committee should include individuals from multiple institutions. - The primary email address for contacting the organizing committee. - Expected duration of the workshop (half or full day). - A brief description of the workshop format. - List of potential program committee members (if applicable), including their title and affiliations. - List of potential invited speakers, panelists, or disputants (if applicable). The second part with a maximum of three pages should contain additional information not suitable for a Call for Papers, including: - A discussion of why and to whom the workshop is of interest. - A list of related workshops held within the last three years, if any, and their relation to the proposed workshop. - Information about previous offerings of the proposed workshop: when and where it has been offered in the past, organizers names and affiliations, number of submissions, acceptances and registered attendees. - A description of the qualifications of the individual committee members with respect to organizing a SASO workshop, including a list of workshops previously arranged by any members of the proposed organizing committee, if any. - A list of places (distribution lists, web sites, journals, etc.) where the workshop is planned to be advertised. All proposals should be submitted in plain ASCII text or PDF format by electronic mail to the SASO 2015 Workshops Chair. The selection of the workshops to be included in the final SASO 2015 Workshop program will be based upon multiple factors, including: - the scientific/technical interest of the topics, - the quality of the proposal, - complementarity with the conference topics, - balance and distinctness of workshop topics, - and the capacity of the conference workshop program. Note that authors of proposals addressing similar and/or overlapping content areas and/or audiences may be requested to merge their proposals. ------------------------------------------------------------------------- Responsibilities of SASO 2015 and Workshop Organizers ------------------------------------------------------------------------- For all accepted proposals, SASO 2015 will be responsible for: - Providing publicity for the workshop series as a whole. - Providing logistical support and a meeting place for the workshop. - Together with the organizers, determining the workshop date and time. - Liaising and coordinating between the workshop chairs and the finance chair, publicity chair, registration chair, and web chair for SASO. - Arranging for publication of proceedings. Workshop organizers will be responsible for the following: - Setting up a web site for the workshop. - Advertising the workshop (and the main SASO conference), and issuing a call for papers and a call for participation. - Collecting and evaluating submissions, notifying authors of acceptance or rejection on a timely basis, and ensuring a transparent and fair selection process. All workshop organizers commit themselves to adopt the deadlines set by the committee. - Making the pdf of the whole workshop notes available to the workshop chair, as well as a list of audio-visual requirements and any special room requirements. - Writing a 1-page organizers introduction for your proceedings. - Ensuring that the workshop organizers and the participants register for the workshop and/or the main conference (at least one author must register for the paper to appear in the proceedings). SASO reserves the right to cancel any workshop if the above responsibilities are not fulfilled, or if too few attendees register for the workshop to support its running costs. ------------------------------------------------------------------------- Submissions and Inquiries ------------------------------------------------------------------------- Please send proposals (as a PDF document) and inquiries to the SASO 2015 workshop chair: Gauthier Picard (MINES Saint-Etienne, France) gauthier.picard at emse.fr CfP-SASO2015.txt ****************************************************************************************** CALL FOR PAPERS The Ninth IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2015) Boston Massachusetts; 21-25 September 2015 https://saso2015.mit.edu/ ****************************************************************************************** Part of FAS* - Foundation and Applications of Self* Computing Conferences Collocated with: The International Conference on Cloud and Autonomic Computing (CAC 2015) The 15th IEEE Peer-to-Peer Computing Conference (P2P 2015) ------------------- Aims and Scope ------------------- The aim of the Self-Adaptive and Self-Organizing systems conference series (SASO) is to provide a forum for the foundations of a principled approach to engineering systems, networks and services based on self-adaptation and self-organization. The complexity of current and emerging networks, software and services, especially in dealing with dynamics in the environment and problem domain, has led the software engineering, distributed systems and management communities to look for inspiration in diverse fields (e.g., complex systems, control theory, artificial intelligence, sociology, and biology) to find new ways of designing and managing such computing systems. In this endeavor, self-organization and self-adaptation have emerged as two promising interrelated approaches. They form the basis for many other self-* properties, such as self-configuration, self-healing, or self-optimization. Systems exhibiting such properties are often referred to as self-* systems. The ninth edition of the SASO conference embraces the inter-disciplinarity and the scientific, empirical, and application dimensions of self-* systems and welcomes novel results on both self-adaptive and self-organizing systems research. The topics of interest include, but are not limited to: - Self-* systems theory: theoretical frameworks and models; biologically- and socially-inspired paradigms; inter-operation of self-* mechanisms; - Self-* systems engineering: reusable mechanisms, design patterns, architectures, methodologies; software and middleware development frameworks and methods, platforms and toolkits; hardware; self-* materials; - Self-* system properties: robustness, resilience and stability; emergence; computational awareness and self-awareness; reflection; - Self-* cyber-physical and socio-technical systems: human factors and visualization; self-* social computers; crowdsourcing and collective awareness; human-in-the-loop; - Applications and experiences of self-* systems: cyber security, transportation, computational sustainability, big data and creative commons, power systems; swarm systems and robotics. - Self-* in education: experience reports; curricula; innovative course concepts; methodological aspects of self-* systems education Contributions must present novel theoretical or experimental results; novel design patterns, mechanisms, system architectures, frameworks or tools; or practical approaches and experiences in building or deploying real-world systems and applications. Contributions contrasting different approaches for engineering a given family of systems, or demonstrating the applicability of a certain approach for different systems, are equally encouraged. Likewise, papers describing substantial innovation or insights in the use and communication of self-* systems in the classroom are welcome. Where relevant and appropriate, accepted papers will also be encouraged to participate in the Demo or Poster Sessions. -------------------- Important Dates -------------------- Abstract submission: May 8, 2015 Paper submission: May 22, 2015 (There will be no extensions of this deadline!) Notification: June 30, 2015 Camera ready copy due: July 17, 2015 Conference: September 21-25, 2015 ---------------------------- Submission Instructions ---------------------------- All submissions should be 10 pages and formatted according to the IEEE Computer Society Press proceedings style guide and submitted electronically in PDF format. Please register as authors and submit your papers using the SASO 2015 conference management system that will be announced on the website. The proceedings will be published by IEEE Computer Society Press, and made available as a part of the IEEE Digital Library. Note that a separate Call for Poster Submissions will also be issued. --------------------- Review Criteria --------------------- Papers should present novel ideas in the cross-disciplinary research context described in this call, clearly motivated by problems from current practice or applied research. We expect both theoretical and empirical contributions to be clearly stated, substantiated by formal analysis, simulation, experimental evaluations, comparative studies, and so on. Appropriate reference must be made to related work. Because SASO is a cross-disciplinary conference, papers must be intelligible and relevant to researchers who are not members of the same specialized sub-field. Authors are also encouraged to submit papers describing applications. Application papers are expected to provide an indication of the real world relevance of the problem that is solved, including a description of the deployment domain, and some form of evaluation of performance, usability, or comparison to alternative approaches. Experience papers are also welcome but they must clearly state the insight into any aspect of design, implementation or management of self-* systems which is of benefit to practitioners and the SASO community. ------------------------------- Conference General Chairs ------------------------------- Howard E Shrobe MIT CSAIL, Cambridge, MA, USA Julie A McCann Imperial College London, UK -------------------- Program Chairs -------------------- Emma Hart Edinburgh Napier University Gregory Sullivan BAE Systems AIT Jan-Philipp Stegh?fer University of Gothenburg, Sweden CallForDemos.txt ========================================================================= SASO 2015 Call for Demos ========================================================================= ------------------------------------------------------------------------- Overview ------------------------------------------------------------------------- The demonstration track at SASO 2015 aims at providing an opportunity to participants from academia and industry to present their latest applications and systems to fellow researchers and practitioners in the field. Submissions will be evaluated based on their overall self-* characteristics, originality and maturity. The committee will particularly consider system robustness, resilience and scaling abilities in addition to the self-* functions of the contributions. Interactivity of the demos will be considered a further asset. ------------------------------------------------------------------------- Demonstrations may target: ------------------------------------------------------------------------- - virtual systems, such as software applications; - physical systems, such as robots or sensor networks; - cyber-physical systems, combining the above; where physical systems might be presented either with real equipment, by simulation, or hybrid demos using both simulations and real platforms. We particularly solicit authors to highlight the utility and general applicability of their contributions, whether for the short, medium or long term. This call is open to the full range of conference topics, however we encourage authors to also consider socio-inspired and normative systems as focus issue. These comprise self-adaptive and self-organizing algorithms, platforms and coordination mechanisms which are influenced by the design or modeling of social and normative systems. ------------------------------------------------------------------------- Submission ------------------------------------------------------------------------- Demonstration submissions must include: a short paper (2 pages, conference format) describing the system and its self-* capabilities; if accepted, papers will be published in the official proceedings; a URL of a website providing a self-explanatory video showing the system at work; and (optionally) allowing viewers to interact with the real system or with an emulator. Electronic submission: Not available yet. At the conference, software applications will be presented on computers. For cyber-physical systems, if possible, authors are invited to bring their equipment (smart devices, sensors, actuators, robots, et cetera). Software simulations or video recordings can be accepted as an alternative. Additionally, authors must bring a poster summarizing their system and demo. ------------------------------------------------------------------------- Important Dates ------------------------------------------------------------------------- Deadline for demo submission : June 15, 2015 Notification: July 17, 2015 Conference: September 21-25, 2015 ------------------------------------------------------------------------- Evaluation and Awards ------------------------------------------------------------------------- Submitted demos will undergo a selection process based to equal parts on the quality of the short paper (novelty and impact, technical soundness and presentation) and the online demo system (design, degree of innovation, technical solution, applicability, clarity of the contribution and potential of reuse). At least one author of accepted demos is required to register to the conference and to do an on-site presentation and demonstration of the contributions to the evaluation committee, as well as the other conference attendees. The evaluation committee, consisting of the Demo Program Committee members attending the conference, will award a prize for the best demo in each system category, with cyber-physical systems classifying for both. ------------------------------------------------------------------------- For More Information ------------------------------------------------------------------------- Please contact the chairs for any questions regarding the Demonstration session. ------------------------------------------------------------------------- Demonstration Chair ------------------------------------------------------------------------- Sokratis Kartakis, Imperial College London, UK CallForDoctoralConsortium.txt ========================================================================= Call for Doctoral Consortium ========================================================================= The aim of FAS* Doctoral Symposium is to provide an international forum for PhD Students working in any of the areas addressed by FAS*. PhD students have the opportunity to discuss their research in an international forum, and with a panel of well-known experts in the field. PhD students working in any area addressed by the FAS* conferences can submit a paper describing the core problem of their PhD research and its relevance by providing a clear statement of the problem they intend to address, the motivation of the interest and novelty of the underlying research challenges, the explanation of the main ideas by examples, and a description of the proposed research plan and expected results. The topics of interest include, but are not limited to: - Self-* systems theory; - Self-* systems engineering; - Self-* system properties; - Self-* cyber-physical and socio-technical systems; - Applications and experiences of self-* systems; - Autonomic Cloud Computing; - Autonomics for Extreme Scales; - Autonomic Computing Foundations and Design Methods; - Autonomic Computing Systems, Tools and Applications; - P2P techniques and algorithms; - Experience with widely-deployed and commercial systems and applications; - Measurement and modeling of P2P systems, cloud systems, and large-scale distributed systems; - P2P applications and systems running in the Internet, in clouds, and in mobile systems; - Semantic overlay networks and semantic query routing; - Information retrieval and query support; - Security, privacy, anonymity, and anti-censorship; - P2P economics, participation incentives, trust, reputation, incentives, fairness, policy enforcement; - Overlay architectures and technologies; - Performance, availability, robustness, and scalability; - New applications of P2P technologies; ------------------------------------------------------------------------- SUBMISSION INSTRUCTIONS ------------------------------------------------------------------------- All submissions should be 6 pages and formatted according to the IEEE Computer Society Press proceedings style guide and submitted electronically in PDF format. Please register as authors and submit your papers using the FAS* 2015 PhD Symposium management system, which is located at: https://easychair.org/conferences/?conf=fasphd2015 Submissions must be single-author, on the topic of the doctoral work. The name of the supervisor must be clearly marked (? supervised by ? ?) on the paper, under the author?s name. Submissions should be written using the following structure: - Problem: describe the problem that must be solved by the PhD student and motivate its relevance. - Motivating Scenario and Research Challenges: present a simple scenario in a specific application domain to motivate the research and highlight its challenges. - State of the art: position the work with respects to relevant related work. - Methodology: present the methodology that will be adopted. - Current Status: describe the current status of the work and the preliminary results that have been already reached. - Research Plan: conclude specifying the plan for the overall PhD. ------------------------------------------------------------------------- IMPORTANT DATES ------------------------------------------------------------------------- - Abstract Submission Deadline: June 1, 2015 - Paper Submission Deadline: June 15, 2015 - Notifications of Acceptance: July 3, 2015 - Camera ready copy due: July 17, 2015 - Conference: September 21-25, 2015 ------------------------------------------------------------------------- REVIEW PROCESS, FORMAT OF THE SYMPOSIUM, and AWARD ------------------------------------------------------------------------- Each submission will be reviewed by at least two experts of the PhD Symposium organization and will be evaluated in terms of their relevance to the FAS* topics, motivation and research challenges, soundness of the methodology proposed and feasibility of the research plan. Each accepted paper will have two different opportunities to be presented. Besides the full presentation during the PhD Symposium session, during the main conference, a ?PhD Elevator Pitch Session? will be organized where each PhD student will showcase his/her research shortly. The Best Doctoral Symposium paper will be selected and the award will be presented during the main conference. ------------------------------------------------------------------------- INVITED TALK ------------------------------------------------------------------------- Dr. Jeremy Pitt (Imperial College London) ? Title: ?How To Get a PhD in Self-Organizing Systems?. ------------------------------------------------------------------------- PhD SYMPOSIUM EXPERTS ------------------------------------------------------------------------- - Luciano Baresi, DEIB - Politecnico di Milano ? Italy - Geoffrey Fox - Indiana University Bloomington, USA - Kurt Geihs ? Universitaet Kassel - Salim Hariri University of Arizona, USA - Pedro Garcia Lopez, Universitat Rovira i Virgili, Spain - Julie McCann - Imperial College, UK - Alberto Montresor, University of Trento ? Italy - Manish Parashar - Rutgers University, USA - Jeremy Pitt ? Imperial College London ? UK ------------------------------------------------------------------------- CONTACT INFORMATION ------------------------------------------------------------------------- Doctoral Symposium Chair: Antonio Bucchiarone (FBK-DAS, Trento, Italy) For information, email tobucchiarone at fbk.eu CallForPosters.txt ========================================================================= SASO 2015 Call for Tutorials Call for Posters ========================================================================= ------------------------------------------------------------------------- Overview ------------------------------------------------------------------------- The ninth SASO conference continues its tradition of offering poster sessions, a great opportunity for interactive presentation of emerging ideas, late-breaking results, experiences, and challenges on SASO topics. Poster sessions are informal and highly interactive, and allow authors and participants to engage in in-depth discussions about the presented work from which new collaborations, ideas, and solutions can emerge. Posters should cover the same key areas as Research Papers and should contain original cutting-edge ideas, as well as speculative/provocative ones. Proposals of new research directions and innovative interdisciplinary approaches are also welcome. Submissions in the following areas are particularly encouraged: - Self-* systems theories, frameworks, models, and paradigms, including the ones inspired by the biological, social, and physical worlds. - Self-* systems engineering: goals and requirements, hardware and software design, deployment, management and control, validation. - Properties of self-* systems: self-organisation and emergent behaviour, self- adaptation, self-management, self-monitoring, self-tuning, self-repair, self- configuration, etc. - Evaluation of self-* systems: methods for performance, robustness, and dependability assessment and analysis. - Social self-* systems: emergent human behaviour, crowdsourcing, collective awareness, gamification and serious games. - Applications and experiences with self-* systems: cyber security, transportation, computational sustainability, power systems, large networks, large data centers, and cloud computing. ------------------------------------------------------------------------- Submission Process ------------------------------------------------------------------------- For evaluation and selection, authors should submit a two-page extended abstract of their poster. The format of this extended abstract must comply with the IEEE Computer Society Press proceedings style guide and it shall be submitted electronically in PDF format. Templates for Word and LaTeX are available here. Electronic submission: Not available yet. ------------------------------------------------------------------------- Important Dates ------------------------------------------------------------------------- Deadline for submission: May 22, 2015 Notification: June 30, 2015 Camera ready copy due: July 17, 2015 Conference: September 21-25, 2015 ------------------------------------------------------------------------- Accepted Posters ------------------------------------------------------------------------- If selected, authors shall prepare a final, camera ready version of the extended abstract, taking into account all feedback from reviewers, and formatted according to the IEEE Computer Society Press proceedings style guide. Posters will be advertised in the final program, and authors' two-page extended abstracts will be submitted to IEEE Xplore as part of the conference proceedings. Abstracts will also be available as part of the IEEE Digital Library. ------------------------------------------------------------------------- Poster Content ------------------------------------------------------------------------- Authors shall prepare their poster for presentation in the reserved poster session, taking into consideration that all posters should include the following information: The purpose and goals of the work. Any background and motivation needed to understand the work. Any critical hypotheses and assumptions that underlie the work. A clear summary of the contribution and/or results, in sufficient detail for a (re)viewer to understand the work and its relevance. If the work is at an initial stage, it is especially important to state clearly the anticipated contributions and any early results towards them. The relationship to other related efforts, where appropriate. Authors of accepted posters may be asked to point out relationships to work represented by other accepted posters. Where to find additional information. This should include but is not restricted to: a web site where viewers can go to find additional information about the work how to contact the authors, including email addresses citations for any papers, books, or other materials that provide additional information. ------------------------------------------------------------------------- Poster Layout Guidelines ------------------------------------------------------------------------- The format of posters and the nature of poster sessions require authors to capture the viewers' attention effectively, and present core concepts so as to clearly position the context of their research work. For this reason, graphic representations, figures, and screen shots are typically the main medium of communication in successful posters. Few attendees will stop to read a large poster with dense text. If screen shots are used, please ensure that they print legibly and that the fonts are large enough to be read easily once printed. The recommended size for the poster is A0 and all poster authors are required to print and bring their posters at the conference. Attendance At least one of the poster authors is required to register at the conference and will be required to give a brief presentation of the poster in the interactive poster session, as well as staying with the poster to discuss the work with conference attendees for the duration of the scheduled poster sessions. ------------------------------------------------------------------------- For More Information ------------------------------------------------------------------------- For additional information, clarification, or questions, please contact the Poster Chair. ------------------------------------------------------------------------- Poster Chair ------------------------------------------------------------------------- Sokratis Kartakis, Imperial College London, UK CallForTutorials.txt ========================================================================= Call for Tutorials FAS* - Foundation and Applications of Self* Computing Conferences 9th IEEE International Conference on Self-Adaptive and Self-Organizing System (SASO 2015) The International Conference on Cloud and Autonomic Computing (CAC 2015) The 15th IEEE Peer-to-Peer Computing Conference ========================================================================= ------------------------------------------------------------------------- Important Dates ------------------------------------------------------------------------- The exact deadlines are at 11:59 PM ET (Eastern Time Zone). - Proposal Submission Deadline: April 20, 2015 - Presenter Notification: April 27, 2015 - Extended Abstract and Presentation Handouts due: August 17, 2015 - Tutorial presentation: September 21-25, 2015 FAS* - Foundation and Applications of Self* Computing Conferences 2015 will host a joint tutorial program, hosted by MIT, Cambridge, Massachusetts, in the week of September 21-25, 2015. FAS* federates the 9th IEEE International Conference on Self-Adaptive and Self-Organizing System (SASO 2015), The International Conference on Cloud and Autonomic Computing (CAC 2015) and The 15th IEEE Peer-to-Peer Computing Conference. For detailed information about SASO 2015, CAC 2015 and P2P 2015 please visit their respective conference websites. ------------------------------------------------------------------------- Goal and Scope ------------------------------------------------------------------------- The goal of the tutorial program of FAS* 2015 is to provide an instructional offer to scholars, practitioners and students attending the conference, on a range of topics related to self* computing systems. We plan to accommodate either half-day tutorials (approx. 3.0 hours, plus one 30-minutes break) and full-day tutorials (approx 6.0 hours, plus two 30-minutes breaks, and a lunch break). The topic of a tutorial may range from practical techniques and technologies, to methodologies, guidelines over standards, to theoretical aspects related to self* systems (software, networks or services). The topic areas that fall into the general scope of FAS* conferences, as well as the focus of this year's conferences, are listed in the Call for Papers that is available on the FAS* conferences? web site. Please note that no marketing or product specific tutorials will be accepted. Tutorial levels may be introductory, intermediate, or advanced. Topics that can capture the interest of a broad audience of scholars, practitioners or students are preferred. ------------------------------------------------------------------------- Review Process ------------------------------------------------------------------------- Each tutorial proposal will be evaluated by the FAS* organizing committee according to relevance and to FAS* conferences and their communities, attractiveness and novelty of the topic, consistency with the focus of the conference, general fit within the overall tutorial program, and previous teaching experience of the proposers. ------------------------------------------------------------------------- Submission Guidelines ------------------------------------------------------------------------- Tutorial proposals must not be longer than three pages, in the same format of the FAS* research papers, that is, compliant with the IEEE Computer Society Press proceedings style. Please make sure the submission includes the following elements: - title of the tutorial; - preferred duration (half-day or full-day); - intended level (introductory, intermediate, or advanced) and prerequisites; - contact information for all presenters, including full name, affiliation, email address, full postal address, phone and fax number, URL of personal homepage; - short bio of all presenters including prior teaching and tutorial experiences; - description of the material covered by the tutorial, not exceeding two pages (approx. 1500 words): must include a proposed structure of the content to be presented; - identification of the target audience (e.g., researchers, teachers, practitioners, students); - references of publications (books, papers etc.) the tutorial builds on; - indication of whether the submission of a tutorial paper (see below) is planned. All proposals should be submitted as a PDF document via EasyChair athttps://easychair.org/conferences/?conf=fas2015 ------------------------------------------------------------------------- Accepted Proposals ------------------------------------------------------------------------- Once notified that the tutorial has been accepted, tutorial proposers should prepare a two-page extended abstract - compliant with the IEEE Computer Society Press proceedings style - describing the content of the tutorial, in addition to the handout material that is going to be distributed to the participants to their tutorial. Both the extended abstract and the handout material must be ready and submitted to the Tutorial Chair by the deadline noted above. ------------------------------------------------------------------------- Tutorials Chair ------------------------------------------------------------------------- Ivan Rodero, Rutgers, The State University of New Jersey, USA (irodero AT rutgers.edu) CallForWorkshops.txt ========================================================================= SASO 2015 Call For Workshops at the Ninth IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2015) Cambridge, MA September 21 & 25, 2015 http://saso2015.mit.edu ========================================================================= The SASO 2015 Steering Committee invites proposals for the Workshop Program to be held along with the technical conference. SASO 2015 workshops will provide a meeting for presenting novel ideas in a less formal and possibly more focused way than the conference itself. Its aim is to stimulate and facilitate active exchange, interaction, and comparison of approaches, methods, and ideas related to specific topics, both theoretical and applied, in the general area of Self-Adaptive and Self-Organizing Systems. To motivate the discussion and participation of all the workshop attendants, we encourage organizers to get away of the typical "mini-conference" format of a workshop, and include more discussion sessions, panels, etc. Members from all areas of the SASO community are invited to submit workshop proposals for review. Workshops on global challenges, applications or on new and emerging topics are particularly encouraged. Workshops can vary in length, but most will be one full day in dura tion. Optionally, if desired by the organizers, workshop proceedings can be published through IEEE. Attendance of workshops will be included in the registration fee for the main SASO conference. ------------------------------------------------------------------------- Important Dates ------------------------------------------------------------------------- - Proposal Submission Deadline: April 20, 2015 - Acceptance Notification: April 27, 2015 - CFP Submission Deadline: May 4, 2015 - Paper Submission Deadline: July 11, 2015 - Paper Acceptance Notification: July 31, 2015 - Early Registration Deadline: TBD - Camera-Ready Papers due: August 10, 2015 - Workshop notes submission to WS chairs: August 17, 2015 - Workshops dates: September 21 & 25, 2015 ------------------------------------------------------------------------- SASO 2015 Workshops - Requirements for Submission ------------------------------------------------------------------------- Proposals for workshops should be separated in two parts. The first part should be organized as preliminary call for papers or call for participation, depending on the intended format of the workshop with a maximum of two pages and contain the following information: - Title of the workshop. - A brief technical description of the workshop, specifying the workshop goals, the technical issues that it will address, and the relevance of the workshop to the main conference. - Description of paper review process (if any) and acceptance standards in order to keep the workshop high in quality. Note that papers must be in the same format as the conference proceedings and may not be more than 6 pages in length. - The names, affiliations, postal addresses, phone numbers, and email addresses of the proposed workshop organizing committee. This committee should consist of three or four people knowledgeable about the technical issues to be addressed. The organizing committee should include individuals from multiple institutions. - The primary email address for contacting the organizing committee. - Expected duration of the workshop (half or full day). - A brief description of the workshop format. - List of potential program committee members (if applicable), including their title and affiliations. - List of potential invited speakers, panelists, or disputants (if applicable). The second part with a maximum of three pages should contain additional information not suitable for a Call for Papers, including: - A discussion of why and to whom the workshop is of interest. - A list of related workshops held within the last three years, if any, and their relation to the proposed workshop. - Information about previous offerings of the proposed workshop: when and where it has been offered in the past, organizers names and affiliations, number of submissions, acceptances and registered attendees. - A description of the qualifications of the individual committee members with respect to organizing a SASO workshop, including a list of workshops previously arranged by any members of the proposed organizing committee, if any. - A list of places (distribution lists, web sites, journals, etc.) where the workshop is planned to be advertised. All proposals should be submitted in plain ASCII text or PDF format by electronic mail to the SASO 2015 Workshops Chair. The selection of the workshops to be included in the final SASO 2015 Workshop program will be based upon multiple factors, including: - the scientific/technical interest of the topics, - the quality of the proposal, - complementarity with the conference topics, - balance and distinctness of workshop topics, - and the capacity of the conference workshop program. Note that authors of proposals addressing similar and/or overlapping content areas and/or audiences may be requested to merge their proposals. ------------------------------------------------------------------------- Responsibilities of SASO 2015 and Workshop Organizers ------------------------------------------------------------------------- For all accepted proposals, SASO 2015 will be responsible for: - Providing publicity for the workshop series as a whole. - Providing logistical support and a meeting place for the workshop. - Together with the organizers, determining the workshop date and time. - Liaising and coordinating between the workshop chairs and the finance chair, publicity chair, registration chair, and web chair for SASO. - Arranging for publication of proceedings. Workshop organizers will be responsible for the following: - Setting up a web site for the workshop. - Advertising the workshop (and the main SASO conference), and issuing a call for papers and a call for participation. - Collecting and evaluating submissions, notifying authors of acceptance or rejection on a timely basis, and ensuring a transparent and fair selection process. All workshop organizers commit themselves to adopt the deadlines set by the committee. - Making the pdf of the whole workshop notes available to the workshop chair, as well as a list of audio-visual requirements and any special room requirements. - Writing a 1-page organizers introduction for your proceedings. - Ensuring that the workshop organizers and the participants register for the workshop and/or the main conference (at least one author must register for the paper to appear in the proceedings). SASO reserves the right to cancel any workshop if the above responsibilities are not fulfilled, or if too few attendees register for the workshop to support its running costs. ------------------------------------------------------------------------- Submissions and Inquiries ------------------------------------------------------------------------- Please send proposals (as a PDF document) and inquiries to the SASO 2015 workshop chair: Gauthier Picard (MINES Saint-Etienne, France) gauthier.picard at emse.fr CfP-SASO2015.txt ****************************************************************************************** CALL FOR PAPERS The Ninth IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2015) Boston Massachusetts; 21-25 September 2015 https://saso2015.mit.edu/ ****************************************************************************************** Part of FAS* - Foundation and Applications of Self* Computing Conferences Collocated with: The International Conference on Cloud and Autonomic Computing (CAC 2015) The 15th IEEE Peer-to-Peer Computing Conference (P2P 2015) ------------------- Aims and Scope ------------------- The aim of the Self-Adaptive and Self-Organizing systems conference series (SASO) is to provide a forum for the foundations of a principled approach to engineering systems, networks and services based on self-adaptation and self-organization. The complexity of current and emerging networks, software and services, especially in dealing with dynamics in the environment and problem domain, has led the software engineering, distributed systems and management communities to look for inspiration in diverse fields (e.g., complex systems, control theory, artificial intelligence, sociology, and biology) to find new ways of designing and managing such computing systems. In this endeavor, self-organization and self-adaptation have emerged as two promising interrelated approaches. They form the basis for many other self-* properties, such as self-configuration, self-healing, or self-optimization. Systems exhibiting such properties are often referred to as self-* systems. The ninth edition of the SASO conference embraces the inter-disciplinarity and the scientific, empirical, and application dimensions of self-* systems and welcomes novel results on both self-adaptive and self-organizing systems research. The topics of interest include, but are not limited to: - Self-* systems theory: theoretical frameworks and models; biologically- and socially-inspired paradigms; inter-operation of self-* mechanisms; - Self-* systems engineering: reusable mechanisms, design patterns, architectures, methodologies; software and middleware development frameworks and methods, platforms and toolkits; hardware; self-* materials; - Self-* system properties: robustness, resilience and stability; emergence; computational awareness and self-awareness; reflection; - Self-* cyber-physical and socio-technical systems: human factors and visualization; self-* social computers; crowdsourcing and collective awareness; human-in-the-loop; - Applications and experiences of self-* systems: cyber security, transportation, computational sustainability, big data and creative commons, power systems; swarm systems and robotics. - Self-* in education: experience reports; curricula; innovative course concepts; methodological aspects of self-* systems education Contributions must present novel theoretical or experimental results; novel design patterns, mechanisms, system architectures, frameworks or tools; or practical approaches and experiences in building or deploying real-world systems and applications. Contributions contrasting different approaches for engineering a given family of systems, or demonstrating the applicability of a certain approach for different systems, are equally encouraged. Likewise, papers describing substantial innovation or insights in the use and communication of self-* systems in the classroom are welcome. Where relevant and appropriate, accepted papers will also be encouraged to participate in the Demo or Poster Sessions. -------------------- Important Dates -------------------- Abstract submission: May 8, 2015 Paper submission: May 22, 2015 (There will be no extensions of this deadline!) Notification: June 30, 2015 Camera ready copy due: July 17, 2015 Conference: September 21-25, 2015 ---------------------------- Submission Instructions ---------------------------- All submissions should be 10 pages and formatted according to the IEEE Computer Society Press proceedings style guide and submitted electronically in PDF format. Please register as authors and submit your papers using the SASO 2015 conference management system that will be announced on the website. The proceedings will be published by IEEE Computer Society Press, and made available as a part of the IEEE Digital Library. Note that a separate Call for Poster Submissions will also be issued. --------------------- Review Criteria --------------------- Papers should present novel ideas in the cross-disciplinary research context described in this call, clearly motivated by problems from current practice or applied research. We expect both theoretical and empirical contributions to be clearly stated, substantiated by formal analysis, simulation, experimental evaluations, comparative studies, and so on. Appropriate reference must be made to related work. Because SASO is a cross-disciplinary conference, papers must be intelligible and relevant to researchers who are not members of the same specialized sub-field. Authors are also encouraged to submit papers describing applications. Application papers are expected to provide an indication of the real world relevance of the problem that is solved, including a description of the deployment domain, and some form of evaluation of performance, usability, or comparison to alternative approaches. Experience papers are also welcome but they must clearly state the insight into any aspect of design, implementation or management of self-* systems which is of benefit to practitioners and the SASO community. ------------------------------- Conference General Chairs ------------------------------- Howard E Shrobe MIT CSAIL, Cambridge, MA, USA Julie A McCann Imperial College London, UK -------------------- Program Chairs -------------------- Emma Hart Edinburgh Napier University Gregory Sullivan BAE Systems AIT Jan-Philipp Stegh?fer University of Gothenburg, Sweden -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- ========================================================================= SASO 2015 Call for Demos ========================================================================= ------------------------------------------------------------------------- Overview ------------------------------------------------------------------------- The demonstration track at SASO 2015 aims at providing an opportunity to participants from academia and industry to present their latest applications and systems to fellow researchers and practitioners in the field. Submissions will be evaluated based on their overall self-* characteristics, originality and maturity. The committee will particularly consider system robustness, resilience and scaling abilities in addition to the self-* functions of the contributions. Interactivity of the demos will be considered a further asset. ------------------------------------------------------------------------- Demonstrations may target: ------------------------------------------------------------------------- - virtual systems, such as software applications; - physical systems, such as robots or sensor networks; - cyber-physical systems, combining the above; where physical systems might be presented either with real equipment, by simulation, or hybrid demos using both simulations and real platforms. We particularly solicit authors to highlight the utility and general applicability of their contributions, whether for the short, medium or long term. This call is open to the full range of conference topics, however we encourage authors to also consider socio-inspired and normative systems as focus issue. These comprise self-adaptive and self-organizing algorithms, platforms and coordination mechanisms which are influenced by the design or modeling of social and normative systems. ------------------------------------------------------------------------- Submission ------------------------------------------------------------------------- Demonstration submissions must include: a short paper (2 pages, conference format) describing the system and its self-* capabilities; if accepted, papers will be published in the official proceedings; a URL of a website providing a self-explanatory video showing the system at work; and (optionally) allowing viewers to interact with the real system or with an emulator. Electronic submission: Not available yet. At the conference, software applications will be presented on computers. For cyber-physical systems, if possible, authors are invited to bring their equipment (smart devices, sensors, actuators, robots, et cetera). Software simulations or video recordings can be accepted as an alternative. Additionally, authors must bring a poster summarizing their system and demo. ------------------------------------------------------------------------- Important Dates ------------------------------------------------------------------------- Deadline for demo submission : June 15, 2015 Notification: July 17, 2015 Conference: September 21-25, 2015 ------------------------------------------------------------------------- Evaluation and Awards ------------------------------------------------------------------------- Submitted demos will undergo a selection process based to equal parts on the quality of the short paper (novelty and impact, technical soundness and presentation) and the online demo system (design, degree of innovation, technical solution, applicability, clarity of the contribution and potential of reuse). At least one author of accepted demos is required to register to the conference and to do an on-site presentation and demonstration of the contributions to the evaluation committee, as well as the other conference attendees. The evaluation committee, consisting of the Demo Program Committee members attending the conference, will award a prize for the best demo in each system category, with cyber-physical systems classifying for both. ------------------------------------------------------------------------- For More Information ------------------------------------------------------------------------- Please contact the chairs for any questions regarding the Demonstration session. ------------------------------------------------------------------------- Demonstration Chair ------------------------------------------------------------------------- Sokratis Kartakis, Imperial College London, UK -------------- next part -------------- ========================================================================= Call for Doctoral Consortium ========================================================================= The aim of FAS* Doctoral Symposium is to provide an international forum for PhD Students working in any of the areas addressed by FAS*. PhD students have the opportunity to discuss their research in an international forum, and with a panel of well-known experts in the field. PhD students working in any area addressed by the FAS* conferences can submit a paper describing the core problem of their PhD research and its relevance by providing a clear statement of the problem they intend to address, the motivation of the interest and novelty of the underlying research challenges, the explanation of the main ideas by examples, and a description of the proposed research plan and expected results. The topics of interest include, but are not limited to: - Self-* systems theory; - Self-* systems engineering; - Self-* system properties; - Self-* cyber-physical and socio-technical systems; - Applications and experiences of self-* systems; - Autonomic Cloud Computing; - Autonomics for Extreme Scales; - Autonomic Computing Foundations and Design Methods; - Autonomic Computing Systems, Tools and Applications; - P2P techniques and algorithms; - Experience with widely-deployed and commercial systems and applications; - Measurement and modeling of P2P systems, cloud systems, and large-scale distributed systems; - P2P applications and systems running in the Internet, in clouds, and in mobile systems; - Semantic overlay networks and semantic query routing; - Information retrieval and query support; - Security, privacy, anonymity, and anti-censorship; - P2P economics, participation incentives, trust, reputation, incentives, fairness, policy enforcement; - Overlay architectures and technologies; - Performance, availability, robustness, and scalability; - New applications of P2P technologies; ------------------------------------------------------------------------- SUBMISSION INSTRUCTIONS ------------------------------------------------------------------------- All submissions should be 6 pages and formatted according to the IEEE Computer Society Press proceedings style guide and submitted electronically in PDF format. Please register as authors and submit your papers using the FAS* 2015 PhD Symposium management system, which is located at: https://easychair.org/conferences/?conf=fasphd2015 Submissions must be single-author, on the topic of the doctoral work. The name of the supervisor must be clearly marked (? supervised by ? ?) on the paper, under the author?s name. Submissions should be written using the following structure: - Problem: describe the problem that must be solved by the PhD student and motivate its relevance. - Motivating Scenario and Research Challenges: present a simple scenario in a specific application domain to motivate the research and highlight its challenges. - State of the art: position the work with respects to relevant related work. - Methodology: present the methodology that will be adopted. - Current Status: describe the current status of the work and the preliminary results that have been already reached. - Research Plan: conclude specifying the plan for the overall PhD. ------------------------------------------------------------------------- IMPORTANT DATES ------------------------------------------------------------------------- - Abstract Submission Deadline: June 1, 2015 - Paper Submission Deadline: June 15, 2015 - Notifications of Acceptance: July 3, 2015 - Camera ready copy due: July 17, 2015 - Conference: September 21-25, 2015 ------------------------------------------------------------------------- REVIEW PROCESS, FORMAT OF THE SYMPOSIUM, and AWARD ------------------------------------------------------------------------- Each submission will be reviewed by at least two experts of the PhD Symposium organization and will be evaluated in terms of their relevance to the FAS* topics, motivation and research challenges, soundness of the methodology proposed and feasibility of the research plan. Each accepted paper will have two different opportunities to be presented. Besides the full presentation during the PhD Symposium session, during the main conference, a ?PhD Elevator Pitch Session? will be organized where each PhD student will showcase his/her research shortly. The Best Doctoral Symposium paper will be selected and the award will be presented during the main conference. ------------------------------------------------------------------------- INVITED TALK ------------------------------------------------------------------------- Dr. Jeremy Pitt (Imperial College London) ? Title: ?How To Get a PhD in Self-Organizing Systems?. ------------------------------------------------------------------------- PhD SYMPOSIUM EXPERTS ------------------------------------------------------------------------- - Luciano Baresi, DEIB - Politecnico di Milano ? Italy - Geoffrey Fox - Indiana University Bloomington, USA - Kurt Geihs ? Universitaet Kassel - Salim Hariri University of Arizona, USA - Pedro Garcia Lopez, Universitat Rovira i Virgili, Spain - Julie McCann - Imperial College, UK - Alberto Montresor, University of Trento ? Italy - Manish Parashar - Rutgers University, USA - Jeremy Pitt ? Imperial College London ? UK ------------------------------------------------------------------------- CONTACT INFORMATION ------------------------------------------------------------------------- Doctoral Symposium Chair: Antonio Bucchiarone (FBK-DAS, Trento, Italy) For information, email to bucchiarone at fbk.eu -------------- next part -------------- ========================================================================= SASO 2015 Call for Tutorials Call for Posters ========================================================================= ------------------------------------------------------------------------- Overview ------------------------------------------------------------------------- The ninth SASO conference continues its tradition of offering poster sessions, a great opportunity for interactive presentation of emerging ideas, late-breaking results, experiences, and challenges on SASO topics. Poster sessions are informal and highly interactive, and allow authors and participants to engage in in-depth discussions about the presented work from which new collaborations, ideas, and solutions can emerge. Posters should cover the same key areas as Research Papers and should contain original cutting-edge ideas, as well as speculative/provocative ones. Proposals of new research directions and innovative interdisciplinary approaches are also welcome. Submissions in the following areas are particularly encouraged: - Self-* systems theories, frameworks, models, and paradigms, including the ones inspired by the biological, social, and physical worlds. - Self-* systems engineering: goals and requirements, hardware and software design, deployment, management and control, validation. - Properties of self-* systems: self-organisation and emergent behaviour, self- adaptation, self-management, self-monitoring, self-tuning, self-repair, self- configuration, etc. - Evaluation of self-* systems: methods for performance, robustness, and dependability assessment and analysis. - Social self-* systems: emergent human behaviour, crowdsourcing, collective awareness, gamification and serious games. - Applications and experiences with self-* systems: cyber security, transportation, computational sustainability, power systems, large networks, large data centers, and cloud computing. ------------------------------------------------------------------------- Submission Process ------------------------------------------------------------------------- For evaluation and selection, authors should submit a two-page extended abstract of their poster. The format of this extended abstract must comply with the IEEE Computer Society Press proceedings style guide and it shall be submitted electronically in PDF format. Templates for Word and LaTeX are available here. Electronic submission: Not available yet. ------------------------------------------------------------------------- Important Dates ------------------------------------------------------------------------- Deadline for submission: May 22, 2015 Notification: June 30, 2015 Camera ready copy due: July 17, 2015 Conference: September 21-25, 2015 ------------------------------------------------------------------------- Accepted Posters ------------------------------------------------------------------------- If selected, authors shall prepare a final, camera ready version of the extended abstract, taking into account all feedback from reviewers, and formatted according to the IEEE Computer Society Press proceedings style guide. Posters will be advertised in the final program, and authors' two-page extended abstracts will be submitted to IEEE Xplore as part of the conference proceedings. Abstracts will also be available as part of the IEEE Digital Library. ------------------------------------------------------------------------- Poster Content ------------------------------------------------------------------------- Authors shall prepare their poster for presentation in the reserved poster session, taking into consideration that all posters should include the following information: The purpose and goals of the work. Any background and motivation needed to understand the work. Any critical hypotheses and assumptions that underlie the work. A clear summary of the contribution and/or results, in sufficient detail for a (re)viewer to understand the work and its relevance. If the work is at an initial stage, it is especially important to state clearly the anticipated contributions and any early results towards them. The relationship to other related efforts, where appropriate. Authors of accepted posters may be asked to point out relationships to work represented by other accepted posters. Where to find additional information. This should include but is not restricted to: a web site where viewers can go to find additional information about the work how to contact the authors, including email addresses citations for any papers, books, or other materials that provide additional information. ------------------------------------------------------------------------- Poster Layout Guidelines ------------------------------------------------------------------------- The format of posters and the nature of poster sessions require authors to capture the viewers' attention effectively, and present core concepts so as to clearly position the context of their research work. For this reason, graphic representations, figures, and screen shots are typically the main medium of communication in successful posters. Few attendees will stop to read a large poster with dense text. If screen shots are used, please ensure that they print legibly and that the fonts are large enough to be read easily once printed. The recommended size for the poster is A0 and all poster authors are required to print and bring their posters at the conference. Attendance At least one of the poster authors is required to register at the conference and will be required to give a brief presentation of the poster in the interactive poster session, as well as staying with the poster to discuss the work with conference attendees for the duration of the scheduled poster sessions. ------------------------------------------------------------------------- For More Information ------------------------------------------------------------------------- For additional information, clarification, or questions, please contact the Poster Chair. ------------------------------------------------------------------------- Poster Chair ------------------------------------------------------------------------- Sokratis Kartakis, Imperial College London, UK -------------- next part -------------- ========================================================================= Call for Tutorials FAS* - Foundation and Applications of Self* Computing Conferences 9th IEEE International Conference on Self-Adaptive and Self-Organizing System (SASO 2015) The International Conference on Cloud and Autonomic Computing (CAC 2015) The 15th IEEE Peer-to-Peer Computing Conference ========================================================================= ------------------------------------------------------------------------- Important Dates ------------------------------------------------------------------------- The exact deadlines are at 11:59 PM ET (Eastern Time Zone). - Proposal Submission Deadline: April 20, 2015 - Presenter Notification: April 27, 2015 - Extended Abstract and Presentation Handouts due: August 17, 2015 - Tutorial presentation: September 21-25, 2015 FAS* - Foundation and Applications of Self* Computing Conferences 2015 will host a joint tutorial program, hosted by MIT, Cambridge, Massachusetts, in the week of September 21-25, 2015. FAS* federates the 9th IEEE International Conference on Self-Adaptive and Self-Organizing System (SASO 2015), The International Conference on Cloud and Autonomic Computing (CAC 2015) and The 15th IEEE Peer-to-Peer Computing Conference. For detailed information about SASO 2015, CAC 2015 and P2P 2015 please visit their respective conference websites. ------------------------------------------------------------------------- Goal and Scope ------------------------------------------------------------------------- The goal of the tutorial program of FAS* 2015 is to provide an instructional offer to scholars, practitioners and students attending the conference, on a range of topics related to self* computing systems. We plan to accommodate either half-day tutorials (approx. 3.0 hours, plus one 30-minutes break) and full-day tutorials (approx 6.0 hours, plus two 30-minutes breaks, and a lunch break). The topic of a tutorial may range from practical techniques and technologies, to methodologies, guidelines over standards, to theoretical aspects related to self* systems (software, networks or services). The topic areas that fall into the general scope of FAS* conferences, as well as the focus of this year's conferences, are listed in the Call for Papers that is available on the FAS* conferences? web site. Please note that no marketing or product specific tutorials will be accepted. Tutorial levels may be introductory, intermediate, or advanced. Topics that can capture the interest of a broad audience of scholars, practitioners or students are preferred. ------------------------------------------------------------------------- Review Process ------------------------------------------------------------------------- Each tutorial proposal will be evaluated by the FAS* organizing committee according to relevance and to FAS* conferences and their communities, attractiveness and novelty of the topic, consistency with the focus of the conference, general fit within the overall tutorial program, and previous teaching experience of the proposers. ------------------------------------------------------------------------- Submission Guidelines ------------------------------------------------------------------------- Tutorial proposals must not be longer than three pages, in the same format of the FAS* research papers, that is, compliant with the IEEE Computer Society Press proceedings style. Please make sure the submission includes the following elements: - title of the tutorial; - preferred duration (half-day or full-day); - intended level (introductory, intermediate, or advanced) and prerequisites; - contact information for all presenters, including full name, affiliation, email address, full postal address, phone and fax number, URL of personal homepage; - short bio of all presenters including prior teaching and tutorial experiences; - description of the material covered by the tutorial, not exceeding two pages (approx. 1500 words): must include a proposed structure of the content to be presented; - identification of the target audience (e.g., researchers, teachers, practitioners, students); - references of publications (books, papers etc.) the tutorial builds on; - indication of whether the submission of a tutorial paper (see below) is planned. All proposals should be submitted as a PDF document via EasyChair at https://easychair.org/conferences/?conf=fas2015 ------------------------------------------------------------------------- Accepted Proposals ------------------------------------------------------------------------- Once notified that the tutorial has been accepted, tutorial proposers should prepare a two-page extended abstract - compliant with the IEEE Computer Society Press proceedings style - describing the content of the tutorial, in addition to the handout material that is going to be distributed to the participants to their tutorial. Both the extended abstract and the handout material must be ready and submitted to the Tutorial Chair by the deadline noted above. ------------------------------------------------------------------------- Tutorials Chair ------------------------------------------------------------------------- Ivan Rodero, Rutgers, The State University of New Jersey, USA (irodero AT rutgers.edu) -------------- next part -------------- ========================================================================= SASO 2015 Call For Workshops at the Ninth IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2015) Cambridge, MA September 21 & 25, 2015 http://saso2015.mit.edu ========================================================================= The SASO 2015 Steering Committee invites proposals for the Workshop Program to be held along with the technical conference. SASO 2015 workshops will provide a meeting for presenting novel ideas in a less formal and possibly more focused way than the conference itself. Its aim is to stimulate and facilitate active exchange, interaction, and comparison of approaches, methods, and ideas related to specific topics, both theoretical and applied, in the general area of Self-Adaptive and Self-Organizing Systems. To motivate the discussion and participation of all the workshop attendants, we encourage organizers to get away of the typical "mini-conference" format of a workshop, and include more discussion sessions, panels, etc. Members from all areas of the SASO community are invited to submit workshop proposals for review. Workshops on global challenges, applications or on new and emerging topics are particularly encouraged. Workshops can vary in length, but most will be one full day in duration. Optionally, if desired by the organizers, workshop proceedings can be published through IEEE. Attendance of workshops will be included in the registration fee for the main SASO conference. ------------------------------------------------------------------------- Important Dates ------------------------------------------------------------------------- - Proposal Submission Deadline: April 20, 2015 - Acceptance Notification: April 27, 2015 - CFP Submission Deadline: May 4, 2015 - Paper Submission Deadline: July 11, 2015 - Paper Acceptance Notification: July 31, 2015 - Early Registration Deadline: TBD - Camera-Ready Papers due: August 10, 2015 - Workshop notes submission to WS chairs: August 17, 2015 - Workshops dates: September 21 & 25, 2015 ------------------------------------------------------------------------- SASO 2015 Workshops - Requirements for Submission ------------------------------------------------------------------------- Proposals for workshops should be separated in two parts. The first part should be organized as preliminary call for papers or call for participation, depending on the intended format of the workshop with a maximum of two pages and contain the following information: - Title of the workshop. - A brief technical description of the workshop, specifying the workshop goals, the technical issues that it will address, and the relevance of the workshop to the main conference. - Description of paper review process (if any) and acceptance standards in order to keep the workshop high in quality. Note that papers must be in the same format as the conference proceedings and may not be more than 6 pages in length. - The names, affiliations, postal addresses, phone numbers, and email addresses of the proposed workshop organizing committee. This committee should consist of three or four people knowledgeable about the technical issues to be addressed. The organizing committee should include individuals from multiple institutions. - The primary email address for contacting the organizing committee. - Expected duration of the workshop (half or full day). - A brief description of the workshop format. - List of potential program committee members (if applicable), including their title and affiliations. - List of potential invited speakers, panelists, or disputants (if applicable). The second part with a maximum of three pages should contain additional information not suitable for a Call for Papers, including: - A discussion of why and to whom the workshop is of interest. - A list of related workshops held within the last three years, if any, and their relation to the proposed workshop. - Information about previous offerings of the proposed workshop: when and where it has been offered in the past, organizers names and affiliations, number of submissions, acceptances and registered attendees. - A description of the qualifications of the individual committee members with respect to organizing a SASO workshop, including a list of workshops previously arranged by any members of the proposed organizing committee, if any. - A list of places (distribution lists, web sites, journals, etc.) where the workshop is planned to be advertised. All proposals should be submitted in plain ASCII text or PDF format by electronic mail to the SASO 2015 Workshops Chair. The selection of the workshops to be included in the final SASO 2015 Workshop program will be based upon multiple factors, including: - the scientific/technical interest of the topics, - the quality of the proposal, - complementarity with the conference topics, - balance and distinctness of workshop topics, - and the capacity of the conference workshop program. Note that authors of proposals addressing similar and/or overlapping content areas and/or audiences may be requested to merge their proposals. ------------------------------------------------------------------------- Responsibilities of SASO 2015 and Workshop Organizers ------------------------------------------------------------------------- For all accepted proposals, SASO 2015 will be responsible for: - Providing publicity for the workshop series as a whole. - Providing logistical support and a meeting place for the workshop. - Together with the organizers, determining the workshop date and time. - Liaising and coordinating between the workshop chairs and the finance chair, publicity chair, registration chair, and web chair for SASO. - Arranging for publication of proceedings. Workshop organizers will be responsible for the following: - Setting up a web site for the workshop. - Advertising the workshop (and the main SASO conference), and issuing a call for papers and a call for participation. - Collecting and evaluating submissions, notifying authors of acceptance or rejection on a timely basis, and ensuring a transparent and fair selection process. All workshop organizers commit themselves to adopt the deadlines set by the committee. - Making the pdf of the whole workshop notes available to the workshop chair, as well as a list of audio-visual requirements and any special room requirements. - Writing a 1-page organizers introduction for your proceedings. - Ensuring that the workshop organizers and the participants register for the workshop and/or the main conference (at least one author must register for the paper to appear in the proceedings). SASO reserves the right to cancel any workshop if the above responsibilities are not fulfilled, or if too few attendees register for the workshop to support its running costs. ------------------------------------------------------------------------- Submissions and Inquiries ------------------------------------------------------------------------- Please send proposals (as a PDF document) and inquiries to the SASO 2015 workshop chair: Gauthier Picard (MINES Saint-Etienne, France) gauthier.picard at emse.fr -------------- next part -------------- ****************************************************************************************** CALL FOR PAPERS The Ninth IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2015) Boston Massachusetts; 21-25 September 2015 https://saso2015.mit.edu/ ****************************************************************************************** Part of FAS* - Foundation and Applications of Self* Computing Conferences Collocated with: The International Conference on Cloud and Autonomic Computing (CAC 2015) The 15th IEEE Peer-to-Peer Computing Conference (P2P 2015) ------------------- Aims and Scope ------------------- The aim of the Self-Adaptive and Self-Organizing systems conference series (SASO) is to provide a forum for the foundations of a principled approach to engineering systems, networks and services based on self-adaptation and self-organization. The complexity of current and emerging networks, software and services, especially in dealing with dynamics in the environment and problem domain, has led the software engineering, distributed systems and management communities to look for inspiration in diverse fields (e.g., complex systems, control theory, artificial intelligence, sociology, and biology) to find new ways of designing and managing such computing systems. In this endeavor, self-organization and self-adaptation have emerged as two promising interrelated approaches. They form the basis for many other self-* properties, such as self-configuration, self-healing, or self-optimization. Systems exhibiting such properties are often referred to as self-* systems. The ninth edition of the SASO conference embraces the inter-disciplinarity and the scientific, empirical, and application dimensions of self-* systems and welcomes novel results on both self-adaptive and self-organizing systems research. The topics of interest include, but are not limited to: - Self-* systems theory: theoretical frameworks and models; biologically- and socially-inspired paradigms; inter-operation of self-* mechanisms; - Self-* systems engineering: reusable mechanisms, design patterns, architectures, methodologies; software and middleware development frameworks and methods, platforms and toolkits; hardware; self-* materials; - Self-* system properties: robustness, resilience and stability; emergence; computational awareness and self-awareness; reflection; - Self-* cyber-physical and socio-technical systems: human factors and visualization; self-* social computers; crowdsourcing and collective awareness; human-in-the-loop; - Applications and experiences of self-* systems: cyber security, transportation, computational sustainability, big data and creative commons, power systems; swarm systems and robotics. - Self-* in education: experience reports; curricula; innovative course concepts; methodological aspects of self-* systems education Contributions must present novel theoretical or experimental results; novel design patterns, mechanisms, system architectures, frameworks or tools; or practical approaches and experiences in building or deploying real-world systems and applications. Contributions contrasting different approaches for engineering a given family of systems, or demonstrating the applicability of a certain approach for different systems, are equally encouraged. Likewise, papers describing substantial innovation or insights in the use and communication of self-* systems in the classroom are welcome. Where relevant and appropriate, accepted papers will also be encouraged to participate in the Demo or Poster Sessions. -------------------- Important Dates -------------------- Abstract submission: May 8, 2015 Paper submission: May 22, 2015 (There will be no extensions of this deadline!) Notification: June 30, 2015 Camera ready copy due: July 17, 2015 Conference: September 21-25, 2015 ---------------------------- Submission Instructions ---------------------------- All submissions should be 10 pages and formatted according to the IEEE Computer Society Press proceedings style guide and submitted electronically in PDF format. Please register as authors and submit your papers using the SASO 2015 conference management system that will be announced on the website. The proceedings will be published by IEEE Computer Society Press, and made available as a part of the IEEE Digital Library. Note that a separate Call for Poster Submissions will also be issued. --------------------- Review Criteria --------------------- Papers should present novel ideas in the cross-disciplinary research context described in this call, clearly motivated by problems from current practice or applied research. We expect both theoretical and empirical contributions to be clearly stated, substantiated by formal analysis, simulation, experimental evaluations, comparative studies, and so on. Appropriate reference must be made to related work. Because SASO is a cross-disciplinary conference, papers must be intelligible and relevant to researchers who are not members of the same specialized sub-field. Authors are also encouraged to submit papers describing applications. Application papers are expected to provide an indication of the real world relevance of the problem that is solved, including a description of the deployment domain, and some form of evaluation of performance, usability, or comparison to alternative approaches. Experience papers are also welcome but they must clearly state the insight into any aspect of design, implementation or management of self-* systems which is of benefit to practitioners and the SASO community. ------------------------------- Conference General Chairs ------------------------------- Howard E Shrobe MIT CSAIL, Cambridge, MA, USA Julie A McCann Imperial College London, UK -------------------- Program Chairs -------------------- Emma Hart Edinburgh Napier University Gregory Sullivan BAE Systems AIT Jan-Philipp Stegh?fer University of Gothenburg, Sweden From Hugo.Larochelle at USherbrooke.ca Mon Mar 23 14:44:15 2015 From: Hugo.Larochelle at USherbrooke.ca (Hugo Larochelle) Date: Mon, 23 Mar 2015 18:44:15 +0000 Subject: Connectionists: 2nd CfP: ACL Workshop on Continuous Vector Space Models and their Compositionality (CVSC), 3rd edition Message-ID: Second Call for Papers (Apologies for multiple postings) **************************************************************************************************** Workshop on Continuous Vector Space Models and their Compositionality (3rd edition) Co-located with ACL 2015, Beijing, China July 31, 2015 Submission deadline: May 14, 2015 https://sites.google.com/site/cvscworkshop2015 **************************************************************************************************** INVITED SPEAKERS The workshop will showcase presentations from 5 keynote speakers. ? Kyunghyun Cho (Universit? de Montr?al) ? Stephen Clark (University of Cambridge) ? Yoav Goldberg (Bar Ilan University) ? Ray Mooney (University of Texas at Austin) ? Jason Weston (Facebook AI Research) AIMS AND SCOPE In recent years, there has been a growing interest in algorithms that learn and use continuous representations for words, phrases, or documents in many natural language processing applications. Among many others, influential proposals that illustrate this trend include latent Dirichlet allocation, neural network based language models and spectral methods. These approaches are motivated by improving the generalization power of the discrete standard models, by dealing with the data sparsity issue and by efficiently handling a wide context. Despite the success of single word vector space models, they are limited since they do not capture compositionality. This prevents them from gaining a deeper understanding of the semantics of longer phrases, sentences and documents. Regarding this issue, some pertinent questions arise: should word/phrase/sentence representations be of the same sort? Could different linguistic levels require different modelling approaches ? Is compositionality determined by syntax, and if so, how do we learn/define it? Should word representations be fixed and obtained distributionally, or should the encoding be variable? Should word representations be task-specific, or should they be general? In this workshop, we invite submissions of papers on continuous vector space models for natural language processing. Topics of interest include, but are not limited to: * Neural networks * Spectral methods * Distributional semantic models * Language modeling for automatic speech recognition, statistical machine translation, and information retrieval * Automatic annotation of texts * Phrase and sentence-level distributional representations * The role of syntax in compositional models * Formal and distributional semantic models * Language modeling for logical and natural reasoning * Integration of distributional representations with other models * Multi-modal learning for distributional representations * Knowledge base embedding SUBMISSION INFORMATION Authors should submit a full paper of up to 8 pages in electronic, PDF format, with up to 2 additional pages for references. The reported research should be substantially original. The papers will be presented orally or as posters. All submissions must be in PDF format and must follow the ACL 2015 formatting requirements (see the ACL 2015 Call For Papers http://acl2015.org/call_for_papers.html). Reviewing will be double-blind, and thus no author information should be included in the papers; self-reference should be avoided as well. Submissions must be made through the Softconf website set up for this workshop: https://www.softconf.com/acl2015/CVSC/ Accepted papers will appear in the workshop proceedings, where no distinction will be made between papers presented orally or as posters. IMPORTANT DATES 14 May 2015 : Submission deadline 4 June 2015 : Notification of acceptance 21 June 2015 : Camera-ready deadline 31 July 2015 : Workshop ORGANIZERS Alexandre Allauzen (LIMSI-CNRS/Universit? Paris-Sud, France) Edward Grefenstette (Google DeepMind, UK) Karl Moritz Hermann (Google DeepMind, UK) Hugo Larochelle (Universit? de Sherbrooke, Canada) Scott Wen-tau Yih (Microsoft Research, USA) PROGRAM COMMITTEE Marco Baroni, University of Trento Yoshua Bengio, Universit? de Montreal Phil Blunsom, University of Oxford Antoine Bordes, Facebook Leon Bottou, Facebook Stephen Clark, University of Cambridge Shay Cohen, University of Edinburgh Georgiana Dinu, University of Trento Kevin Duh, Nara Institute of Science and Technology Yoav Goldberg, Bar Ilan University Andriy Mnih, Google DeepMind Mehrnoosh Sadrzadeh, University of London Mark Steedman, University of Edinburgh Peter Turney, NRC Jason Weston, Facebook Guillaume Wisniewski, LIMSI-CNRS From thomaskreuz at gmail.com Wed Mar 25 12:43:07 2015 From: thomaskreuz at gmail.com (Thomas Kreuz) Date: Wed, 25 Mar 2015 17:43:07 +0100 Subject: Connectionists: 15 PhD Fellowships - Complex Oscillatory Systems: Modeling and Analysis (COSMOS) Message-ID: The following announcement could be of high interest to the Connectionists-Community. Projects deal among others with neural networks, pulse-coupled oscillatory networks, directional coupling, networks of spiking neurons. European Joint Doctorates Programme Complex Oscillatory Systems: Modeling and Analysis (COSMOS) announces 15 PhD Fellowships. COSMOS is a Marie Sk?odowska-Curie Action Innovative Training Network (MSCA-ITN-2014-EJD 642563) aiming at an understanding of the general properties of collective dynamics and synchronization of complex systems composed of oscillatory elements. It includes both theoretical projects where such systems are studied with the methods of nonlinear dynamics and statistical physics, as well as applied ones related to the analysis of experimental multivariate time series, such as physiological and neural data. The COSMOS network is highly interdisciplinary, and fellows will benefit from interactions with world-leading researchers in a broad range of disciplines. ESR positions are available at following universities: University of Potsdam, University of Aberdeen, Lancaster University, University of Florence, University Pompeu Fabra (Barcelona), VU University Amsterdam, Faculty of Information studies in Novo Mesto (Slovenia), and Medical University of Graz. All fellows will be jointly supervised by two partner universities and will receive a PhD degree from each of them. Most of the fellows are expected to be hired in July 2015, but later starting dates can potentially be accepted. Marie Sk?odowska-Curie 36-months PhD fellowships offer an attractive remuneration package including salary, mobility, and family allowances, and are subject to eligibility and mobility conditions. For further information, an overview of the projects, and a detailed description of open positions visit www.cosmos-itn.org Positions will be filled starting May 1st, 2015. Applications prior to April 15 will be given full consideration. -------------- next part -------------- An HTML attachment was scrubbed... URL: From ale at sissa.it Thu Mar 26 06:38:00 2015 From: ale at sissa.it (Alessandro Treves) Date: Thu, 26 Mar 2015 11:38:00 +0100 Subject: Connectionists: One week left to apply for an independent postdoc at SISSA Message-ID: <20150326113800.Horde.iG2mch8V4mxVE_GIHI41H1A@webmail.sissa.it> The Neuroscience Area of SISSA has opened a new postdoctoral position. The fellowship awardee may join any of the available research groups, see http://www.sissa.it/announcement/neuroscience-area-new-postdoc-position or may choose to work independently. Candidates with a potential to bring extra diversity are particularly encouraged to apply. Deadline April 3rd! -- Alessandro Treves http://people.sissa.it/~ale/limbo.html SISSA - Cognitive Neuroscience, via Bonomea 265, 34136 Trieste, Italy and Master in Complex Actions http://www.mca.sissa.it/ From jutta.kretzberg at uni-oldenburg.de Thu Mar 26 04:14:38 2015 From: jutta.kretzberg at uni-oldenburg.de (Jutta Kretzberg) Date: Thu, 26 Mar 2015 09:14:38 +0100 Subject: Connectionists: PhD position - Coding of retinal ganglion cells - Multi-electrode array - Oldenburg, Germany Message-ID: <5513BFEE.9000103@uni-oldenburg.de> The Visual Neuroscience group at the University of Oldenburg, Germany is offering a PhD position (TV-L E13 50%) in population coding of retinal ganglion cells starting in May 2015. The position is initially funded until March 31 2018. The goal of our research is to understand how visual signals are transmitted from the retina to the brain. We study how populations of neurons encode information using large-scale multi-electrode arrays, which are able to record the responses of around a thousand neurons of various cell-types simultaneously for several hours. The visual stimulus is transduced into electrical signals by the photoreceptors of the retina, processed by many types of interneurons, and conveyed to the brain by the ganglion cells along their axons that form the optic nerve. All visual information is encoded in temporal patterns of electrical impulses of the ganglion cells. We know from morphological studies that over 20 types of ganglion cells exist. Each type carries a specialized and distinct representation of the visual environment to different targets in the brain. We do not know the response properties of many types, especially in natural viewing conditions, nor do we fully understand how the diverse information sent by the different cell types collectively determines visual perception and behavior. For more information please visit www.uni-oldenburg.de/retina. We seek a highly motivated PhD student with an academic university degree (Master or Diploma) in Biology, Physics, Informatics or related fields. Applicants should have strong computing skills, experience or training in neuroscience and interest in vision research. Electrophysiological experience is an advantage. The Carl von Ossietzky University of Oldenburg is dedicated to increasing the percentage of women in science. Therefore, equally qualified female candidates will be given preference. Applicants with disabilities will be preferentially considered in case of equal qualification. Please submit your application (in English or German) including a motivation letter with a description of your scientific interest, a CV, degree certificates, and contact information of two references to Prof. Dr. Martin Greschner (martin.greschner at uni-oldenburg.de) preferably by email, as a single pdf-file or by mail to the Universit?t Oldenburg, Fakult?t VI, Visual Neuroscience, 26111 Oldenburg. Applications will be considered until April 20th. From norbert.kopco at upjs.sk Thu Mar 26 06:48:37 2015 From: norbert.kopco at upjs.sk (Norbert Kopco) Date: Thu, 26 Mar 2015 06:48:37 -0400 Subject: Connectionists: Kosice Neuroscience Workshop April 20-24 Message-ID: <5513E405.8030105@upjs.sk> The Second Workshop and Lecture Series on */"Cognitive neuroscience of auditory and cross-modal perception"/* 20 - 24 April 2015 Kosice, Slovakia http://pcl.upjs.sk/ *Objectives:* This workshop and lecture series will include introductory lectures and advanced research talks on a range of topics related to the */neural processes of auditory, visual and cross-modal perception/*. The talks will illustrate the */multidisciplinary character of cognitive neuroscience research/*, covering behavioral, neuroimaging, and modeling approaches, as well as applications of the research in auditory prosthetic devices. The workshop is aimed at */early-stage and advanced students and young researchers/*, and it will provide ample opportunities for direct interactions between the lecturers and the attendees. Themes Spatial hearing, vision and crossmodal perception, neural modeling, methods in cognitive neuroscience: behavioral experiments, EEG and fMRI imaging, modeling, applications: cochlear implants, hearing aids. *Format* Lectures 20 - 22 April, Consultations 23 ? 24 April *Venue* Historicka aula, P. J. Safarik University, Srobarova 2, 040 11 Kosice, Slovakia *Organizers* Norbert Kopco, PhD. (norbert.kopco at upjs.sk ) Frederick Gallun, PhD. (Frederick.Gallun at va.gov ) *Organizing team and contact* Beata Tomoriova, Lubos Hladek, Perception and Cognition Lab ,**kogneuro at gmail.com Program overview Lectures, talks, posters: Mon, Tue, Wed: 8:30 ? 12:00, 13:30 ? 16:05 expert lectures, 16:05 ? 17:00: contributed posters & presentations Plenary lecture and panel discussion: Wed: 17:30-19:00 in Zlaty Dukat hotel Consultations: * Thu: 8:30 ? 11:30 Individual consultations with experts (by appointment) and work on assignments, 12:00 ? 17:00 individual work on assignments (8:30 ? 11:30 alternatively, interested participants can attend the Symposium on university spin-offs and start-up companies ) * Fri: 8:30 ? 11:30 Individual consultations with experts (by appointment) and work on assignments Plenary lecture and panel discussion *Virginia Best, Frederick Gallun, and Norbert Kopco*?Audibility and spatial hearing? Speakers and lecture topics *Simon Carlile*(University of Sydney) Lecture 1: Active listening: Speech intelligibility in cocktail party listening. Lecture 2: Listening in motion *Pierre Divenyi*(Stanford University) Lecture 1: Toward an evolutionary theory of speech: how and why did it develop the way it did. Lecture 2: What is the cost of simultaneously listening to the ?what? and the ?when? in speech? ** *Christopher Stecker *(Vanderbilt University) Lecture 1: RESTART theory: discrete sampling of binaural information during envelope fluctuations is a fundamental constraint on binaural processing. Lecture 2: Neuroimaging of task-dependent spatial processing in human auditory cortex. Assignment 1: Psychophysical exploration of binaural cues synchronized to envelope fluctuations: testing the RESTART theory with synthetic and naturalistic sounds. (hackathon type assignment) Assignment 2: Analysis of an fMRI data set combining task and binaural manipulations in a factorial manner. ** *Bernhard Laback*(Austrian Academy of Sciences) Lecture 1: Sound Localization Cues and Perceptual Grouping in Electric Hearing Lecture 2: Temporal effects in the perception of interaural time differences: Data and model predictions Assignment: Acoustic simulation of cochlear implant perception with low-frequency residual hearing ** *Volker Hohmann *(University of Oldenburg) Lecture 1: Modeling Auditory Scene Analysis by multidimensional statistical filtering Lecture 2: Modeling Cocktail Party Processing in a Multitalker Mixture using Harmonicity and Binaural Features Assignment: Implementation of a statistical estimator (particle filter) that tracks a (simulated) pitch track partially masked by noise. ** *Arash Yazdanbakhsh*(Boston University) Lecture 1: Pursuit eye movements and perceived object velocity, potential clinical applications. Lecture 2: Visuospatial memory and where eyes look when the percept changes. Assignment: A simulation assignment to replicate the gain of eye pursuit in following a target. ** *Aaron Seitz*(University of California, Riverside) Lecture 1: Perceptual Learning; specificity, transfer and how learning is a distributed process Lecture 2: Brain Training; How to train cognition to yield transfer to real world contexts ** *Frederick (Erick) Gallun *(US Dept. of Veterans Affairs and Oregon Health & Science University) Lecture 1: Learning From Nature?s Experiments: What Clinical Research Can Mean for Sensory Scientists Lecture 2: Auditory Processing After mild Traumatic Brain Injury: New Findings and Next Steps Assignment: Establishing normative ranges of performance using non-linear functions ** *Istvan Winkler*(Hungarian Academy of Science) Lecture 1: Auditory processing capabilities supporting communication in preverbal infants Lecture 2: Modeling auditory stream segregation by predictive processes ** *Virginia Best*(Boston University) Lecture 1: Spatial Hearing: Effect of hearing loss and hearing aids. Assignment: MATLAB assignment: simulating the effect of hearing loss on spatial cues ** *Petr Mar??lek*(Charles University in Prague) Lecture 1: Coincidence detection in the MSO ? computational approaches Lecture 2: On the single neuron computation Travel, accommodation, visitor information /Travel: /The Kosice Airport is served by Austrian Airlines and Czech Airlines (via Vienna, Prague, Bratislava) and by low-cost airline Wizzair (London Luton Airport). Alternatively you can fly to Budapest and take a 3.5-hr shuttle bus to Kosice (for example, using the cassoviaexpres shuttle bus company). From Krakow you can take the 4-hr shuttle bus operated by Airtrans.sk . More information about how to get to Kosice (also by train or bus) can be found here .// /Accommodation:/A conference rate of 50EUR/night+(1.5e local tax) has been negotiated with the Zlaty dukat hotel. Please, make your reservation by contacting the hotel directly, either through their website or by emailing the hotel at hotel at hotelzlatydukat.sk and mention the ?Cognitive Neuroscience Workshop? to get the rate. Otherwise, there are several hotels close to the workshop venue, for example Hotel Teledom , Villa Regia , Doubletree by Hilton , Hotel Yasmin , Hotel Maraton (for more hotel options please see http://www.booking.com, http://www.hotels.com, for hostels see: http://www.hostels.com, http://www.hostelworld.com) // /Visitor information and current events:/Ko?ice was one of the European Capitals of Culture in 2013 . For the list of new cultural venues and current events there, see http://k13.sk/(in Slovak). For all events and trip ideas see http://www.visitkosice.eu/, http://www.slovaktours.eu/, http://www.mickosice.sk/ , http://slovakia.travel/, or http://www.slovakia.com/ // Registration The workshop is open to all interested students/scientists. Registration is free of charge but required (mostly for organizational reasons). In order to register, please send an email to kogneuro at gmail.com stating your name and affiliation, dates on which you are planning to attend. In case you would like to have a presentation please send us an abstract (up to 200 words) and an indication whether you prefer poster or oral presentation no later than April 10, 2015. Related event Workshop attendees might also be interested in an independent Symposium on university spin-offs and start-up companies that will take place on 23 April 2015. Last year?s website http://pcl.upjs.sk/workshop2014/ Funding This workshop / lecture series is organized within the Project implementation: SOFOS ? knowledge and skill development of the academic staff and students at the University of Pavol Jozef Safarik in Kosice with emphasis on interdisciplinary competencies and integration into international research centres, ITMS: 26110230088, supported by the Research & Development Operational Programme funded by the ESF. Modern education for knowledge society / This project is being co-financed by the European Union -- doc. Norbert Kopco, Ph.D. Assoc Professor / Senior Researcher: Inst of Computer Sci, Faculty of Science, Safarik Univ, Kosice, Slovakia Adjunct: Ctr for Computational Neurosci (CompNet), Boston University & Martinos Ctr for Biomed Imaging, Harvard Med School - Mass Gen Hospital P: +16175759556 F: +14847279884, kopco at bu.edu, http://cns.bu.edu/~kopco -------------- next part -------------- An HTML attachment was scrubbed... URL: From marcel.van.gerven at gmail.com Fri Mar 27 03:53:59 2015 From: marcel.van.gerven at gmail.com (Marcel van Gerven) Date: Fri, 27 Mar 2015 08:53:59 +0100 Subject: Connectionists: Radboud Summer School Neural Metrics 2.0 : Connectomics & Large-Scale Methods Message-ID: Neural Metrics 2.0 : Connectomics & Large-Scale Methods Second call The Donders Institute for Brain, Cognition and Behaviour/Radboud University is organizing a summer school on neural metrics with the aim to get participants acquainted with the quantitative analysis of neural organisation and function. In Neural Metrics 2.0 we will build on the success from the previous year, focussing on methods for understanding brain networks such as connectomics as well as large scale and Bayesian methods, with world class speakers, hands-on tutorials, student projects and an interactive debate. The topics covered range from cellular connectomics to human functional connectomics. The course is designed for PhD students and starting postdoctoral researchers working at the interface between cognitive neuroscience and the application of advanced methods. Please consult the Radboud Summer school website (http://www.ru.nl/radboudsummerschool/ ) for details on the program, social events and registration. Further details for the Neural Metrics Summer School can be found below and on the website (http://www.ru.nl/radboudsummerschool/courses/brain-behaviour/@972443/neural-metrics-2-0-0/ ). Dates : Monday 10 August - Friday 14 August 2015 (1 week) Application Deadline : 15 June 2015 Course leaders : Bernhard Englitz, Marcel van Gerven, Fleur Zeldenrust, Tansu Celikel Donders Institute for Brain, Cognition and Behaviour & Radboud University Participant profile : This course was developed for PhD students and early postdoctoral researchers working at the interface between cellular and cognitive neuroscience requiring advanced methods of analysis. This includes research in the field of Neuroscience with an MSc in Biology, Computer Science, Psychology, Physics, Al, Mathematics, Engineering or a similar major. Admission requirements : As part of the admission procedure, we ask you to send us your CV and a brief motivation letter in which you explain your interest in our course. Course fee : 600 Euros The course fee includes the registration fee, course materials, access to library and IT facilities, coffee/tea, lunch, and a number of social activities. Accommodation is available for the course participants (additional charges apply). For details please see http://www.ru.nl/radboudsummerschool/practical-matters/housing/ Discounts : ? 15% discount for students and PhD candidates from Radboud University and partner universities, ? 10% Early bird discount deadline: 1 April 2015 -------------- next part -------------- An HTML attachment was scrubbed... URL: From neumann at cbs.mpg.de Fri Mar 27 04:23:18 2015 From: neumann at cbs.mpg.de (Jane Neumann) Date: Fri, 27 Mar 2015 09:23:18 +0100 Subject: Connectionists: 2nd Model-based Neuroscience Summer School Amsterdam June 1-5 In-Reply-To: <55142F46.6000209@cbs.mpg.de> References: <55142F46.6000209@cbs.mpg.de> Message-ID: <55151376.5010909@cbs.mpg.de> Dear colleagues, *June 1-5 2015* will see the second *Model-based Neuroscience Summer School*, hosted at the *University of Amsterdam*. The school will provide students with hands-on experience in both cognitive modeling using diffusion and accumulator models and simple neuroscience methods. In addition, the program includes a debate between the two most prominent perspectives on the model-based neuroscience of perceptual decision-making. These perspectives place a different primary focus on either behavior (Ratcliff) or neural dynamics (Logan). Consequently, they bring different insights to the combined research agenda. The summer school is aimed at PhD students and early PostDocs who wish to combine cognitive modelling with experimental and theoretical neuroscience research. Students should be familiar with general programming concepts and state in their application which programming languages and software packages they typically use. The summer school is only 100 euro, however, we ask that students make their own housing arrangements. Space is limited, therefore we ask that you provide a statement of interest. We will base selection of students based on the relevance of the summer school to their research. More information about the teachers, preliminary programme, and application can be found at www.modelbasedneuroscience.com We are looking forward to welcoming you in Amsterdam! Organization: Birte Forstmann, University of Amsterdam Jane Neumann, University Medical Center Leipzig and MPI for Human Cognitive and Brain Sciences Roger Ratcliff, Ohio State University Leendert van Maanen, University of Amsterdam -------------- next part -------------- An HTML attachment was scrubbed... URL: From simone.seeger at zi-mannheim.de Fri Mar 27 04:18:58 2015 From: simone.seeger at zi-mannheim.de (Seeger, Simone) Date: Fri, 27 Mar 2015 08:18:58 +0000 Subject: Connectionists: Call for Abstracts: Bernstein Conference 2015 Message-ID: <68B5BBF569FEF84891D3AAB4D3141E4568DDCE34@ZIMAIL2.Zi.local> Call for Abstracts: Bernstein Conference 2015 Deadline of Abstract Submission: May 15, 2015 ************************************************************** Satellite Workshops September 14, 2015 Main Conference September 15-17, 2015 ************************************************************** The Bernstein Conference has become the largest annual Computational Neuroscience Conference in Europe and now regularly attracts more than 500 international participants. This year, the Conference is organized by the Bernstein Center for Computational Neuroscience Heidelberg-Mannheim and will take place on September 15-17, 2015, in Heidelberg. In addition, there will be a series of pre-conference satellite workshops on September 14, 2015. The Bernstein Conference is a single-track conference, covering all aspects of Computational Neuroscience and Neurotechnology, and sessions for poster presentations are an integral part of the conference. We now invite the submission of abstracts for poster presentations from all relevant areas. Accepted abstracts will be published online and will be citable via Digital Object Identifiers (DOI). Additionally, a small number of abstracts will be selected for contributed talks. DETAILS FOR ABSTRACT SUBMISSION: For abstract submission visit: http://www.nncn.de/de/bernstein-conference/2015/abstracts Please note that the submission of an abstract does not replace the conference registration! Conference registration starts on April 27. Abstract submission deadline: May 15, 2015 CONFERENCE DETAILS: Venue: Satellite Workshops and Main Conference, "Neue Universit?t", Grabengasse 3-5 ("Universit?tsplatz"), 69117 Heidelberg, Germany Registration: Conference Registration starts on April 27, 2015 Early registration deadline: July 21, 2015 For more information on the conference, please visit the website: http://www.bernstein-conference.de PUBLIC PHD STUDENT EVENT: September 17-18, 2015 PUBLIC LECTURE: September 15, 2015 FOR THE ORGANIZING COMMITTEE: Peter Bastian We look forward to seeing you in Heidelberg in September! *** Simone Seeger, M.A. Administration Bernstein Center for Computational Neuroscience Zentralinstitut f?r Seelische Gesundheit Postfach 12 21 20, 68072 Mannheim J5, 68159 Mannheim Telefon: 0621/1703-1326 oder 06221/54-8310 Fax: 0621/1703-2915 E-Mail: Simone.Seeger at zi-mannheim.de Internet: http://www.bccn-heidelberg-mannheim.de -------------- next part -------------- An HTML attachment was scrubbed... URL: From mlsp at neuro.kuleuven.be Fri Mar 27 08:28:40 2015 From: mlsp at neuro.kuleuven.be (2015 IEEE International Workshop on Machine Learning fo Signal Processing) Date: Fri, 27 Mar 2015 13:28:40 +0100 Subject: Connectionists: call for papers - 2015 IEEE International Workshop on Machine Learning, for Signal Processing (MLSP) Message-ID: <55154CF8.8020609@neuro.kuleuven.be> call for papers - 2015 IEEE International Workshop on Machine Learning for Signal Processing (MLSP) September 17-20, 2015 Boston, Massachusetts, USA http://mlsp2015.conwiz.dk CALL FOR PAPERS The 25th MLSP workshop in the series of workshops organized by the IEEE Signal Processing Society MLSP Technical Committee will present the most recent and exciting advances in machine learning for signal processing through keynote talks, tutorials, as well as special and regular single-track sessions. Prospective authors are invited to submit papers on relevant algorithms and applications including, but not limited to: - Learning theory and techniques - Graphical models and kernel methods - Data-driven adaptive systems and models - Pattern recognition and classification - Distributed, Bayesian, subspace/manifold/sparsity-aware learning - Multiset data analysis and multimodal data fusion - Perceptual signal processing in audio, image and video - Cognitive information processing - Multichannel adaptive and nonlinear signal processing - Applications, including: speech & audio, image & video, music, biomedical signals & images, communications, bioinformatics, biometrics, computational intelligence, genomic signals & sequences, social networks, games, smart grid, security & privacy DATA ANALYSIS AND SIGNAL PROCESSING COMPETITION The competition is organized in conjunction with the workshop. The goal of the competition is to advance the current state-of-the-art in theoretical and practical aspects of signal processing domains. SPECIAL SESSIONS MLSP 2015 seeks proposals for Special Sessions that will address research in emerging or interdisciplinary areas of particular interest, not covered already by traditional MLSP sessions. Please submit proposals to the Special Session Chair. BEST STUDENT AWARD The MLSP Best Student Paper Award will be granted to the best paper for which a student is the principal author and presenter. PAPER SUBMISSION Prospective authors are invited to submit a double column paper of up to six pages using the electronic submission procedure at http://mlsp2015.conwiz.dk. Accepted papers will be published on a password-protected website that will be available during the workshop. The presented papers will be published in and indexed by IEEE Xplore. IMPORTANT DATES AND DEADLINES: Special session proposals: April 12, 2015 Paper submissions: May 17, 2015 Decision notifications: June 21, 2015 Camera-ready papers due: June 28, 2015 Advance registration: August 2, 2015 ORGANIZING COMMITTEE: General Chair: Deniz Erdo?mu?, Northeastern University Program Chairs: Murat Ak?akaya, University of Pittsburgh Serdar Kozat, Bilkent University Competition Chair: Vince Calhoun, University of New Mexico Special Session Chair: Catherine Huang, Intel Labs Publicity Chairs: Kostas Diamantaras, TEI of Thessaloniki Marc Van Hulle, KU Leuven Publication Chair: Jan Larsen, Technical University of Denmark From morrison at fz-juelich.de Fri Mar 27 06:17:25 2015 From: morrison at fz-juelich.de (Abigail Morrison) Date: Fri, 27 Mar 2015 11:17:25 +0100 Subject: Connectionists: Graduate Researcher / Postdoc position available at the SimLab Neuroscience, Juelich Research Centre Message-ID: <55152E35.60607@fz-juelich.de> Dear colleagues, we have a position available in the SImLab Neuroscience, Juelich Research Centre, Germany, at the graduate or postdoc level. We are looking for candidates with a proven track record in developing scientific software, especially with an HPC focus, and an interest in Neuroscience. For a full description and details of how to apply, please see the announcement on our website: http://www.fz-juelich.de/SharedDocs/Stellenangebote/_common/dna/2015-062-EN-JSC.html All the best, Abigail Morrison -- Prof. Dr. Abigail Morrison IAS-6 & INM-6 / SimLab Neuroscience J?lich Research Center http://www.fz-juelich.de/inm/inm-6/ http://www.fz-juelich.de/ias/jsc/EN/Expertise/SimLab/slns/_node.html Office: +49 2461 61-9805 Fax # : +49 2461 61-9460 ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Juelich GmbH 52425 Juelich Sitz der Gesellschaft: Juelich Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Dr. Karl Eugen Huthmacher Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Prof. Dr.-Ing. Harald Bolt, Prof. Dr. Sebastian M. Schmidt ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ From sethu.vijayakumar at ed.ac.uk Sun Mar 29 13:48:47 2015 From: sethu.vijayakumar at ed.ac.uk (Sethu Vijayakumar) Date: Sun, 29 Mar 2015 18:48:47 +0100 Subject: Connectionists: [meetings] Robotics Science and Systems (RSS) 2015, Rome, Italy In-Reply-To: <548037BD.3040309@ed.ac.uk> References: <542D5F0F.1070307@ed.ac.uk> <54660CB2.6050701@ed.ac.uk> <548037BD.3040309@ed.ac.uk> Message-ID: <55183AFF.3070300@ed.ac.uk> *************************************** Robotics Science and Systems (RSS) 2015 *************************************** The 11th Robotics Science and Systems (R:SS 2015) conference will be held in Rome during Jul 13-17, 2015. Accepted workshops and list of invited speakers (tentative) have been announced: http://www.roboticsconference.org/workshops.html http://www.roboticsconference.org/invited.html RSS2015 conference: Jul 13-15, 2015 workshops: Jul 16-17, 2015 venue: Sapienza University of Rome, Rome, Italy Some additional key dates: * mid April, registration web site opens * 04/30 accepted papers announced * 05/15, early registration closes We look forward to another record attendance! Lydia E. Kavraki, RSS 2015 General Chair David Hsu, RSS 2015 Program Chair Sethu Vijayakumar, RSS 2015 Publicity Chair -- ------------------------------------------------------------------ Professor Sethu Vijayakumar FRSE Personal Chair in Robotics Director, Edinburgh Centre for Robotics [edinburgh-robotics.org] Director, IPAB, School of Informatics, The University of Edinburgh 1.28 Informatics Forum, 10 Crichton Street, Edinburgh EH8 9AB, UK URL: http://homepages.inf.ed.ac.uk/svijayak Ph: +44(0)131 651 3444 SLMC Research Group URL: http://www.ipab.informatics.ed.ac.uk/slmc ------------------------------------------------------------------ Adjunct Faculty, Department of Computer Science University of Southern California, Los Angeles, CA, USA 90089-0781 ------------------------------------------------------------------ Microsoft Research & Royal Academy of Engg. Senior Research Fellow ------------------------------------------------------------------ The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336. From feisha at usc.edu Sun Mar 29 17:11:18 2015 From: feisha at usc.edu (Fei Sha) Date: Sun, 29 Mar 2015 14:11:18 -0700 Subject: Connectionists: CFP: ICML 2015 Workshop on Large-scale Kernel Learning Message-ID: Apologies for cross-postings. ************************* CALL FOR PAPERS * ************************* The ICML 2015 workshop "Large-scale Kernel Learning: challenges and new opportunities" invites paper submissions that will be presented as spotlights or posters. Topics of interest include (but are not limited to): - Foundational algorithmic techniques for large-scale kernel learning: matrix factorization, randomization and approximation, variational inference and sampling, inducing variables, random Fourier features, unifying frameworks - Interface between kernel methods and deep learning architectures - Tradeoffs between statistical and computational efficiency in kernel methods - Kernel methods and Gaussian processes for Big Data - Kernel methods and Gaussian processes on GPUs and other hardware and software systems - Stochastic gradient techniques with kernel methods - Large-scale multiple kernel learning - Large-scale representation learning with kernels - Large-scale kernel methods for complex data types beyond perceptual data Both theoretical contributions and empirical studies will be considered. Submissions should be written as extended abstracts, no longer than 5 pages (excluding references) in the camera-ready format using the ICML style. Relevant work previously presented in other conferences will be allowed, though authors should note this in their submission. All submissions must be in PDF format and should be sent by email to lskl.workshop.icml2015 at gmail.com. Authors should note that the workshop presentation (slides, posters, etc) will not be considered as a part of formal proceedings. Please check the workshop website ( https://sites.google.com/site/largescalekernelwsicml15/ ) for updated info. We have confirmed a list of stellar speakers: Francis Bach (ENS), Zaid Harchaoui (INRIA), Marius Kloft (Humbold U of Berlin), Neil Lawrence (Sheffeld), Ruslan Salakhutdinov (Toronto) and more are to be confirmed. Deadline for Submissions: Friday, May 1st, 2015, 23:00 UTC. Notifications of Acceptance : May 10th, 2015. ----------------------------------------------------------------------- Best Fei Sha on behalf of other organizers Dino Sejdinovic (Oxford), Le Song (Gatech), Andrew Wilson (CMU) and Zhiyun Lu (USC) -------------- next part -------------- An HTML attachment was scrubbed... URL: From ralph.etiennecummings at gmail.com Sun Mar 29 22:11:22 2015 From: ralph.etiennecummings at gmail.com (Ralph Etienne-Cummings) Date: Sun, 29 Mar 2015 22:11:22 -0400 Subject: Connectionists: DEADLINE APPROACHING: 2015 Telluride Neuromorpic Cognition Workshop Message-ID: Telluride Neuromorphic Cognition Engineering Workshop 2015 Neuromorphic Cognition Engineering WorkshopTelluride, Colorado, June 28th - July 18th, 2015CALL FOR APPLICATIONS: Deadline is April 2nd, 2015 NEUROMORPHIC COGNITION ENGINEERING WORKSHOP www.ine-web.org Sunday June 28th - Saturday July 18th, 2015, Telluride, Colorado Previous year workshop can be found at: http://ine-web.org/workshops/workshops-overview/index.html and the workshop wiki is athttps://neuromorphs.net/ GOALS: Neuromorphic engineers design and fabricate artificial neural systems whose organizing principles are based on those of biological nervous systems. Over the past 18 years, this research community has focused on the understanding of low-level sensory processing and systems infrastructure; efforts are now expanding to apply this knowledge and infrastructure to addressing higher-level problems in perception, cognition, and learning. In this 3-week intensive workshop and through the Institute for Neuromorphic Engineering (INE), the mission is to promote interaction between senior and junior researchers; to educate new members of the community; to introduce new enabling fields and applications to the community; to promote on-going collaborative activities emerging from the Workshop, and to promote a self-sustaining research field. FORMAT: The three week summer workshop will include background lectures on systems and cognitive neuroscience (in particular sensory processing, learning and memory, motor systems and attention), practical tutorials on emerging hardware design, mobile robots, hands-on projects, and special interest groups. Participants are required to take part and possibly complete at least one of the projects proposed. They are furthermore encouraged to become involved in as many of the other activities proposed as interest and time allow. There will be two lectures in the morning that cover issues that are important to the community in general. Because of the diverse range of backgrounds among the participants, some of these lectures will be tutorials, rather than detailed reports of current research. These lectures will be given by invited speakers. Projects and interest groups meet in the late afternoons, and after dinner. In the early afternoon there will be tutorials on a wide spectrum of topics, including analog VLSI, mobile robotics, vision and auditory systems, central-pattern-generators, selective attention mechanisms, cognitive systems, etc. 2015 TOPIC AREAS: 1. *Human Auditory Cognition: Communicating with EEG and Virtual Reality Links (The Matrix):* Shihab Shamma (UM-College Park), Malcolm Slaney (Google), and Alain de Cheveigne (UPMC, France) 2. *Manipulation Actions: Movements, Forces and Affordances:* Cornelia Ferm?ller (UMCP), Michael Pfeiffer (INI-UZH), Ryad Benosman (UPMC, Paris), and Andreas Andreou (JHU) 3. *Neuromorphic Natural Language Processing:* John Harris (UFL, Gainesville) and Chris Huyck (Middlesex University) 4. *Spike-Based Cognitive Computing:* Seeing, Hearing, and Thinking with Spikes: Arindam Basu (NTU, Singapore) and John Arthur (IBM Research Almaden) 5. *Computational Neuroscience (invitational mini-workshop):* Terry Sejnowski (Salk Institute) LOCATION AND ARRANGEMENTS: The summer school will take place in the small town of Telluride, 9000 feet high in southwest Colorado, about 6 hours drive away from Denver (350 miles). Great Lakes Aviation and America West Express airlines provide daily flights directly into Telluride. All facilities within the beautifully renovated public school building are fully accessible to participants with disabilities. Participants will be housed in ski condominiums, within walking distance of the school. Participants are expected to share condominiums. The workshop is intended to be very informal and hands-on. Participants are not required to have had previous experience in analog VLSI circuit design, computational or machine vision, systems level neurophysiology or modeling the brain at the systems level. However, we strongly encourage active researchers with relevant backgrounds from academia, industry and national laboratories to apply, in particular if they are prepared to work on specific projects, talk about their own work or bring demonstrations to Telluride (e.g. robots, chips, software). Wireless internet access will be provided. Technical staff present throughout the workshops will assist with software and hardware issues. We will have a network of PCs running LINUX and Microsoft Windows for the workshop projects. We encourage participants to bring along their personal laptop. No cars are required. Given the small size of the town, we recommend that you do not rent a car. Bring hiking boots, warm clothes, rain gear, and a backpack, since Telluride is surrounded by beautiful mountains. Unless otherwise arranged with one of the organizers, we expect participants to stay for the entire duration of this three week workshop. FINANCIAL ARRANGEMENTS: Notification of acceptances will be mailed out around the April 15th, 2015. The Workshop covers all your accommodations and facilities costs for the 3 weeks duration. You are responsible for your own travel to the Workshop, however, sponsored fellowships will be available as described below to further subsidize your cost. *Registration Fees:* For expenses not covered by federal funds, a Workshop registration fee is required. The fee is $1250 per participant for the 3-week Workshop. This is expected from all participants at the time of acceptance. *Accommodations:* The cost of a shared condominium, typically a bedroom in a shared condo for senior participants or a shared room for students, will be covered for all academic participants. Upgrades to a private rooms or condos will cost extra. Participants from National Laboratories and Industry are expected to pay for these condominiums. FELLOWSHIPS: This year we will offer one Fellowship program to subsidize your costs: The EU-CSNII Fellowship (http://csnetwork.eu/) which is funded by the 7th Research Framework Program FP7-ICT-CSNII-601167. The top 8 EU applicants will be reimbursed for their registration fees ($1250), subsistence/travel subsidy (up to Euro 2000) and accommodations cost ($1500). The registration and accommodation costs will go directly to the INE (the INE will reimburse them) while the subsistence/travel reimbursement will be provided directly to the participants by the CSNII at the University of Pompeu Fabra, Barcelona, Spain. We invite applications for a three-week summer workshop that will be held in Telluride, Colorado. Sunday June 28th - Saturday July 18th, 2015. The application deadline is Wednesday, April 2nd and application instructions are described at the bottom of this document. The 2015 Workshop and Summer School on Neuromorphic Engineering is sponsored by the National Science Foundation, Institute of Neuromorphic Engineering, DARPA, Office of Naval Research, The EU-Collaborative Convergent Science Network (CNS-II), University of Maryland - College Park, Institute for Neuroinformatics ? University of Zurich and ETH Zurich, Georgia Institute of Technology, Johns Hopkins University, Boston University, University of Western Sydney and the Salk Institute. DIRECTORS: - Cornelia Fermuller, University of Maryland, College Park - Ralph Etienne-Cummings, Johns Hopkins University - Shih-Chii Liu, Institute of Neuroinformatics, UNI/ETH Zurich, Switzerland - Timothy Horiuchi, University of Maryland, College Park WORKSHOP ADVISORY BOARD: - Andreas Andreou, Johns Hopkins University - Andre van Schaik, University Western Sydney, Australia - Avis Cohen, University of Maryland - Barbara Shinn-Cunningham, Boston University - Giacomo Indiveri, Institute of Neuroinformatics, UNI/ETH Zurich, Switzerland - Jonathan Tapson, University Western Sydney, Australia - Malcolm Slaney, Google - Jennifer Hasler, Georgia Institute of Technology - Rodney Douglas, Institute of Neuroinformatics, Uni/Eth Zurich, Switzerland - Shihab Shamma, University of Maryland - Tobi Delbruck, Institute of Neuroinformatics, Uni/Eth Zurich, Switzerland HOW TO APPLY: Applicants should be at the level of graduate students or above (i.e. postdoctoral fellows, faculty, research and engineering staff and the equivalent positions in industry and national laboratories). We actively encourage women and minority candidates to apply. Anyone interested in proposing or discussing specific projects should contact the appropriate topic leaders directly. The application website is (after February 23rd, 2015): ine-web.org/telluride-conference-2015/apply-info *Application information needed:* - Contact email address. - First name, Last name, Affiliation, valid e-mail address. - Curriculum Vitae (a short version, please). - One page summary of background and interests relevant to the workshop, including possible ideas for workshop projects. Please indicate which topic areas you would most likely join. - Two letters of recommendation (uploaded directly by references). *Applicants will be notified by e-mail.* 23rd February, 2015 - Applications accepted on website 2nd April, 2015 - Applications Due 15th April, 2015 - Notification of Acceptance -- Ralph Etienne-Cummings, PhD, FIEEE Professor and Chairman Department of Electrical and Computer Engineering Computational Sensor Motor Systems Lab Laboratory for Computational Sensing and Robotics The Johns Hopkins University Baltimore, MD [image: cid:image001.png at 01CFC064.B58B46A0] -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image001.png Type: image/png Size: 20171 bytes Desc: not available URL: From n.lepora at bristol.ac.uk Mon Mar 30 12:04:06 2015 From: n.lepora at bristol.ac.uk (Nathan Lepora) Date: Mon, 30 Mar 2015 17:04:06 +0100 Subject: Connectionists: [jobs] PhD studentship in Robot Touch at Bristol (UK only) Message-ID: We are looking for an outstanding science or engineering graduate interested in working on the interface of robotics and neuroscience, specifically on applying biologically inspired theories of active perception to tactile robotics. Candidate requirements: **Only UK applicants will qualify for funding** (see below) but applications from overseas candidates with their own source of funding are welcomed. Suitable applicants will be expected to have a first or upper second-class honours degree in a relevant discipline. The student will be enrolled within the Faculty of Engineering at the University of Bristol and will also be a member and have full access to facilities at the Bristol Robotics Laboratory, the UK's most comprehensive robotics innovation facility and a world-leading centre of robotics research. Funding: Studentship covers full UK/EU (EU applicants who have resided in the UK for 3 years prior to application) PhD tuition fees and a tax-free stipend at the current RCUK rate (?14,057 for 2015/16). EU nationals resident in the EU may also apply but will qualify only for PhD tuition fees. Application procedure: Applicants should send a CV and contact information for 2 referees to Dr Nathan Lepora (n.lepora at bristol.ac.uk). The deadline for Applications is Thursday 9th April, although informal enquiries should be made beforehand. -- Dr N Lepora Phone: +44 (0) 117 331 5169 Website: http://www.bristol.ac.uk/engineering/people/nathan-f-lepora Lecturer and MSc Program Director in Robotics (UoB) Department of Engineering Mathematics University of Bristol BS8 1UB From n.lepora at bristol.ac.uk Mon Mar 30 11:41:36 2015 From: n.lepora at bristol.ac.uk (Nathan Lepora) Date: Mon, 30 Mar 2015 16:41:36 +0100 Subject: Connectionists: [news] New scholarships available for MSc study in Robotics in Bristol Message-ID: 12 Scholarships of ?2500 each are available for UK students to study robotics on the MSc in Robotics at Bristol. The MSc in Robotics at Bristol The MSc in Robotics at Bristol is unique in drawing on the strengths of two universities, the University of Bristol and the University of the West of England. The Universities are partners in the Bristol Robotics Laboratory (BRL), a world leading facility for multi-disciplinary robotics research, and the leading and largest academic centre for robotics research in the UK with over 150 academic staff and 3000 square meters of laboratory space. The MSc in Robotics will provide you with a wide understanding of the practice and theory of advanced robotic systems, with wide-ranging applications from industry to research. The programme is sufficiently general to give you an excellent background for a professional career in the robotics sector whilst also providing the specialism and detail necessary for a career as a researcher. The MSc in Robotics has been designed to: - Deliver a broad Robotics education at postgraduate level including courses spanning from practical aspects of robot control and construction to artificial intelligence and machine learning. A very wide range of options are also available spanning from computational neuroscience to digital systems. - Enable students to develop their skills in a robotics through selected taught courses, case studies and laboratory work. Students receive lectures both at the University of Bristol and the University of the West of England, and undertake a significant component of practical work in robotics at Bristol Robotics Laboratory throughout the year. - Provide all students with a major research project, undertaken under the supervision of senior academic staff and experts in robotics. Research projects span the whole range of robotics including, but not limited to, aerial robotics, medical robotics, biomimetics, neuro-robotics, bioenergy, nonlinear control, haptics, robot vision, human-robot interaction, soft robotics, swarm robotics, manufacturing robotics and robot safety. The MSc in Robotics also benefits from synthesis with Bristol's new Centre for Doctoral Training in robotics and autonomous systems FARSCOPE (http://farscope.bris.ac.uk/). The MSc in Robotics provides an excellent route into a highly important and rapidly growing area of industry and research, at a world-leading centre for robotics. Bristol is also renowned for the standing of its Universities, its historic and beautiful town centre, and is consistently voted the 'best city to live in the UK'. Information on how to apply: See the webpages for details of who to contact and how to apply: http://www.bristol.ac.uk/engineering/interdisciplinary/robotics/ http://www.brl.ac.uk/studyatbrl/roboticscourses/mscinrobotics.aspx Places on this programme are limited so early applications are strongly encouraged. Scholarships will be awarded on a competitive basis. -- Dr N Lepora Phone: +44 (0) 117 331 5169 Website: http://www.bristol.ac.uk/engineering/people/nathan-f-lepora Lecturer and MSc Program Director in Robotics (UoB) Department of Engineering Mathematics University of Bristol BS8 1UB From liuwfxy at gmail.com Mon Mar 30 09:53:07 2015 From: liuwfxy at gmail.com (=?UTF-8?B?5YiY5Lyf6ZSL?=) Date: Mon, 30 Mar 2015 21:53:07 +0800 Subject: Connectionists: Fwd: The second call for paper (one month left): signal processing SI on Big Data Meets Multimedia Analytics Message-ID: Signal Processing Special Issue on Big Data Meets Multimedia Analytics With the rapid development of computing and sensing technologies, such as the emergence of social networking websites and wearable devices, many new research opportunities and challenges for multimedia content analysis have arisen. Many big data modeling methods, computing algorithms, and signal processing technologies have recently been successfully developed and applied to multimedia content analysis: for example, multi-view learning algorithms have been proposed for exploring the variety of multimedia content; sparse and manifold learning have been developed for high dimensional multimedia data representation; deep learning has produced promising results in large scale multimedia retrieval; and compressive sensing and new sampling schemes have been investigated for big data analytics. Motivated by the inclination to collect a set of recent advances and results in these related topics, provide a platform for researchers to exchange their innovative ideas on big modeling and computing solutions for multimedia content analytics, and introduce interesting utilizations of modeling and computing algorithms for particular social/personal media applications, this special issue will target emergent big modeling and computing methods for multimedia signal processing and understanding (with a special focus on social media and personal data). To summarize, this special issue welcomes a broad range of submissions on the development and use of artificial intelligence and computing techniques for multimedia analytics. We are especially interested in: 1) theoretical advances as well as algorithm developments in big data technology for specific social/personal media analytics problems; 2) reports of practical applications and system innovations in social/personal media analytics; and 3) novel datasets as test beds for new developments, preferably with implemented standard benchmarks. The following list suggests (but is not limited to) possible topics of interest: - Big Data Technology Specifically for Multimedia Analytics - Big Data Technology for Multimedia Annotation, Tagging and Classification - Big Data Technology for Multimedia Abstraction and Summarization - Big Data Technology for Multimedia Indexing and Retrieval - Big Data Technology and Computing for Social Media Analytics - Big Data Technology and Computing for Biological Data - Big Data Technology and Computing for Personal Data Mining - Modeling of Wearable Device Sensor Streams - Personal Data based Social Network Analysis and Web Mining - Cloud Computing for Social Intelligence and Personal Data - Deep Learning for Social Media Analytics - Deep Learning for Security in Social Media *Important dates:* Manuscript Submission: May 01, 2015 Initial Decision: August 01, 2015 R1 Version: October 01, 2015 Acceptance Notification: November 01, 2015 Final Manuscripts Due: November 15, 2015 Anticipated Publication: January 01, 2016 *Submission:* Manuscripts (Please follow Signal Processing publishing format, details can be found athttp://www.elsevier.com/ journals/signal-processing/0165-1684/guide-for-authors) should be submitted via the Electronic Editorial System of Elsevier: http://ees.elsevier.com/sigpro/. Please make sure to select the "SI: BDMA" as Article Type during the submission process. -------------- next part -------------- An HTML attachment was scrubbed... URL: From birgit.ahrens at bcf.uni-freiburg.de Mon Mar 30 10:15:06 2015 From: birgit.ahrens at bcf.uni-freiburg.de (Birgit Ahrens) Date: Mon, 30 Mar 2015 16:15:06 +0200 Subject: Connectionists: BCF/NWG Course "Analysis and Models in Neurophysiology" 2015 at the Bernstein Center Freiburg, Germany Message-ID: <55195A6A.9050800@bcf.uni-freiburg.de> *BCF/NWG Course*** *"Analysis and Models in Neurophysiology"*** /Sunday, October 4 - Friday, October 9, 2015 / /Bernstein Center Freiburg, Hansastra?e 9a, 79104 Freiburg, Germany/ *Aim of the course:* The course is intended to provide advanced Diploma/Masters and PhD students, as well as young researchers from the neurosciences with approaches for the analysis of electrophysiological data and the theoretical concepts behind them. *The course includes various topics such as*: * Neuron Models and Point Processes (Prof. Stefan Rotter) * Local field potentials (Prof. Ulrich Egert) * Neural Coding (Dr. Robert Schmidt) * Neural Decoding (Prof. Carsten Mehring) The course will consist of lectures in the morning and matching exercises using Matlab and Mathematica in the afternoon. The participants should have a basic understanding of scientific programming. This course is designated especially for advanced diploma/master students and PhD students (preferentially in their first year). *Application:* Please apply by sending one pdf document containing your CV and a meaningful letter of motivation to nwg-course at bcf.uni-freiburg.de . The letter of motivation should refer to the following points: * Reasons for wanting to take this course * Background in mathematics * Background in scientific programming * Experience in using Matlab and Mathematica * Background in neuroscience The course is limited to 20 participants. *Course fees:*NWG members - 50?, others - 125? *Application deadline: *June 30, 2015 *More information: *http://www.bcf.uni-freiburg.de/events/conferences-workshops/20151004-nwgcourse *-- Dr. Birgit Ahrens --* Teaching & Training Coordinator Bernstein Center Freiburg University of Freiburg Hansastr. 9a D - 79104 Freiburg Germany Phone: +49 (0) 761 203-9575 Fax: +49 (0) 761 203-9559 -------------- next part -------------- An HTML attachment was scrubbed... URL: From chengsoon.ong at anu.edu.au Mon Mar 30 02:52:17 2015 From: chengsoon.ong at anu.edu.au (Cheng Soon. Ong) Date: Mon, 30 Mar 2015 06:52:17 +0000 Subject: Connectionists: CFP: MLOSS 2015 at ICML Message-ID: ********************************************************************** Call for Contributions Workshop on Machine Learning Open Source Software 2015: Open Ecosystems http://mloss.org/workshop/icml15/ at ICML 2015, Lille, France 10th July 2015 ********************************************************************** The ICML workshop on Machine Learning Open Source Software (MLOSS) is aimed at all machine learning researchers who wish to have their algorithms and implementations included as a part of the greater open source machine learning environment. Continuing the tradition of well received workshops on MLOSS at NIPS 2006, NIPS 2008, ICML 2010 and NIPS 2013, we plan to have a workshop that is a mix of invited speakers, contributed talks and discussion/activity sessions. For 2015, we focus on building open ecosystems. Our invited speakers will illustrate the process for Python and Julia through presenting modern high-level high-performance computation engines, and we encourage submissions that showcase the benefits of multiple tools in the same ecosystem. All software presentations are required to include a live demonstration. The workshop will also include an active session (?hackathon?) for planning and starting to develop infrastructure for measuring software impact. IMPORTANT DATES * Submission Date: 28 April 2015 * Notification of Acceptance: 11 May 2015 * Workshop date: 10 July 2015 CALL FOR CONTRIBUTIONS The organizing committee is currently seeking abstracts for talks at MLOSS 2015. MLOSS is a great opportunity for you to tell the community about your use, development, philosophy, or other activities related to open source software in machine learning. The committee will select several submitted abstracts for 20-minute talks. We look forward for submissions that are novel, exciting and that appeal to the wider community. For more details see: http://mloss.org/workshop/icml15/ Please submit your contributions at https://www.easychair.org/conferences/?conf=mloss2015 ORGANIZERS: Ga?l Varoquaux (http://gael-varoquaux.info/) Antti Honkela (http://www.hiit.fi/u/ahonkela/) Cheng Soon Ong (http://www.ong-home.my/) From tbesold at uni-osnabrueck.de Tue Mar 31 04:44:29 2015 From: tbesold at uni-osnabrueck.de (Tarek R. Besold) Date: Tue, 31 Mar 2015 10:44:29 +0200 Subject: Connectionists: 2nd CfP: Tenth International Workshop on Neural-Symbolic Learning and Reasoning (NeSy'15) Message-ID: <47A1646A-0E7A-4A72-8553-54A9D0D0BEFD@uni-osnabrueck.de> +++ Apologies for multiple postings +++ == 10th INTERNATIONAL WORKSHOP ON NEURAL-SYMBOLIC LEARNING AND REASONING (NeSy?15) == July 25, 26, or 27, 2015 In conjunction with IJCAI-15 (Buenos Aires, Argentina) Artificial Intelligence researchers continue to face huge challenges in their quest to develop truly intelligent systems. The recent developments in the field of neural-symbolic integration bring an opportunity to integrate well-founded symbolic artificial intelligence with robust neural computing machinery to help tackle some of these challenges. The Workshop on Neural-Symbolic Learning and Reasoning is intended to create an atmosphere of exchange of ideas, providing a forum for the presentation and discussion of the key topics related to neural-symbolic integration. Topics of interest include: - The representation of symbolic knowledge by connectionist systems; - Neural Learning theory; - Integration of logic and probabilities, e.g., in neural networks, but also more generally; - Structured learning and relational learning in neural networks; - Logical reasoning carried out by neural networks; - Integrated neural-symbolic learning approaches; - Extraction of symbolic knowledge from trained neural networks; - Integrated neural-symbolic reasoning; - Neural-symbolic cognitive models; - Biologically-inspired neural-symbolic integration; - Applications in robotics, simulation, fraud prevention, natural language processing, semantic web, software engineering, fault diagnosis, bioinformatics, visual intelligence, etc. == SUBMISSION == Researchers and practitioners are invited to submit original papers that have not been submitted for review or published elsewhere. Submitted papers must be written in English, use the IJCAI style, and should not exceed 6 pages in the case of research and experience papers, and 4 pages in the case of position papers (including figures, bibliography and appendices). All submitted papers will be judged based on their quality, relevance, originality, significance, and soundness. Papers must be submitted through EasyChair (please see http://www.neural-symbolic.org/NeSy15/ for details). == PRESENTATION == Selected papers will be presented during the workshop. The workshop will include extra time for audience discussion of the presentation allowing the group to have a better understanding of the issues, challenges, and ideas being presented. == PUBLICATION == Accepted papers will be published in official workshop proceedings, which will be distributed during the workshop. Authors of the best papers will be invited to submit a revised and extended version of their papers to the Journal of Logic and Computation. == IMPORTANT DATES == Deadline for submission: April 27, 2015 Notification of acceptance: May 20, 2015 Camera-ready paper due: May 30, 2015 Workshop day: July 25, 26, or 27, 2015 IJCAI-14 main conference dates: July 28-31, 2015 == WORKSHOP ORGANIZERS == Tarek Besold (Universit?t Osnabr?ck, Germany) Thomas Icard (Stanford University, USA) Luis Lamb (Universidade Federal do Rio Grande do Sul, Brazil) Risto Miikkulainen (The University of Texas at Austin, USA) == PROGRAMME COMMITTEE == Artur d?Avila Garcez (City University London, UK) Ross Gayler (Melbourne, Australia) Ramanathan V. Guha (Google Inc., USA) Pascal Hitzler (Wright State University, USA) Steffen H?lldobler (TU Dresden, Germany) Frank J?kel (Universit?t Osnabr?ck, Germany) Kai-Uwe K?hnberger (Universit?t Osnabr?ck, Germany) Alan Perotti (University of Turin, Italy) Christopher Potts (Stanford University, USA) Ron Sun (Rensselaer Polytechnic Institute, USA) Jakub Szymanik (University of Amsterdam, The Netherlands) Gerson Zaverucha (Federal University of Rio de Janeiro, Brazil) == KEYNOTE SPEAKER == Dan Roth (University of Illinois at Urbana-Champaign, USA) == ADDITIONAL INFORMATION == General questions concerning the workshop should be addressed to Luis Lamb at LuisLamb at acm.org For additional information, please see the workshop website at http://www.neural-symbolic.org/NeSy15/ The neural-symbolic integration mailing list will be used for announcements and discussions. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Tarek R. Besold Institute of Cognitive Science University of Osnabr?ck (Germany) tbesold at uni-osnabrueck.de -------------- next part -------------- An HTML attachment was scrubbed... URL: From oleary at usc.edu Mon Mar 30 16:56:44 2015 From: oleary at usc.edu (Daniel Edmund O'Leary) Date: Mon, 30 Mar 2015 20:56:44 +0000 Subject: Connectionists: =?windows-1252?q?Call_for_papers_-_Special_Issue_?= =?windows-1252?q?on_=93Computational_Economics_and_Finance=94?= Message-ID: <1427748961237.76921@usc.edu> ?? Call for Papers Special Issue on ?Computational Economics and Finance? John Wiley?s journal ?Intelligent Systems in Accounting, Finance and Management? will have a special issue focusing on papers in ?Computational Economics and Finance.? All Topics in Computational Economics and Finance are welcomed, including, but not limited to * Agent-based computing * Cognitive agent models * Computational Macroeconomics * Economic simulation models * Econophysics * Evolutionary economics * Experimental and prediction markets * Financial physics * Genetic models in economics and finance * Heterogeneous agent modeling * Neural models of economic processes * Social networks Papers should be submitted by May 15, 2015, for the special issue. General information about submissions is available at http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1099-1174 Papers should be submitted to the journal on-line at http://mc.manuscriptcentral.com/isafm Questions should be directed to the editor, Daniel E. O?Leary at oleary at usc.edu -------------- next part -------------- An HTML attachment was scrubbed... URL: From jbednar at inf.ed.ac.uk Tue Mar 31 21:19:35 2015 From: jbednar at inf.ed.ac.uk (James A. Bednar) Date: Wed, 1 Apr 2015 02:19:35 +0100 Subject: Connectionists: ANN: HoloViews 1.0 and ImaGen 2.0 released Message-ID: <21787.18343.370436.622901@hebb.inf.ed.ac.uk> We are pleased to announce the first public release of HoloViews, a free Python package for scientific and engineering data visualization: http://ioam.github.io/holoviews and version 2.0 of ImaGen, a free Python package for generating two-dimensional patterns useful for vision research and computational modeling: http://ioam.github.io/imagen HoloViews provides composable, sliceable, declarative data structures for building even complex visualizations of any scientific data very easily. With HoloViews, you can see your data as publication-quality figures almost instantly, so that you can focus on the data itself, rather than on laboriously putting together your figures. Even complex multi-subfigure layouts and animations are very easily built using HoloViews. ImaGen provides highly configurable, resolution-independent input patterns, directly visualizable using HoloViews but also available without any plotting package so that they can easily be incorporated directly into your computational modeling or visual stimulus generation code. With ImaGen, any software with a Python interface can immediately support configurable streams of 0D, 1D, or 2D patterns, without any extra coding. HoloViews and ImaGen are very general tools, but they were designed to solve common problems faced by vision scientists and computational modelers. HoloViews makes it very easy to visualize data from vision research, whether it is visual patterns, neural activity patterns, or more abstract measurements or analyses. Essentially, HoloViews provides a set of general, compositional, multidimensional data structures suitable for both discrete and continuous real-world data, and pairs them with separate customizable plotting classes to visualize them without extensive coding. ImaGen 2.0 uses the continuous coordinate systems provided by HoloViews to implement flexible resolution-independent generation of streams of patterns, with parameters controlled by the user and allowing randomness or other arbitrary changes over time. These patterns can be used for visual stimulus generation, testing or training computational models, initializing connectivity in models, or any other application where random or dynamic but precisely controlled streams of patterns are needed. Features: - Freely available under a BSD license - Python 2 and 3 compatible - Minimal external dependencies -- easy to integrate into your workflow - Declarative approach provides powerful compositionality with minimal coding - Include extensive, continuously tested IPython Notebook tutorials - Easily reconfigurable using documented and validated parameters - Animations are supported natively, with no extra work - Supports reproducible research -- simple specification, archived in an IPython Notebook, providing a recipe for regenerating your results - HoloViews is one of three winners of the 2015 UK Open Source Awards To get started, check out ioam.github.io/holoviews and ioam.github.io/imagen! Jean-Luc Stevens Philipp Rudiger Christopher Ball James A. Bednar -- The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336. From ted.carnevale at yale.edu Tue Mar 31 13:40:26 2015 From: ted.carnevale at yale.edu (Ted Carnevale) Date: Tue, 31 Mar 2015 13:40:26 -0400 Subject: Connectionists: 2015 NEURON Summer Course Message-ID: <551ADC0A.3000102@yale.edu> This year's NEURON Summer Course has two components that can be taken individually or together. NEURON Fundamentals, which runs from June 20-23, presents what you need to know to use NEURON to model individual neurons and networks of neurons, and introduces parallel simulation. Parallel Simulation with NEURON, which runs from June 24-26, is for users who already know how to write hoc or Python code for NEURON, and need to create models that will run on parallel hardware. Strategies for debugging, and measuring and improving performance, receive special attention. Because of its advanced nature, each day of "Parallel Simulation" includes a block of time in which participants can work on their own projects with expert help close at hand. Registration is limited, and the registration deadline is Friday, May 29, 2015. Discounts are available for applicants who sign up for both courses and/or register by April 20, 2015. For more information see http://www.neuron.yale.edu/neuron/static/courses/nscsd2015/nscsd2015.html --Ted From tildie.stijns at donders.ru.nl Tue Mar 31 07:55:31 2015 From: tildie.stijns at donders.ru.nl (Stijns, M.H. (Tildie)) Date: Tue, 31 Mar 2015 11:55:31 +0000 Subject: Connectionists: Summer school on Neurocomputational Approaches to Decision Making (10-14 August 2015) Message-ID: <90D0A92901510646B5CD061AE2F9AC036DE2EF@exprd04.hosting.ru.nl> Radboud Summer School 2015 (10-14 August 2015): Neurocomputational approaches to decision making: from perception to social cognition In this course you will learn how to use modern computational approaches to further your understanding of the human mind and its neural implementation. You will learn how to combine state?of?the art research approaches, adopting computational models of human behaviour and testing those models with neurophysiological and neuroimaging methods. This course will promote the integration of these disciplines and approaches, stimulating new ways of conceptualising human behaviour, and new lines of research to understand complex brain functions. Early bird discount The early bird application deadline is 1 April 2015. If you apply before this date you will receive a 10% discount on your course fee. Discount for students from Radboud University and partner universities Students from Radboud University as well as from partner universities will receive an additional 15% discount. Best regards, Tildie Stijns =================================================== Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging (DCCN) Radboud University P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Visiting address: Kapittelweg 29 Office 01.120 6525 EN Nijmegen Tel. 00 31 (0)24 - 3610651 Fax 00 31 (0)24 - 3610652 www.ru.nl/donders -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: RadboudSummerschool_2015.pdf Type: application/pdf Size: 492261 bytes Desc: RadboudSummerschool_2015.pdf URL: