From marco.baroni at unitn.it Sun Oct 2 02:49:12 2016 From: marco.baroni at unitn.it (Marco Baroni) Date: Sun, 2 Oct 2016 08:49:12 +0200 Subject: Connectionists: MAchine INtelligence @ NIPS: Call for abstracts and participation Message-ID: (Apologies for multiple postings) What: MAchine INtelligence workshop at NIPS 2016 (MAIN at NIPS) When and Where: Fri Dec 9th 2016, 9am-12.30pm and 2pm-5.30pm Where: Centre Convencions Internacional, Barcelona (Spain) (co-located with NIPS) Website: https://mainatnips.github.io/ ABSTRACT SUBMISSION DEADLINE APPROACHING: Sunday, October 9th *** Motivation *** Recent years have seen the success of machine learning systems, in particular deep learning architectures, on specific challenges such as image classification and playing Go. Nevertheless, machines still fail on hallmarks of human intelligence such as the flexibility to quickly switch between a number of different tasks, the ability to creatively combine previously acquired skills in order to perform a more complex goal, the capacity to learn a new skill from just a few examples, or the use of communication and interaction to extend one's knowledge in order to accomplish new goals. This workshop aims to stimulate theoretical and practical advances in the development of machines endowed with human-like general-purpose intelligence, focusing in particular on benchmarks to train and evaluate progress in machine intelligence. The workshop will feature invited talks by top researchers from machine learning, AI, cognitive science and NLP, who will discuss with the audience their ideas about what are the most pressing issues we face in developing true AI and the best methods to measure genuine progress. We are moreover calling for position statements from interested researchers to complement the workshop program (see below). The workshop will also introduce the new Environment for Communication-Based AI (CommAI-env) to the research community, encouraging discussion on how to make it the ultimate benchmark for communication-based machine intelligence. The Environment aims at being an interactive playground where systems can only succeed if they possess the hallmarks of intelligence we listed above. A prototype of the environment is available here: https://github.com/facebookresearch/CommAI-env *** Call for abstracts *** We invite submission of 3-page abstracts (or shorter) presenting a position statement on what are the most important challenges to develop general machine intelligence (with special interest in communication-based intelligence), and what are the data and benchmarks we need to properly address such challenges. While all points of view are welcome, we also encourage critiques of the Environment for Communication-Based AI. Abstracts must be submitted in PDF format to main.at.nips2016 at gmail.com by Sunday, October 9th. We will notify acceptance by Sunday, October 23d. Authors of accepted abstracts are expected to present their ideas in an oral presentation at the workshop, and to take part in the panel discussions. *** Invited speakers *** * Emannuel Dupoux (Laboratoire de Sciences Cognitives et Psycholinguistique, Paris): http://www.lscp.net/persons/dupoux/ * Fernando Diaz (Microsoft Research, New York): http://msr.nyc/fdiaz/ * Raquel Fernandez (Institute for Logic, Language & Computation, Amsterdam): https://staff.fnwi.uva.nl/r.fernandezrovira/ * Brenden Lake (NYU Center for Data Science): http://cims.nyu.edu/~brenden/ * J?rgen Schmidhuber (IDSIA, Lugano): http://people.idsia.ch/~juergen/ * Arthur Szlam (Facebook Artificial Intelligence Reserch, New York): https://research.facebook.com/arthur-szlam * Julian Togelius (NYU Game Innovation Lab, New York): http://julian.togelius.com/ *** Organizers *** Tomas Mikolov, Allan Jabri, Armand Joulin, Klemen Simonic (Facebook) Marco Baroni, Angeliki Lazaridou, Germ?n Kruszewski (University of Trento/Facebook) *** Program *** The workshop will feature oral presentations and two panel discussions. The program will be posted on the workshop website. *** Important dates *** * Sunday, October 9th: Abstract submission deadline * Sunday, October 23d: Notification of acceptance * Friday, December 9th: Workshop *** Contact *** main.at.nips2016 at gmail.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From tarek.besold at googlemail.com Sun Oct 2 14:40:16 2016 From: tarek.besold at googlemail.com (Tarek R. Besold) Date: Sun, 2 Oct 2016 20:40:16 +0200 Subject: Connectionists: Final CfP: Cognitive Computation @ NIPS 2016 (December 9/Barcelona) - Deadline October 10 Message-ID: <000001d21cdc$6be8fde0$43baf9a0$@gmail.com> **************************************************** Cognitive Computation: Integrating Neural and Symbolic Approaches (CoCo @ NIPS 2016) **************************************************** Workshop at NIPS 2016, Barcelona, Spain December 09, 2016 == WORKSHOP WEBPAGE == http://www.neural-symbolic.org/CoCo2016/ == KEYNOTE SPEAKERS == Barbara Hammer, Bielefed University Pascal Hitzler, Wright State University Risto Miikkulainen, University of Texas at Austin & Sentient Technologies, Inc. Dan Roth, University of Illinois at Urbana-Champaign Kristina Toutanova, Microsoft Research == PANELISTS == Yoshua Bengio, University of Montreal Marco Gori, University of Siena Alessio Lomuscio, Imperial College London Gary Marcus, New York University & Geometric Intelligence, Inc. == MISSION STATEMENT == While early work on knowledge representation and inference was primarily symbolic, the corresponding approaches subsequently fell out of favor, and were largely supplanted by connectionist methods. In this workshop, we will work to close the gap between the two paradigms, and aim to formulate a new unified approach that is inspired by our current understanding of human cognitive processing. This is important to help improve our understanding of Neural Information Processing and build better Machine Learning systems, including the integration of learning and reasoning in dynamic knowledge-bases, and reuse of knowledge learned in one application domain in analogous domains. The workshop brings together established leaders and promising young scientists in the fields of neural computation, logic and artificial intelligence, knowledge representation, natural language understanding, machine learning, cognitive science and computational neuroscience. Invited lectures by senior researchers will be complemented with presentations based on contributed papers reporting recent work (following an open call for papers) and a poster session, giving ample opportunity for participants to interact and discuss the complementary perspectives and emerging approaches. The workshop targets a single broad theme of general interest to the vast majority of the NIPS community, namely translations between connectionist models and symbolic knowledge representation and reasoning for the purpose of achieving an effective integration of neural learning and cognitive reasoning, called neural-symbolic computing. The study of neural-symbolic computing is now an established topic of wider interest to NIPS with topics that are relevant to almost everyone studying neural information processing. == KEYWORDS == The following list gives some (but by far not all) relevant keywords for the CoCo @ NIPS 2016 workshop: - neural-symbolic computing; - language processing and reasoning; - cognitive agents; - multimodal learning; - deep networks; - knowledge extraction; - symbol manipulation; - variable binding; - memory-based networks; - dynamic knowledge-bases; - integration of learning and reasoning; - explainable AI. == CALL FOR PAPERS == We invite submission of papers dealing with topics related to the research questions discussed in the workshop. The reported work can range from theoretical/foundational research to reports on applications and/or implemented systems. We explicitly also encourage the submission of more controversial papers which can serve as basis for open discussions during the event. Possible topics of interest include but are (by far!) not limited to: - 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 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. - Approaches/techniques making AI and/or Machine Learning systems/algorithms better explainable or increasing human comprehensibility. = Submission instructions = - Submissions have to be made via EasyChair (https://easychair.org/conferences/?conf=coconips2016) before the paper submission deadline indicated below. - Submissions are limited to at most eight pages, an additional ninth page containing only cited references is allowed. Still, also shorter papers are expressly welcomed. - Submissions have to use the NIPS 2016 submission format (see http://nips.cc/Conferences/2016/PaperInformation/StyleFiles). - Reviewing will be single-blind, i.e., you are free to indicate your name etc. on the paper. (Still, this is not an obligation.) Please note that at least one author of each accepted paper must register for the event and be available to present the paper at the workshop. =Publication= Accepted papers will be published in official workshop proceedings submitted to CEUR-WS.org. Authors of selected papers will be invited to submit a revised and extended version of their papers to a journal special issue after the workshop. == IMPORTANT DATES == - Deadline for paper submission: October 10, 2016 - Notification of paper acceptance: October 30, 2016 - Camera-ready paper due: November 14, 2016 - Workshop date: December 09 or 10, 2016 - NIPS 2015 main conference: December 5-8, 2016 == ADMISSION == The workshop is open to anybody, please register via NIPS 2016 (http://nips.cc ). == WORKSHOP ORGANIZERS == - Tarek R. Besold (University of Bremen, Germany) - Antoine Bordes (Facebook AI Research, USA) - Artur d'Avila Garcez (City University London, UK) - Greg Wayne (Google DeepMind, UK) == ADDITIONAL INFORMATION == - General questions concerning the workshop should be addressed to Tarek R. Besold at Tarek(dot)Besold(at)uni(hyphen)bremen(dot)de. - This workshop is conceptually related to the series of International Workshops on Neural-Symbolic Learning and Reasoning (NeSy). If interested, have a look at http://www.neural-symbolic.org - Please also feel free to join the neural-symbolic integration mailing list for announcements and discussions - it's a low traffic mailing list. If interested, register at http://maillists.city.ac.uk/mailman/listinfo/nesy. -- Digital Media Lab Center for Computing and Communication Technologies (TZI) University of Bremen Email: Tarek.Besold at uni-bremen.de Web: http://sites.google.com/site/tarekbesold/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From mccallum at cs.umass.edu Mon Oct 3 07:54:21 2016 From: mccallum at cs.umass.edu (Andrew McCallum) Date: Mon, 3 Oct 2016 07:54:21 -0400 Subject: Connectionists: Faculty positions at UMass Amherst: junior & senior openings in data science Message-ID: <3A23F1D2-2753-41E8-BF63-C5F46E9E4F22@cs.umass.edu> UMass Amherst Computer Science is hiring faculty in data science broadly this year and for multiple years to come---at both the junior and senior levels. 5 openings in data science this year; 12+ openings over the coming several years; (there are additional faculty openings in other areas this year, as well). I am chairing data science faculty recruiting. I would be happy to receive email from anyone interested and to answer further questions. https://www.cics.umass.edu/job/assistantassociate-professor-positions-data-science Please forward this message to anyone who might be interested. Best, Andrew McCallum Professor; Director, Center for Data Science College of Information and Computer Sciences UMass Amherst =============================================================== data science, broadly: machine learning & decision-making, broadly systems & scalable data management, broadly theory & algorithms for big data, broadly ...non-exclusive list of examples: Methods: algorithms for big data artificial intelligence & ML with big data databases decision processes and reinforcement learning deep learning distributed systems game theory, mechanism design learning theory optimization parallel-distributed machine learning probabilistic programming scalable probabilistic inference statistical machine learning visualization, interpretable ML, and data exploration Modalities: crowd sourcing and human computation images & video information integration natural language processing sensor networks and wearable sensors social networks and computational social science Applications: agriculture, climate, ecology and sustainability computational economics computational biology & bio-medicine education eGovernment energy eScience finance health analytics internet of things manufacturing cities & regions =============================================================== Our Department has become a College and we are dramatically growing our current set of ~50 faculty. UMass CS is highly ranked in AI, exceptionally collaborative, and has long-standing broad interests touching many areas of data science. Selected current faculty include: * Justin Domke (ML & optimization) * Sunghoon Ivan Lee (mobile & personalized health) * Phillipa Gill (networking & security) * Akshay Krishnamurthy (statistical machine learning) * Arya Mazumdar (information theory) * Joydeep Biswas (robotics) * Subhransu Maji (computer vision & ML) * Brendan O'Connor (NLP and computational social science) * Barna Saha (algorithms & data management) * Alexandra Meliou (databases, analytics & causality) * Yuriy Brun (software engineering & analytics) * Dan Sheldon (computational ecology & ML) * Evangelos Kalogerakis (graphics & ML) * Ben Marlin (ML, health analytics) * Deepak Ganesan (sensor and mobile networks, wearable health) * Yanlei Diao (databases) * Gerome Miklau (databases & privacy) * Andrew McGregor (algorithms) * Rui Wang (graphics) * Erik Learned-Miller (computer vision & ML) * David Jensen (data mining & causality) * Andrew McCallum (information extraction & ML) * Brian Levine (security) * Sridhar Mahadevan (ML, RL & manifolds) * Prashant Shenoy (distributed systems, cloud computing) * Ramesh Sitaraman (theory & parallel/distributed systems) * Shlomo Zilberstein (AI) * James Allan (information retrieval) * Beverly Woolf (intelligent tutoring systems) * Rod Grupen (robotics) * Jim Kurose (networking, on leave as head of NSF CISE) * Neil Immerman (complexity theory) * Bruce Croft (information retrieval) * Don Towsley (networking) =============================================================== The College of Information and Computer Sciences at the University of Massachusetts Amherst invites applications for multiple tenure-track faculty positions in Computer Science for the 2017-2018 academic year. Applicants must have a Ph.D. in Computer Science or a related area, and should show evidence of exceptional research promise. Multiple openings are available for Assistant and Associate level Professors in the broad field of Data Science. One position in particular, at the Assistant Professor level, will focus on the subarea of Systems for Data Science. Under exceptional circumstances, highly qualified candidates at other ranks may receive consideration for these openings. Our college is highly supportive of junior faculty, providing both formal and informal mentoring. Many of our faculty are involved in interdisciplinary research, working closely with other departments including statistics/mathematics, linguistics, electrical and industrial engineering, biology, physics, behavioral sciences, economics, political science, and nursing, as well as new green initiatives. Amherst, a historic New England town, is the center of a vibrant and culturally rich area that includes five colleges. For more information about our college, visit https://cics.umass.edu. All applicants should submit a cover letter, curriculum vitae, research statement, and statement of teaching interests. Applicants at the Assistant Professor level should submit the names and contact information for three references and links to two papers that best represent their research/experience, using the submission link specific to the position. Applicants at the Associate Professor level should submit the names and contact information for four references and links to three papers that best represent their research/experience, using the submission link specific to the position. https://umass.interviewexchange.com/jobofferdetails.jsp?JOBID=75312 (Assistant Professor Data Science) https://umass.interviewexchange.com/jobofferdetails.jsp?JOBID=75213 (Associate Professor Data Science) https://umass.interviewexchange.com/jobofferdetails.jsp?JOBID=75221 (Assistant Professor Data Science Systems) Review of applications for the general Data Science openings will begin on October 17, 2016. Review of applications for the Data Science Systems opening will begin on December 15, 2016. We will continue to accept and review applications for all positions through the spring. Rank and salary will be highly competitive and commensurate with qualifications and experience. Inquiries and requests for more information can be sent to: facrec at cs.umass.edu. The university is committed to active recruitment of a diverse faculty and student body. The University of Massachusetts Amherst is an Affirmative Action/Equal Opportunity Employer of women, minorities, protected veterans, and individuals with disabilities and encourages applications from these and other protected group members. Because broad diversity is essential to an inclusive climate and critical to the University's goals of achieving excellence in all areas, we will holistically assess the many qualifications of each applicant and favorably consider an individual's record working with students and colleagues with broadly diverse perspectives, experiences, and backgrounds in educational, research or other work activities. We will also favorably consider experience overcoming or helping others overcome barriers to an academic degree and career. From bremeseiro at udc.es Mon Oct 3 08:58:16 2016 From: bremeseiro at udc.es (Beatriz Remeseiro =?utf-8?Q?L=C3=B3pez?=) Date: Mon, 3 Oct 2016 14:58:16 +0200 (CEST) Subject: Connectionists: EXTENDED deadline: CFP for the special issue "Machine learning in Bioinformatics and Biomedical Engineering" In-Reply-To: <1689365807.24768539.1473247408200.JavaMail.zimbra@udc.es> References: <1689365807.24768539.1473247408200.JavaMail.zimbra@udc.es> Message-ID: <1229072395.29745872.1475499496842.JavaMail.zimbra@udc.es> NEW DEADLINE: October 24, 2016 ================================================== Apologies if you receive this more than once ================================================== CALL FOR PAPERS Machine learning in Bioinformatics and Biomedical Engineering Special issue in Computational and Mathematical Methods in Medicine (open access, JCR-indexed) http://www.hindawi.com/journals/cmmm/si/618503/cfp/ Machine learning is an Artificial Intelligence branch that has been well applied and recognized as an effective tool to handle a wide range of real situations. In the last few years, we have witnessed to the explosion of Big Data, which has enabled researchers to store data for analysis in an unprecedented way. This explosion in data available for analysis is as evident in healthcare as anywhere else. In particular, this special issue is focused on the areas of bioinformatics and biomedical engineering. These are two of the fastest developing research fields in the last few decades, since the biological data used to provide information is rapidly generated, and is mandatory to be able to extract information and knowledge from them, as technological innovation in these fields are to be probably one of the most important developments in the next coming years. Many research problems in the field, such as DNA microarray classification or the identification of candidate genes and nucleotides (SNPs) are computationally hard. Machine learning techniques have become an indispensable tool to discover new biomedical and bioinformatics insights, enabling unprecedented advances and yet embracing new emerging challenges with the advent of Big Data. Visualization will be undoubtedly a challenge during this post-genomic era, as researchers are trying to confront the difficulty of exploring and analyzing a huge amount of biological data as well as making it possible the analysis and data mining by aiding recognition of patterns and trends. In this special issue, we invite investigators to contribute with their recent advances addressing machine learning methods related to, or with application in, Bioinformatics and Biomedical Engineering, as well as review articles that will stimulate the continuing efforts to understand the problems usually encountered in this field. ========================= LIST OF TOPICS ========================= Topics of interest include, but are not limited to: Clinical interpretation, diagnosis and prediction Feature selection and extraction Pattern recognition and classification Dealing with unbalanced, non-static and/or cost-sensitive data Image analysis and visualization Microarray and SNPs analysis Ontologies, taxonomies and semantic web Intelligent sensorization Data mining for knowledge discovery Security, privacy and data integrity ========================= IMPORTANT DATES ========================= Manuscript due: October 24, 2016 First round of reviews: December 16, 2016 Publication date: February 10, 2017 ========================= SUBMISSION ========================= Authors can submit their manuscripts via the Manuscript Tracking System at http://mts.hindawi.com/submit/journals/cmmm/raml/ ========================= ORGANIZATION ========================= Guest Editors Ver?nica Bol?n-Canedo, Universidade da Coru?a, Spain. Beatriz Remeseiro, INESC TEC ? INESC Technology and Science, Portugal. Diego ?lvarez-Est?vez, Medisch Centrum Haaglanden and Bronovo-Nebo, The Netherlands. Amparo Alonso-Betanzos, Universidade da Coru?a, Spain. From samuel.kaski at aalto.fi Mon Oct 3 12:53:47 2016 From: samuel.kaski at aalto.fi (Kaski Samuel) Date: Mon, 3 Oct 2016 16:53:47 +0000 Subject: Connectionists: Tenure Track Professor in Machine Learning Message-ID: <60FF7446-E3CA-41E8-ACA8-B478073AB9DF@aalto.fi> http://www.aalto.fi/en/about/careers/jobs/view/987/ Aalto University School of Science (Helsinki, Finland) invites applications for a Tenure Track Professor in Machine Learning. The vacancy at the Department of Computer Science is open to outstanding individuals who hold a doctorate and are interested in an excellent opportunity to pursue a successful scientific career. The call is open on the Assistant Professor levels of the tenure track system. While we expect most successful applicants to have carried out at least one postdoctoral period, all outstanding candidates will be considered. We are looking for a professor to either further strengthen our strong research fields, with keywords including statistical machine learning, probabilistic modelling, Bayesian inference, kernel methods, computational statistics, or complementing them with deep learning. Collaboration with other fields is welcome, with local opportunities both at Aalto and University of Helsinki. A joint appointment with the Helsinki Institute for Information Technology HIIT (http://hiit.fi/), a joint research centre with University of Helsinki, can be negotiated. Applications with attachments for the tenure track position are to be addressed to the Dean of the Aalto University School of Science and the review of the position will begin on 6 November 2016. The position will remain open until filled. Further details of the application procedure are available at http://www.aalto.fi/en/about/careers/jobs/view/987/. Aalto CS With nine professors and ca. 100 PhD students and postdocs working in machine learning, data mining, and probabilistic modelling, Aalto Department of Computer Science is one of Europe?s leading centres of research in the field of the call. The current faculty?s strength is apparent in e.g. the high volume of extremely competitive funding from the Academy of Finland (equivalent to National Science Foundation) and the European Research Council (ERC), as well as the volume of high-achieving international students entering the MSc and PhD programs in Machine Learning and Data Mining. Furthermore, as the foremost CS educator in Finland, the department is home to the majority of the best Finnish students. In total, the department hosts 44 professors with diverse interests, forming a fertile environment for cross- disciplinary collaborations. On a larger scale, as a technology-friendly, yet small country, Finland offers ample opportunities for low-overhead collaboration with in! dustrial and government partners as well. Aalto University is a community of bold thinkers where science and art meet technology and business. We are committed to identifying and solving grand societal challenges and building an innovative future. Aalto University has six schools with more than 400 professors. Our campuses are located in the Helsinki metropolitan area, Finland. From kau.subbu at gmail.com Mon Oct 3 21:03:40 2016 From: kau.subbu at gmail.com (Kaushik Subramanian) Date: Mon, 3 Oct 2016 18:03:40 -0700 Subject: Connectionists: 2nd CfP: Future of Interactive Learning Machines Workshop @ NIPS 2016 Message-ID: Hi Everyone, We would like to invite submissions for the workshop on the Future of Interactive Learning Machines (FILM) at NIPS 2016 in Barcelona, Spain in December this year. The submission deadline is Oct 14th 2016 (less than two weeks away). Please find the call for papers below. We look forward to your submissions. ====================================================================== NIPS 2016 Workshop: Future of Interactive Learning Machines Barcelona, Spain http://www.filmnips.com/ ====================================================================== Important Dates --------------------------------------------------------------------------------------- Paper submission deadline: *Oct 14th 2016* Notification of acceptance: Oct 29th 2016 Camera-ready submission deadline: Nov 11th 2016 FILM workshop at NIPS 2016 in Barcelona, Spain: Dec 9th 2016 Invited Speakers --------------------------------------------------------------------------------------- Emma Brunskill, Carnegie Mellon University Todd Gureckis, New York University Ece Kamar, Microsoft Research Matthew E. Taylor, Washington State University Vladimir Vapnik, Columbia University and Facebook Overview --------------------------------------------------------------------------------------- Interactive machine learning (IML) explores how intelligent agents solve a task together, often focusing on adaptable collaboration over the course of sequential decision making tasks. Past research in the field of IML has investigated how autonomous agents can learn to solve problems more effectively by making use of interactions with humans. Designing and engineering fully autonomous agents is a difficult and sometimes intractable challenge. As such, there is a compelling need for IML algorithms that enable artificial and human agents to collaborate and solve independent or shared goals. The range of real-world examples of IML spans from web applications such as search engines, recommendation systems and social media personalization, to dialog systems and embodied systems such as industrial robots and household robotic assistants, and to medical robotics (e.g. bionic limbs, assistive devices, and exoskeletons). As intelligent systems become more common in industry and in everyday life, the need for these systems to interact with and learn from the people around them will also increase. This workshop seeks to brings together experts in the fields of IML, reinforcement learning (RL), human-computer interaction (HCI), robotics, cognitive psychology and the social sciences to share recent advances and explore the future of IML. Some questions of particular interest for this workshop include: How can recent advancements in machine learning allow interactive learning to be deployed in current real world applications? How do we address the challenging problem of seamless communication between autonomous agents and humans? How can we improve the ability to collaborate safely and successfully across a diverse user set? We hope that this workshop will produce several outcomes: - A review of current algorithms and techniques for IML, and a focused perspective on what is lacking - A formalization of the main challenges for deploying modern interactive learning algorithms in the real world - A forum for interdisciplinary researchers to discuss open problems and challenges, present new ideas on IML and plan for future collaborations Relevant Topics --------------------------------------------------------------------------------------- - Human-robot interaction - Collaborative and/or shared control - Semi-supervised learning with human intervention - Learning from demonstration, interaction and/or observation - Reinforcement learning with human-in-the-loop - Active learning, Preference learning - Transfer learning (human-to-machine, machine-to-machine) - Natural language processing for dialog systems - Computer vision for human interaction with autonomous systems - Transparency and feedback in machine learning - Computational models of human teaching - Intelligent personal assistants and dialog systems - Adaptive user interfaces - Brain-computer interfaces (e.g. human-semi-autonomous system interfaces) - Intelligent medical robots (e.g. smart wheelchairs, prosthetics, exoskeletons) We seek broad participation from researchers in the fields of artificial intelligence, machine learning, human-computer interaction, cognitive science, robotics, intelligent interface design, adaptive systems and related fields. Submission Details --------------------------------------------------------------------------------------- We encourage submissions covering new ideas in interactive learning, reports on research in progress as well as discussions of open problems and challenges facing interactive machine learning. We are particularly interested in research regarding the practical application of interactive learning systems (for robotics, virtual agents, online education, dialog systems, health care, security, transportation, etc.), and the ability of these systems to handle the complexity of real world problems. We also encourage submissions bringing perspectives from the fields of psychology and social science, and from human computer interaction. Authors are invited to submit long papers (8 pages for main text and 1 page for references) or short papers (2 to 4 pages for main text and 1 page for references) on research relevant to the theme of the workshop. The papers should be formatted according to NIPS formatting guidelines and submitted as a PDF document. All submissions are handled electronically through EasyChair (https://easychair.org/conferences/?conf=filmnips2016). Papers will be subject to a single-blind peer review, i.e. authors can keep their names and affiliations on their submitted papers. Papers will be evaluated based on originality, technical soundness, clarity and potential impact on the field of interactive machine learning. Accepted papers will be made publicly available on the workshop website. Accepted papers will be presented as talks and/or posters at the workshop. --------------------------------------------------------------------------------------- Contact: If you have any questions, comments or concerns, please contact the organizers at film.nips2016 at gmail.com. Looking forward to seeing you in Barcelona! - FILM Organizers -------------- next part -------------- An HTML attachment was scrubbed... URL: From luca.oneto at unige.it Tue Oct 4 05:27:03 2016 From: luca.oneto at unige.it (Luca Oneto) Date: Tue, 4 Oct 2016 11:27:03 +0200 Subject: Connectionists: IJCNN 2017 SPECIAL SESSION on "Large Datasets and Big Data Analytics" Message-ID: [Apologies if you receive multiple copies of this CFP] Call for papers: special session on "Large Datasets and Big Data Analytics: Theory, Methods, and Applications" at IJCNN 2017 International Joint Conference on Neural Networks (IJCNN 2017). 14-19 May 2017, Anchorage, Alaska, USA - http://www.ijcnn.org/ DESCRIPTION: The information age brings along an exponentially growing quantity of heterogeneous data from multiple sources in every aspect of our lives: data coming from social networks, internet of things, experiments in biology research and data from transportation systems are only a few examples. Recent trends in the area suggest that in the coming years the exponential data growth will continue, and that there is a strong need to find efficient solutions to deal with aspects such as data wrangling, real-time processing, information extraction and abstract model generation. Large datasets and big data analytics is the area of research focused on collecting, examining and processing large multi-structure, multi-modal, and multi-source datasets in order to discover patterns, correlations and extract information from data. In order to be able to perform such an analysis, conventional technologies and machine learning theory and algorithms are not directly applicable because they are not able to deal efficiently and effectively with such amount of data. Thus, specific techniques have to be developed. The purpose of this special session is to highlight recent advances in the field of large datasets and big data analytics. In particular, this session welcomes contributions toward both the development of new machine learning methods and the improvement of already available tools suited for big data analysis. We also encourage the submission of new theoretical results in the Statistical Learning Theory framework and innovative solutions to real world problems. In particular, topics of interest include, but are not limited to: - Statistical Learning Theory for Large Datasets; - Big Data Technologies; - Learning on data Streams; - Deep Learning for Large Datasets; - Scalable Machine Learning for Structured Data; - Scalable Kernel Methods for Large Datasets; - Recommender Systems for Large Datasets; - Big Data for Smart Cities and Transportation; - Big Social Data Analysis; - Big Data for Cybersecurity; - Big Data in Bioinformatics and Healthcare; - Big Data in the Internet of Things. SUBMISSION: Prospective authors must submit their paper through the IJCNN portal following the instructions provided inhttp://www.ijcnn.org/paper-submission. Each paper will undergo a peer reviewing process for its acceptance. IMPORTANT DATES: Paper submission deadline : 15 November 2016 Notification of acceptance : 20 January 2017 Camera-ready submission: 20 February 2017 The IJCNN 2017 conference : 14-19 May 2017 SPECIAL SESSION ORGANISERS Luca Oneto University of Genoa (Italy) Nicol? Navarin University of Padua (Italy) Michele Donini Istituto Italiano di Tecnologia (Italy) Fabio Aiolli University of Padua (Italy) Davide Anguita University of Genoa (Italy) ------------------------------------------------------------ ----------------------- Luca Oneto, PhD University of Genoa web: www.lucaoneto.com DIBRIS Department e-mail: Luca.Oneto at unige.it SmartLab Laboratory e-mail: Luca.Oneto at gmail.com Via Opera Pia 11a Fax: +39-010-3532897 16145 Genoa ITALY Phone: +39-010-3532192 www.smartlab.ws ------------------------------------------------------------ ----------------------- -------------- next part -------------- An HTML attachment was scrubbed... URL: From Wilson_Truccolo at brown.edu Tue Oct 4 18:34:03 2016 From: Wilson_Truccolo at brown.edu (Wilson Truccolo) Date: Tue, 4 Oct 2016 18:34:03 -0400 Subject: Connectionists: POSTDOCTORAL POSITIONS IN COMPUTATIONAL NEUROSCIENCE AT BROWN UNIVERSITY Message-ID: Applications for post-doctoral positions are invited for the Laboratory of Dr. Wilson Truccolo in the Department of Neuroscience at Brown University, Providence, RI, USA. The positions are for the development of data-driven stochastic models of multiscale neural dynamics. Neural data consist of recordings of single-neuron ensembles and local field potentials obtained via multiple intracortical microelectrode arrays implanted in human and non-human primates. Research topics include: (1) Role of neuronal network intrinsic dynamics in neural encoding and decoding. (2) Multiscale neocortical dynamics in human focal epilepsy: seizure transition, propagation and termination. (3) Precursor signatures of focal seizure transitions, prediction and control. The ideal candidate will have a strong background in computational/theoretical neuroscience and modeling of stochastic neural dynamics. Related publications can be found on the Truccolo lab website ( http://www.truccololab.com/ ). Inquiries should be addressed to Dr. Truccolo (wilson_truccolo at brown.edu). Applications including a CV, statement of research interests, and the names and full contact details of three referees should be sent to wilson_truccolo at brown.edu. -- Wilson Truccolo, Ph.D. Pablo J. Salame '88 Goldman Sachs Assistant Professor of Computational Neuroscience Department of Neuroscience & Institute for Brain Science, Brown University Lab website: http://www.truccololab.com/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From poma at mmmi.sdu.dk Wed Oct 5 05:33:28 2016 From: poma at mmmi.sdu.dk (Poramate Manoonpong) Date: Wed, 5 Oct 2016 09:33:28 +0000 Subject: Connectionists: [jobs] 2 Available Postdoc Positions in Neural Control and Embedded System Technologies for for Brain Machine Interface at University of Southern Denmark in Odense Message-ID: Two postdoc positions available for our new FET-PROACT project on monkey brain-based smart house control The Embodied AI and Neurorobotics Lab http://ens-lab.sdu.dk/ , part of Centre for BioRobotics (CBR) at the Maersk Mc-Kinney Moller Institute at the University of Southern Denmark, is offering: Two postdoc positions starting from January 2017 or as soon as possible thereafter, for up to four years. The postdocs will work on our exciting Plan4Act: "Predictive Neural Information for Proactive Actions: From Monkey Brain to Smart House Control" project recently funded by FET-Proactive (Area 2: Biotech for better life) under Horizon 2020 Framework Program. The goal of the Plan4Act project is to record and understand predictive neural activity from monkey brain and use it to proactively control devices in a smart house. The far-future vision behind this is to endow motor-impaired patients with the ability to plan a daily-life goal - like making coffee - and achieve it without having to invoke one by one every single individual action to reach this goal. In the context of the project, we provide two topics for the positions: Topic 1 "neural control technology": Postdoc1 will focus on the development of generic adaptive neural-based control for processing recorded sequence-predicting neural activity from monkey brain, predicting the upcoming sequence of actions, and finally generating the corresponding complex action sequences for smart house control. Topic 2 "embedded system technology": Postdoc2 will focus on the development of a controller board based on a field-programmable gate array (FPGA) for the hardware implementation of the adaptive neural-based control. The FPGA-based hardware controller will interface with a neural recording device and a smart house. It will receive neural activities from monkey brain through the recording device, process the information, and transmit final commands to a smart house. The successful candidates will be expected to have 1) a PhD degree in - Topic1: theoretical and computational neuroscience, artificial intelligence, physics of complex systems, control system engineering, robotics or a quantitative field. - Topic2: embedded system, electrical engineering and computer science, robotics or a quantitative field. 2) articles published in international peer-reviewed journals documenting experience with - Topic1: neural dynamics, learning and adaptation in neural systems, mean field methods, complex signal processing, information theory, adaptive control for human-machine interaction. - Topic2: brain machine interface, embedded systems, FPGA systems (Design), FPGA interfacing, Neural Networks in FPGAs, etc. 3) strong background on - Topic1: artificial neural networks (in particular recurrent networks and cell assemblies), statistical machine learning, mean field theory, information theory, complex signal processing, hardware implementation, robotics, and adaptive control for human-machine interaction. - Topic2: system integration, FPGA system design, PCB design, Circuit Design, Xilinx FPGAs, Micro Blaze, Zynq, Neural Networks in FPGAs. 4) good programming skills (e.g., ROS, C, C++, MatLab for Topic1, and VHDL, C, C++, Matlab Simulink for Topic2). Additionally, the candidate should have excellent writing skills and be able to work independently. The successful candidates for the positions will be affiliated to the Embodied AI and Neurorobotics Lab at the Maersk Mc-Kinney Moller Institute, the University of Southern Denmark. Applicants should provide a covering letter explaining their approach to the problems of Topic1 and Topic2 alluded to above, and at most three articles illustrating their publication record and research interests, in addition to standard items such as CV, full publication list, etc. Please refer to the official advert [1] for application details and guideline. The deadline for applications via the online system [1] is 15 November 2016. [1] https://ssl1.peoplexs.com/Peoplexs22/CandidatesPortalNoLogin/Vacancy.cfm?PortalID=3794&VacatureID=859268 Contact Information: Further information is available from Associate Prof. Poramate Manoonpong, email poma at mmmi.sdu.dk Assistant Prof. J?rgen Christian Larsen, email jcla at mmmi.sdu.dk Research environment: Please see http://ens-lab.sdu.dk/contact for the location of the Embodied AI and Neurorobotics Lab. To get a better idea of related research, please visit http://ens-lab.sdu.dk Best regards Poramate Manoonpong Associate Professor The Maersk Mc-Kinney Moller Institute T +45 65 50 86 98 poma at mmmi.sdu.dk University of Southern Denmark Campusvej 55 DK-5230 Odense M www.sdu.dk [http://cdn.sdu.dk/img/sdulogos/SDU_BLACK_signatur.png] -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image001.png Type: image/png Size: 1388 bytes Desc: image001.png URL: From triesch at fias.uni-frankfurt.de Wed Oct 5 09:23:03 2016 From: triesch at fias.uni-frankfurt.de (Jochen Triesch) Date: Wed, 5 Oct 2016 15:23:03 +0200 Subject: Connectionists: Call for applications: The International Max Planck Research School for Neural Circuits in Frankfurt, Germany Message-ID: The International Max Planck Research School (IMPRS) for Neural Circuits (Frankfurt am Main, Germany) offers up to ten positions every year for talented students holding a relevant Master?s or Bachelor?s degree to perform research resulting in a PhD. The program is taught in English. The common focus of the IMPRS for Neural Circuits will be the understanding of neural circuits (from the simple to the large and complex), at all scales required to achieve this understanding. This ambitious objective will require analyses at the molecular, cellular, multi-cellular, network and behavioral levels, with the full understanding that macroscopic phenomena (spatial patterns, dynamics) can be scale-dependent, and that reductionism is not always sufficient as a method. Research areas are perception, connectomics, theoretical neuroscience, synaptic plasticity, brain dynamics, neural circuits, behavior and systems neuroscience. In the IMPRS for Neural Circuits we offer a multidisciplinary program to excellent doctoral students with backgrounds in neuroscience, mathematics, physics, computer science, (bio) chemistry, biology and medicine as well as research experience in the participating institutions of the Frankfurt Neuroscience community. Students will participate in a tailor-made educational program including research rotations and neuroscience courses but also in trainings in transferable skills as well as summer schools, lecture series and exchange programs with excellent research institutes abroad. The call for applications of the seventh round is now open. The deadline is December 15, 2016 for positions starting in the Fall of 2017. For exciting PhD studies in the heart of Europe, please apply via www.imprs.brain.mpg.de. -- Prof. Dr. Jochen Triesch Johanna Quandt Research Professor Frankfurt Institute for Advanced Studies http://fias.uni-frankfurt.de/neuro/triesch/ Tel: +49 (0)69 798-47531 Fax: +49 (0)69 798-47611 From danny.silver at acadiau.ca Wed Oct 5 10:29:15 2016 From: danny.silver at acadiau.ca (Danny Silver) Date: Wed, 5 Oct 2016 14:29:15 +0000 Subject: Connectionists: =?utf-8?q?JOB=3A_Research_Assistant_to_work_on_ma?= =?utf-8?q?chine_learning_project_entitled_=E2=80=9CDeep_Sequencing_Learni?= =?utf-8?q?ng_for_Smart_Virtual_Assistants=E2=80=9D=2E?= Message-ID: The Acadia Institute for Data Analytics, Acadia University, is looking for a Research Assistant to work on a short-term machine learning project entitled ?Deep Sequencing Learning for Smart Virtual Assistants?. The Project The project aims to develop, test & apply innovative sequential event models to predict customer actions and recommend company actions to achieve pre-configured business goals. A sequence (state-action) learning approach will be taken using memory-based recurrent deep learning (RNN) and/or recurrent reinforcement learning (RRL) methods. The ideal candidate will be able to work independently on data preparation, machine learning software development / modifications, model development, and model testing. The work will be done under the guidance of Dr. Danny Silver, Acadia University and in collaboration with Mr. Shameer Iqbal of Singolar Inc. Preference will be given to candidates interested in continuing on to work with Singolar following the successful completion of the project. Essential and Desirable Skills A Bachelor?s or Master?s degree in Math or Computer Science; a background in data analytics & machine learning; strong oral & written skills (a publication record would be welcome), and a track record of working effectively in a team on complex problems is required. Specifically, the person should be proficient in programming with Python (preferred), MATLAB or R; have good knowledge of machine learning libraries like Theano, Tensor Flow, Keras; comfortable working with Linux and parallel processing machines, including cloud-based services such as AWS; demonstrate deep knowledge of artificial neural networks; and have experience building accurate time series & sequential event models with recurrent neural networks and / or reinforcement learning algorithms. Knowledge of data mining suites such as Weka or RapidMiner; and any background in Natural Language Processing would be a plus. The candidate should be capable of independently preparing data (ETL functions of cleaning, consolidating, transforming data) for machine learning purposes. Schedule and Remuneration The project will run for 18 weeks, starting October 31, 2016 to March 3, 2017. The pay is $25 per hour (plus 4% vacation pay) for 35 hours per week for 16 weeks over his period. The project will pause for two weeks over the Christmas holidays (Dec 21 ? Jan 03). How to Apply / Get Project Information For more information or to apply, contact danny.silver at acadiau.ca. When applying, please include a covering email, CV, and the names and contact information (addresses, email, phone number) of three referees. Shortlisted applicants will be interviewed beginning October 10, 2016. Interested candidates should familiarize themselves with the work of Dr. Silver and Singolar. Further information on the Acadia Institute for Data Analytics can be found at http://aida.acadiau.ca. ======================= Daniel L. Silver, Ph.D. danny.silver at acadiau.ca Professor and Acting-Director, Jodrey School of Computer Science Director, Acadia Institute for Data Analytic Acadia University, Office 314, Carnegie Hall, Wolfville, NS Canada B4P2R6 p:902-585-1413 f:902-585-1067 -------------- next part -------------- An HTML attachment was scrubbed... URL: From dr_ravirao at hotmail.com Wed Oct 5 13:07:11 2016 From: dr_ravirao at hotmail.com (Ravi Rao) Date: Wed, 5 Oct 2016 17:07:11 +0000 Subject: Connectionists: CFP: IEEE Transactions on Cognitive and Developmental Systems: Special Issue on Multi-modal Integration and Development Message-ID: IEEE Transactions on Cognitive and Developmental Systems Special Issue on Multi-modal Integration and Development I. Aim And Scope Traditionally, researchers in computational intelligence, cognitive science and neuroscience have focused on one sensory modality at a time, such as vision, audition or touch. This has led to a fundamental understanding of the encoding processes involved for each sensory pathway. The time is now ripe for expanding the focus of this research to investigate the integration of multi-modal inputs. Though the field of neuroscience has identified higher-level convergence zones for multimodal input, there are few computational models that faithfully replicate the workings of these circuits. We note that the vertebrate brain has evolved in a world where stimuli from objects contain multiple sensory modalities. There is also a strong epigenetic, developmental aspect of multi-sensory processing and multimodal integration, as evidenced by results in the experimental literature. This leads to a multi-modal developmental perspective, where several brain structures are devoted to the coordinated representation and processing of these signals, including the hippocampus for memory formation and the basal ganglia for motor action. These are fundamental to understanding processes that govern cognition and mental development. II. Themes The purpose of this Special Issue on Multi-modal Integration is to advance the state of the art in our understanding of neural, cognitive and computational models that govern multi-modal processing. We welcome contributions in areas such as audio-visual processing, visuo-haptic processing and visuo-motor processing. Furthermore, the control of motor action also involves multi-modal processing such as combining proprioception with visual feedback for target tracking. Topics relevant to this special issue include, but are not limited to * Audio-visual processing * Visuo-haptic processing * Computational models of multi-sensory processing * Learning mechanisms for sensory integration * Multi-modal development mechanisms * Motor integration with sensory inputs * Models of sensory convergence * Modeling of proprioceptive inputs * Adaptation mechanisms for sensory deficits * Modeling of proprioceptive inputs * Subcortical models of sensory integration III. Submission Manuscripts should be prepared according to the "Information for Authors" of the journal found at http://cis.ieee.org/publications.html and submissions should be done through the IEEE TCDS Manuscript center: https://mc.manuscriptcentral.com/tcds-ieee and please select the category "SI: Multi-Modal Integration and Development". IV. Important Dates 15 Jan 2017 -- Deadline for manuscript submission 15 Apr 2017 - Notification of authors 15 May 2017- Deadline for revised manuscripts 15 June 2017- Final version For further information, please contact one of the following Guest Editors. V. Guest Editors Dr. A. Ravishankar Rao School of Computer Science and Engineering, Fairleigh Dickinson University, USA ravirao at fdu.edu Dr. Yoonsuck Choe, Department of Computer Science and Engineering, Texas A&M University, USA choe at tamu.edu Dr. Srinivasa Chakravarthy Dept. of Biotechnology, IIT Madras, India schakra at ee.iitm.ac.in ________________________________ -------------- next part -------------- An HTML attachment was scrubbed... URL: From gemmar at mit.edu Wed Oct 5 17:34:31 2016 From: gemmar at mit.edu (Gemma Roig) Date: Wed, 5 Oct 2016 21:34:31 +0000 Subject: Connectionists: Call for Abstracts submission for the AAAI Spring Symposium Series | Science of Intelligence : Computational Principles of Natural and Artificial Intelligence Message-ID: Call for Abstracts submission for the AAAI Spring Symposium Series | Science of Intelligence : Computational Principles of Natural and Artificial Intelligence **************************************************************************** AAAI Spring Symposium Series | Science of Intelligence: Computational Principles of Natural and Artificial Intelligence http://cbmm.mit.edu/Symposium-Science-of-Intelligence Organized by the Center for Brains Minds and Machines March 27?-29 2017 at Stanford University in Palo Alto, California **************************************************************************** OVERVIEW Science of Intelligence is a new emerging field dedicated to developing a computation-based understanding of intelligence -both natural and artificial-, and to establishing an engineering practice based on that understanding. The Center for Brains Minds and Machines is organizing this symposium as a unique opportunity to bring together experts in artificial intelligence, cognitive science, and computational neuroscience to share and discuss the advances and the challenges of the study of the computational principles of natural and artificial intelligence. **************************************************************************** KEYNOTE SPEAKERS ?James DiCarlo (MIT) ?Li Fei-Fei (Stanford) ?Surya Ganguli (Stanford) ?Samuel Gershman (Harvard) ?Kristen Grauman (University of Texas at Austin) ?Gabriel Kreiman (Harvard) ?Karen Livescu (Toyota Technological Institute at Chicago) ?Aude Oliva (MIT) ?Pietro Perona (Caltech) ?Tomaso Poggio (MIT) ?Lorenzo Rosasco (Italian Institute of Technology) ?Amnon Shashua (Hebrew University and CTO at Mobileye) ?Joshua Tenenbaum (MIT) ?Shimon Ullman (Weizmann Institute) ?Patrick Winston (MIT) ?Daniel Yamins (Stanford) ?Alan Yuille (Johns Hopkins) **************************************************************************** CALL FOR PARTICIPATION This will be a 3-day symposium consisting on keynote talks, oral and poster presentations, panel discussions and a doctoral consortium. Authors willing to participate are invited to submit an abstract following these guidelines: http://cbmm.mit.edu/Symposium-Science-of-Intelligence/submissions DEADLINE ABSTRACT SUBMISSION: October 28, 2016 at 11:59pm (UTC-12) Students that submitted an abstract will be eligible for the doctoral consortium. Selected students will be assigned a mentor from the keynote speakers to discuss their work and future career plans. **************************************************************************** Program Chairs and Organizing Committee: ?Gemma Roig (MIT) gemmar at mit.edu The Center for Brains Minds and Machines ?Xavier Boix (MIT) xboix at mit.edu The Center for Brains Minds and Machines **************************************************************************** **************************************************************************** -------------- next part -------------- A non-text attachment was scrubbed... Name: smime.p7s Type: application/pkcs7-signature Size: 1845 bytes Desc: not available URL: From ted.carnevale at yale.edu Wed Oct 5 20:01:47 2016 From: ted.carnevale at yale.edu (Ted Carnevale) Date: Wed, 5 Oct 2016 20:01:47 -0400 Subject: Connectionists: high performance computing with the Neuroscience Gateway Portal Message-ID: Space is still available in the workshop on the Neuroscience Gateway Portal (NSG), but if you are interested you should act soon because space is limited and the registration deadline is Friday Oct. 28. The NSG is an NSF-supported resource for neuroscientists whose research involves computationally intensive modeling and/or data analysis. It has a simple, convenient user interface for running simulations and data analysis tasks on HPC hardware, and provides free CPU time. Currently installed software includes Brian, GENESIS, MOOSE, NEST, NEURON, PyNN, Freesurfer, and the Virtual Personalized Multimodal Connectome Pipeline. The workshop will be held on Saturday, Nov. 12, from 9 AM to noon, just before the start of the 2016 SFN meeting, at a downtown San Diego location near the convention center. The agenda includes instruction on how to use the NSG in your own research, a hands-on exercise, and presentations by research teams about how they are using the NSG for their own high performance computing needs. See http://www.neuron.yale.edu/neuron/static/courses/nsg2016/nsg2016.html for more information and a link to the registration form. --Ted From pascal.fua at epfl.ch Thu Oct 6 05:59:12 2016 From: pascal.fua at epfl.ch (Pascal Fua) Date: Thu, 6 Oct 2016 11:59:12 +0200 Subject: Connectionists: PhD Candidate Position in Computer Vision at EPFL Message-ID: EPFL's Computer Vision laboratory (http://cvlab.epfl.ch) has an opening for a PhD candidates interested in using Deep Learning techniques to model intra-cellular structures in Electron Microscopy images of the brain. For more details about our current research activities in this area, see http://cvlab.epfl.ch/research/ . For practical information about EPFL's doctoral program, see http://phd.epfl.ch/edic. Education: Masters degree in Computer Science or related field with experience in the areas of Computer Vision or Medical Image Processing. A strong background in Mathematics is desirable. Applying: 1. Apply by December 15th to our doctoral program, as explained under http://phd.epfl.ch/edic/application. 2. Specify in the application form that you are interested by Prof. Fua's CVLab. Please do not contact Prof. Fua directly. Your application will be forwarded to him. -- -------------------------------------------------------------------- Prof. P. Fua (Pascal.Fua at epfl.ch) Tel: 41/21-693-7519 FAX: 41/21-693-7520 Url: http://cvlab.epfl.ch/~fua/ -------------------------------------------------------------------- From anastasia.osoianu at gmail.com Wed Oct 5 14:31:41 2016 From: anastasia.osoianu at gmail.com (Anastasia Osoianu) Date: Wed, 5 Oct 2016 20:31:41 +0200 Subject: Connectionists: Brainhack: Anatomy edition in Paris, 24-26 October 2016 Message-ID: Registration is now open for Brain-anatomy-hack in Paris. Brain-anatomy-hack aims at promoting the interaction between scientists on questions concerning (1) the investigation of brain anatomy based on magnetic resonance imaging or post mortem dissection; (2) the evolution of nervous systems across species; (3) the variability of brain features across healthy participants; (4) the insurgence of brain pathologies. Program Each of the three days will begin with an ?Ignite Session? in which speakers will give 15-30 minute talks that will address wide questions in neuroanatomy that would benefit from open, interdisciplinary collaborations. The ?Ignite Session? will be followed by a ?hack session? and a dynamic set of talks organized by attendees. During the ?hack sessions?, participants will be encouraged to work together in small groups on relevant projects. The workshop will culminate on the last day, when participants will have the opportunity to present a brief overview of their project. Participants can bring their own dataset, discuss a project and recruit a team of collaborators on site. Access to free big online databases of MRI images will be also available during the three days, for new creative ideas to be tested. This workshop is also an opportunity to learn methods, develop skills and collaborate with other participants. Participants will be supervised and receive advice on methods from a team of very capable nerds including Roberto Toro, Michel Thiebaut de Schotten, Daniel Margulies, Alexandros Goulas, Julien Lefevre and Leonardo Cerliani throughout the three days. A constant flow of food and drinks (especially coffee?) will be provided during the conference breaks. We kindly request an online preregistration (70?) in order to cover the expenses for the venue, the equipment and the food/drinks. Deadline is 16th of October 2016. For more information and preliminary schedule visit: http://neuroanatomy.github.io/events/brainhack/ To learn more about Brainhack and previous events: http://brainhack.org/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From azahkm at gmail.com Thu Oct 6 08:59:47 2016 From: azahkm at gmail.com (Azah Kamilah Muda) Date: Thu, 6 Oct 2016 05:59:47 -0700 Subject: Connectionists: =?utf-8?q?Final_CFP_=3A_SoCPaR=2716_=26_CaSON=271?= =?utf-8?q?6_-_Springer_=E2=80=93_Vellore=2C_India_-_New_Deadlines?= Message-ID: ** We apologize in advance if you receive multiple copies of this CFP ** ** Kindly help to distribute this CFP to your mailing list ** ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -- The 8th International Conference on Soft Computing and Pattern Recognition (SoCPaR'16) ? C Vellore, India ( December 19 - 21, 2016) http://www.mirlabs.org/socpar16 http://www.mirlabs.net/socpar16 -- The 8th International Conference on Computational Aspects of Social Network (CaSON'16) ? Vellore, India ( December 19 - 21, 2016) http://www.mirlabs.org/cason16 http://www.mirlabs.net/cason16 ** Important Dates ** ---------------------------------- Special sessions/Track/workshop proposals: August 31, 2016 Acceptance of special sessions: September 05, 2016 Paper submission due: September 30, 2016 *Paper submission due (extended): October 21, 2016* *--------------------------------------------------------------------------*Notification of paper acceptance: October 15, 2016 *Notification of paper acceptance (extended): October 31, 2016* *----------------------------------------------------------------------------------------* Registration and Final manuscript due: November 10, 2016 Conference: December 19 - 21, 2016 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ About SoCPaR'16 : ------------------------- Conference Objective: The International Conference on Soft Computing and Pattern Recognition ( SoCPaR) is a major international conference bringing together researchers, engineers, and practitioners who work in the areas of soft computing and pattern recognition in the industry and real world. Every year, SoCPaR attracts authors from over 30 countries. After the success of the Seventh edition, which was held in Japan, this year event will be held in Vellore, India. SoCPaR'16 invites novel contributions/papers of soft computing and pattern recognition from fundamental aspects to various practical applications. All accepted and registered papers will be included in the conference proceedings to expected be published by Springer. Topics ( not limited to ) ----------------------------- [Soft Computing and Applications] Evolutionary computing Swarm intelligence Artificial immune systems Fuzzy Sets Uncertainty analysis Fractals Rough Sets Support vector machines Artificial neural networks Case Based Reasoning Wavelets Hybrid intelligent systems Nature inspired computing techniques Machine learning Ambient intelligence Hardware implementations [Pattern Recognition and Applications] Information retrieval Data Mining Web Mining Image Processing Computer Vision Bio-informatics Information security Network security Steganography Biometry Remote sensing Medical Informatics E-commerce Signal Processing Control systems About CaSON'16 : ------------------------- The International Conference on Computational Aspects of Social Network (CASoN) is a major international conference that brings together an interdisciplinary venue for social scientists, mathematicians, computer scientists, engineers, computer users, and students to exchange and share their experiences, new ideas, and research results about all aspects (theory, applications and tools) of intelligent methods applied to Social Network, and to discuss the practical challenges encountered and the solutions adopted. Industrial Workshop/Tutorials and conference sessions will allow individuals interested in the theory, methods, or applications of social network analysis to share ideas and explore common interests. All accepted and registered papers will be included in the conference proceedings to expected be published by Springer. We solicit original research and technical papers not published elsewhere. The papers can be theoretical, practical and application, and cover a broad set of intelligent methods, with particular emphasis on Social Network computing. Methods such as (but not restricted to) : Neural Networks and Connectionist Models Evolutionary Algorithms Fuzzy Logic Knowledge Management Multi-valued Logic Semantic Networks Rough Sets Intelligent Agents Ontologies Reinforcement Learning Applications on Social Networks: Network evolution Network evolution and growth mechanisms. Online communities and computer networks. Information diffusion in social networks. Detection of communities by document analysis. Topology of real networks. Recommendation: Information diffusion in social networks. Recommendations for product purchase, information acquisition and establishment of social relations. Impact of recommendation models on the evolution of the social network. Classification models and their application in social recommender systems. Advertisement models : Economical impact of social network discovery. Social advertising. Use of social networks for marketing. Search in network: Web page ranking informed by social media. Search algorithms on social networks. Collaborative Filtering. Security : Anomaly detection in social network evolution. Data protection inside communities. Crime data mining and network analysis. Modeling trust and reputation in social networks. Misbehavior detection in communities. Network geography : Geographical clusters, networks, and innovation. Social geography. International Collaborations in e-Social network. Web : Automatic discovery and analysis of Web based social networks. Link Topology and Site Hierarchy. Web mining algorithms. Web communities. Web-Based Cooperative Work. Evaluation : Test collection. Benchmark creation. Measures and methodologies. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Submission Guidelines: ------------------------------------------------------ Submission of paper should be made through the submission page from the conference web page. Please refer to the conference website for guidelines to prepare your manuscript. Paper format templates: http://www.springer.com/series/11156 Proceedings are expected to be published by the Advances in Intelligent and Soft Computing, which is now indexed by ISI Proceedings, DBLP. Ulrich's, EI-Compendex, SCOPUS, Zentralblatt Math, MetaPress, Springerlink Proceedings will be made available during the conference. Expanded versions of selected papers will be published in special issues of internationally referred journals (indexed by SCI) and edited volumes. SoCPaR?16 Submission : http://www.easychair.org/conferences/?conf=socpar2016 CaSON?16 Submission : https://easychair.org/conferences/?conf=cason2016 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ * Organizing Committee * ---------------------------------- Chairs : Ajith Abraham, Machine Intelligence Research Labs (MIR Labs), USA Aswani Kumar Cherukuri, VIT University, India Ana Maria Madureira, Instituto Superior de Engenharia do Porto, Portugal Technical Committee ( Please refer website ) : http://www.mirlabs.net/socpar16/committees.php http://www.mirlabs.net/cason16/committees.php For technical contact: ---------------------------------- Ajith Abraham Email: ajith.abraham at ieee.org -- Best Regards, Azah Muda -- Best Regards, Azah Muda -------------- next part -------------- An HTML attachment was scrubbed... URL: From shelie at purdue.edu Thu Oct 6 09:02:00 2016 From: shelie at purdue.edu (Sebastien Helie) Date: Thu, 6 Oct 2016 09:02:00 -0400 Subject: Connectionists: Department of Psychological Sciences Head Search @ Purdue University Message-ID: <2b5bbf07-2cfa-5138-f88a-032508de9e94@purdue.edu> Applications and nominations are invited for the position of Head of the Department of Psychological Sciences, College of Health and Human Sciences, Purdue University. The position will be available July 1, 2017 with a five-year renewable term reporting to the Dean of the College of Health & Human Sciences. The Head will provide leadership, vision, and serve as a facilitator for departmental research and scholarship, and educational activities. In addition, the Head is responsible for fiscal management of the department, personnel issues, faculty/staff development, and advocacy for the Department to the College, University, and larger community. We are looking for an academic leader and scholar with a strong commitment to the research, teaching, and applied missions of the department. Applicants should have scholarly credentials commensurate with the rank of Tenured Full Professor. A Ph.D. is required in a relevant field. Field of specialization is open. Desirable attributes include a strong record of published research and external funding as well as prior experience in academic administration, graduate education, and a commitment to development and advancement of the department. The successful candidate will be someone with excellent communication skills who values and promotes diversity. The Department of Psychological Sciences (http://www.purdue.edu/hhs/psy/) is a diverse and collegial department with about 50 full-time research/tenure track faculty. Research is conducted in the areas of Behavioral Neuroscience, Clinical Psychology, Cognitive Psychology, Industrial-Organizational Psychology, Mathematical & Computational Cognitive Science, and Social Psychology. The clinical program is APA-accredited. Faculty members in the department have active collaborative research involvement with colleagues across the University. The department awards Bachelors, Masters, and Ph.D. degrees and currently has approximately 600 undergraduate majors, including those in the Research-focused Honors Program, and 70 graduate students. The College of Health and Human Sciences (http://www.purdue.edu/hhs/), home to the Department of Psychological Sciences, is comprised of nine units and is the home of the Master of Public Health program. In addition, Purdue University is invested in promoting an exceptional research and learning environment. This includes the hub for interdisciplinary work in Discovery Park (http://www.purdue.edu/discoverypark/) and a $250M investment into life sciences over the next five years, and a new magnetic resonance imaging center hosting a 3T Siemens MAGNETOM Prisma and 3T General Electric MR750. Purdue is an ADVANCE institution (http://www.purdue.edu/discoverypark/advance/). Purdue University is located 2 hours from Chicago and 1 hour from Indianapolis. The diverse Lafayette/West Lafayette communities of approximately 100,000 boast a low cost of living and some of the best schools in the country (http://www.homeofpurdue.com/). Review of applications will begin November 15, 2016 and will continue until the position is filled. Applicants should submit their complete curriculum vitae, a letter of interest indicating relevant experience and qualifications, statements of research, teaching, and leadership philosophy, and a list of at least three references. Materials should be sent electronically to P. Jane Morris (pmorris1 at purdue.edu). Questions regarding the position may be sent to the Chair of the search committee, Professor Tim Gavin at (765) 494-3179 (gavin1 at purdue.edu). Purdue University is an EOE/AA employer. All individuals, including minorities, women, individuals with disabilities, and protected veterans are encouraged to apply. A background check will be required for employment in this position. -- ----------------------------------------------------------------- Sebastien Helie, Ph.D. Associate Professor of Psychological Sciences Associate Director of the Purdue Life Sciences Imaging Facility Co-Director of CEREBBRAL -- Department of Psychological Sciences Purdue University 703 Third Street West Lafayette, IN 47907-2081 -- Office: Peirce Hall, Room 359 Phone: (765) 496-2692 E-mail: shelie at purdue.edu Website: http://ccn.psych.purdue.edu/ ---------------------------------------------------------------- From j.eppler at fz-juelich.de Thu Oct 6 13:20:36 2016 From: j.eppler at fz-juelich.de (Jochen Martin Eppler) Date: Thu, 6 Oct 2016 19:20:36 +0200 Subject: Connectionists: Workshop "Code Generation from Model Description Languages" Message-ID: Dear Colleagues! We're happy to announce the workshop "Code Generation from Model Description Languages II" on December 7 to 9 2016, which will be hosted at Forschungszentrum J?lich, Germany. With this workshop, we would like to gather computational neuroscience researchers who are interested in modeling languages such as NeuroML, NineML, NESTML and NMODL and how to generate efficient source code from them. The workshop covers introductions to the simulators as well as hands-on sessions for the different languages. More details and a registration page can be found here: https://indico-jsc.fz-juelich.de/event/25/ We're looking forward to your participation! Best regards, Jochen! -- Dr. Jochen Martin Eppler Phone: +49(2461)61-96653 ---------------------------------- Simulation Laboratory Neuroscience J?lich Supercomputing Centre Institute for Advanced Simulation ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ 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 dengdehao at gmail.com Thu Oct 6 11:11:45 2016 From: dengdehao at gmail.com (Teng Teck Hou) Date: Thu, 6 Oct 2016 23:11:45 +0800 Subject: Connectionists: [IJCNN 2017] Upcoming deadlines for Tutorials and Workshop Proposals Message-ID: <002c01d21fe3$f4f74a10$dee5de30$@gmail.com> [Apologies for cross-postings] ############################################################ International Joint Conference on Neural Networks May 14-19, 2017, Anchorage, Alaska, USA http://www.ijcnn.org/ ##################### Important Dates ###################### * Tutorial and Workshop Proposals October 15, 2016 * Paper Submission November 15, 2016 * Paper Decision Notification January 20, 2017 * Camera-Ready Submission February 20, 2017 #################### UPCOMING DEADLINES #################### CALL FOR WORKSHOPS http://www.ijcnn.org/call-for-workshops CALL FOR TUTORIALS http://www.ijcnn.org/call-for-tutorials [UPCOMING DEADLINES 23.59hr UTC-10 on Saturday, 15 OCTOBER 2016] ############################################################ The 2017 International Joint Conference on Neural Networks (IJCNN 2017) will be held at the William A. Egan Civic and Convention Center in Anchorage, Alaska, USA, May 14-19, 2017. The conference is organized jointly by the International Neural Network Society and the IEEE Computational Intelligence Society, and is the premiere international meeting for researchers and other professionals in neural networks and related areas. It will feature invited plenary talks by world-renowned speakers in the areas of neural network theory and applications, computational neuroscience, robotics, and distributed intelligence. In addition to regular technical sessions with oral and poster presentations, the conference program will include special sessions, competitions, tutorials and workshops on topics of current interest. For the latest updates, follow us on Facebook (https://fb.me/ijcnn2017/) and Twitter (@ijcnn2017). #################### Paper Submission is now Open #################### http://www.ijcnn.org/call-for-papers * Regular paper can have up to 8 pages in double-column IEEE Conference format * All papers are to be prepared using IEEE-compliant Latex or Word templates on paper of U.S. letter size. * All submitted papers will be checked for plagiarism through the IEEE CrossCheck system. * Papers with significant overlap with the authors own papers or other papers will be rejected without review. ##########################Call for Workshops########################## Post-conference workshops offer a unique opportunity for in-depth discussions of specific topics in neural networks and computational intelligence. The workshops should be moderated by scientists or professionals who has significant expertise and /or whose recent work has had a significant impact within their field. IJCNN 2017 will emphasize emerging and growing areas of computational intelligence. Each workshop has a duration of 3 or 6 hours. The format of each workshop will be up to the moderator, and can include interactive presentations as well as panel discussions among participants. These interactions should highlight exciting new developments and current research trends to facilitate a discussion of ideas that will drive the field forward in the coming years. Workshop organizers can prepare various materials including handouts or electronic resources that can be made available for distribution before or after the meeting. Researchers interested in organizing workshops are invited to submit a formal proposal including the following information as a single file (pdf, doc, etc.) to the workshop chair: * Title * Organizers and their short bio * Brief description of the scope and impact of the workshop * Timeliness of the topic * Confirmed and/or potential speakers * Half day (3 hours) or full day (6 hours) * Link to organizer's web page and/or workshop web site (optional) For further details, please refer http://www.ijcnn.org/call-for-workshops. Any questions regarding this proposal can be asked to the Workshop Chair: Lazaros Iliadis, Democritus University of Thrace, Greece. E-mail: liliadis at fmenr.duth.gr ##########################Call for Tutorials########################## IJCNN 2017 will feature pre-conference tutorials addressing fundamental and advanced topics in computational intelligence. Tutorial proposals should be emailed to the Tutorial Chair (see below). A tutorial proposal should include the * Title * Presenter/organizer name(s) and affiliations * Expected enrollment * Abstract (less than 300 words) * Additional outline if needed * Presenter/organizer biography * Links to the presenter/organizer web page or the tutorial page (optional) * The proposal should not exceed two pages in 1.5 space, Times 12 point font. The tutorial format (preliminary) is 1 hour and 45 minutes with a 10-minute break. Researchers interested in organizing workshops are invited to submit a formal proposal. For further details, please refer to http://www.ijcnn.org/call-for-tutorials. Any questions regarding this proposal can be asked to the Tutorials Chair: Asim Roy, Arizona State University, USA. E-mail: ASIM.ROY at asu.edu ##################Topics and Areas of Interest################## This conference solicits papers addressing original works in topics and areas of interest including, but are not limited to: NEURAL NETWORK MODELS * Feedforward neural networks * Recurrent neural networks * Self-organizing maps * Radial basis function networks * Attractor neural networks and associative memory * Modular networks * Fuzzy neural networks * Spiking neural networks * Reservoir networks (echo-state networks, liquid-state machines, etc.) * Large-scale neural networks * Other topics in artificial neural networks MACHINE LEARNING * Supervised learning * Unsupervised learning and clustering, (including PCA, and ICA) * Reinforcement learning * Probabilistic and information-theoretic methods * Support vector machines and kernel methods * EM algorithms * Mixture models, ensemble learning, and other meta-learning or committee algorithms * Bayesian, belief, causal, and semantic networks * Statistical and pattern recognition algorithms * Visualization of data * Feature selection, extraction, and aggregation * Evolutionary learning * Hybrid learning methods * Computational power of neural networks * Deep learning * Other topics in machine learning NEURODYNAMICS * Dynamical models of spiking neurons * Synchronization and temporal correlation in neural networks * Dynamics of neural systems * Chaotic neural networks * Dynamics of analog networks * Neural oscillators and oscillator networks * Dynamics of attractor networks * Other topics in neurodynamics COMPUTATIONAL NEUROSCIENCE * Connectomics * Models of large-scale networks in the nervous system * Models of neurons and local circuits * Models of synaptic learning and synaptic dynamics * Models of neuromodulation * Brain imaging * Analysis of neurophysiological and neuroanatomical data * Cognitive neuroscience * Models of neural development * Models of neurochemical processes * Neuroinformatics * Other topics in computational neuroscience NEURAL MODELS OF PERCEPTION, COGNITION AND ACTION * Neurocognitive networks * Cognitive architectures * Models of conditioning, reward and behavior * Cognitive models of decision-making * Embodied cognition * Cognitive agents * Multi-agent models of group cognition * Developmental and evolutionary models of cognition * Visual system * Auditory system * Olfactory system * Other sensory systems * Attention * Learning and memory * Spatial cognition, representation and navigation * Semantic cognition and language * Neural models of symbolic processing * Reasoning and problem-solving * Working memory and cognitive control * Emotion and motivation * Motor control and action * Dynamical models of coordination and behavior * Consciousness and awareness * Models of sleep and diurnal rhythms * Mental disorders * Other topics in neural models of perception, cognition and action NEUROENGINEERING * Brain-machine interfaces * Neural prostheses * Neuromorphic hardware * Embedded neural systems * Other topics in neuroengineering BIO-INSPIRED AND BIOMORPHIC SYSTEMS * Brain-inspired cognitive architectures * Embodied robotics * Evolutionary robotics * Developmental robotics * Computational models of development * Collective intelligence * Swarms * Autonomous complex systems * Self-configuring systems * Self-healing systems * Self-aware systems * Emotional computation * Artificial life * Other topics in bio-inspired and biomorphic systems APPLICATIONS * Bioinformatics * Biomedical engineering * Data analysis and pattern recognition * Speech recognition and speech production * Robotics * Neurocontrol * Approximate dynamic programming, adaptive critics, and Markov decision processes * Neural network approaches to optimization * Signal processing, image processing, and multi-media * Temporal data analysis, prediction, and forecasting; time series analysis * Communications and computer networks * Data mining and knowledge discovery * Power system applications * Financial engineering applications * Applications in multi-agent systems and social computing * Manufacturing and industrial applications * Expert systems * Clinical applications * Big data applications * Smart grid applications * Other applications CROSS-DISCIPLINARY TOPICS * Hybrid intelligent systems * Swarm intelligence * Sensor networks * Quantum computation * Computational biology * Molecular and DNA computation * Computation in tissues and cells * Artificial immune systems * Other cross-disciplinary topics ################## Organizing Committee ###################### The full organizing committee can be found at: http://www.ijcnn.org/organizing-committee General Chair * Yoonsuck Choe, Texas A and M University, USA Program Chair * Christina Jayne, Robert Gordon University, UK Technical Co-Chairs * Irwin King, The Chinese University of Hong Kong, China * Barbara Hammer, University of Bielefeld, Germany ##################Sponsoring Organizations################## * INNS - International Neural Network Society * IEEE - Computational Intelligence Society * BSCS - Budapest Semester in Cognitive Science -------------- next part -------------- An HTML attachment was scrubbed... URL: From tarek.besold at googlemail.com Fri Oct 7 06:10:26 2016 From: tarek.besold at googlemail.com (Tarek R. Besold) Date: Fri, 7 Oct 2016 12:10:26 +0200 Subject: Connectionists: EXTENDED DEADLINE: Cognitive Computation @ NIPS 2016 - new submission deadline: Friday, October 14, 2016 Message-ID: **************************************************** Cognitive Computation: Integrating Neural and Symbolic Approaches (CoCo @ NIPS 2016) **************************************************** Workshop at NIPS 2016, Barcelona, Spain December 09, 2016 == EXTENDED SUBMISSION DEADLINE == The submission deadline for CoCo @ NIPS 2016 has been extended to Friday, October 14, 2016! == WORKSHOP WEBPAGE == http://www.neural-symbolic.org/CoCo2016/ == KEYNOTE SPEAKERS == Barbara Hammer, Bielefed University Pascal Hitzler, Wright State University Risto Miikkulainen, University of Texas at Austin & Sentient Technologies, Inc. Dan Roth, University of Illinois at Urbana-Champaign Kristina Toutanova, Microsoft Research == PANELISTS == Yoshua Bengio, University of Montreal Marco Gori, University of Siena Alessio Lomuscio, Imperial College London Gary Marcus, New York University & Geometric Intelligence, Inc. == MISSION STATEMENT == While early work on knowledge representation and inference was primarily symbolic, the corresponding approaches subsequently fell out of favor, and were largely supplanted by connectionist methods. In this workshop, we will work to close the gap between the two paradigms, and aim to formulate a new unified approach that is inspired by our current understanding of human cognitive processing. This is important to help improve our understanding of Neural Information Processing and build better Machine Learning systems, including the integration of learning and reasoning in dynamic knowledge-bases, and reuse of knowledge learned in one application domain in analogous domains. The workshop brings together established leaders and promising young scientists in the fields of neural computation, logic and artificial intelligence, knowledge representation, natural language understanding, machine learning, cognitive science and computational neuroscience. Invited lectures by senior researchers will be complemented with presentations based on contributed papers reporting recent work (following an open call for papers) and a poster session, giving ample opportunity for participants to interact and discuss the complementary perspectives and emerging approaches. The workshop targets a single broad theme of general interest to the vast majority of the NIPS community, namely translations between connectionist models and symbolic knowledge representation and reasoning for the purpose of achieving an effective integration of neural learning and cognitive reasoning, called neural-symbolic computing. The study of neural-symbolic computing is now an established topic of wider interest to NIPS with topics that are relevant to almost everyone studying neural information processing. == KEYWORDS == The following list gives some (but by far not all) relevant keywords for the CoCo @ NIPS 2016 workshop: - neural-symbolic computing; - language processing and reasoning; - cognitive agents; - multimodal learning; - deep networks; - knowledge extraction; - symbol manipulation; - variable binding; - memory-based networks; - dynamic knowledge-bases; - integration of learning and reasoning; - explainable AI. == CALL FOR PAPERS == We invite submission of papers dealing with topics related to the research questions discussed in the workshop. The reported work can range from theoretical/foundational research to reports on applications and/or implemented systems. We explicitly also encourage the submission of more controversial papers which can serve as basis for open discussions during the event. Possible topics of interest include but are (by far!) not limited to: - 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 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. - Approaches/techniques making AI and/or Machine Learning systems/algorithms better explainable or increasing human comprehensibility. = Submission instructions = - Submissions have to be made via EasyChair ( https://easychair.org/conferences/?conf=coconips2016) before the paper submission deadline indicated below. - Submissions are limited to at most eight pages, an additional ninth page containing only cited references is allowed. Still, also shorter papers are expressly welcomed. - Submissions have to use the NIPS 2016 submission format (see http://nips.cc/Conferences/2016/PaperInformation/StyleFiles). - Reviewing will be single-blind, i.e., you are free to indicate your name etc. on the paper. (Still, this is not an obligation.) Please note that at least one author of each accepted paper must register for the event and be available to present the paper at the workshop. =Publication= Accepted papers will be published in official workshop proceedings submitted to CEUR-WS.org. Authors of selected papers will be invited to submit a revised and extended version of their papers to a journal special issue after the workshop. == IMPORTANT DATES == - Deadline for paper submission (EXTENDED): October 14, 2016 - Notification of paper acceptance: October 30, 2016 - Camera-ready paper due: November 14, 2016 - Workshop date: December 09 or 10, 2016 - NIPS 2015 main conference: December 5-8, 2016 == ADMISSION == The workshop is open to anybody, please register via NIPS 2016 ( http://nips.cc). == WORKSHOP ORGANIZERS == - Tarek R. Besold (University of Bremen, Germany) - Antoine Bordes (Facebook AI Research, USA) - Artur d'Avila Garcez (City University London, UK) - Greg Wayne (Google DeepMind, UK) == ADDITIONAL INFORMATION == - General questions concerning the workshop should be addressed to Tarek R. Besold at Tarek(dot)Besold(at)uni(hyphen)bremen(dot)de. - This workshop is conceptually related to the series of International Workshops on Neural-Symbolic Learning and Reasoning (NeSy). If interested, have a look at http://www.neural-symbolic.org - Please also feel free to join the neural-symbolic integration mailing list for announcements and discussions - it's a low traffic mailing list. If interested, register at http://maillists.city.ac.uk/mailman/listinfo/nesy . -------------- next part -------------- An HTML attachment was scrubbed... URL: From magdalena.seebauer at inf.ethz.ch Fri Oct 7 07:50:22 2016 From: magdalena.seebauer at inf.ethz.ch (Seebauer Magdalena) Date: Fri, 7 Oct 2016 11:50:22 +0000 Subject: Connectionists: Call for applications: PhD Fellowships at the Max Planck ETH Center for Learning Systems Message-ID: The Max Planck ETH Center for Learning Systems is a joint research center of ETH Zurich and the Max Planck Society. The Center?s mission is to pursue research in the design and analysis of learning systems, synthetic or natural. This initiative brings together more than 30 professors and senior researchers in the fields of machine learning, perception, robotics on large and small scales, as well as neuroscience. We offer PhD Fellowships at the Max Planck ETH Center for Learning Systems The Center offers a unique fellowship program, where PhD students are co-supervised by one advisor from ETH Zurich and one from the MPI for Intelligent Systems in T?bingen and Stuttgart. PhD students are expected to take advantage of the opportunities offered by both organizations and to actively seek cross-group collaborations. The Center also offers a wide range of activities like retreats, workshops, and summer schools, as well as the possibility to engage in organizing such events. This is an exciting new program and we expect admission to be highly competitive. Each PhD fellow will have a primary location (chosen based on interests and match) and is expected to spend about one year at the other location as well. Fellowships will be remunerated through employment contracts, subjected to the rules of the Max-Planck-Society and ETH Zurich, respectively. All PhD fellows will register as graduate students at ETH Zurich and - upon successful completion of their PhD project - be granted a doctoral degree by ETH Zurich. Details of this process are governed by ETH regulations and committees. We encourage applications from outstanding candidates with academic backgrounds in Mathematics, Physics, Computer Science, Engineering, Materials Science, Neuroscience and related fields, and a keen interest in doing basic research in areas like: Machine Learning and Empirical Inference of Complex Systems, Machine Intelligence, including Machine Vision and Natural Language Understanding, Perception-Action-Cycle for Autonomous Systems, Robust Model-Based Control for Intelligent Behavior, Robust Perception in Complex Environments, Design, Fabrication, and Control of Synthetic, Bio-Inspired, and Bio-Hybrid Micro/Nanoscale Robotic Systems, Data-Driven Computational Biology, or Neurotechnology and Emergent Intelligence in Nervous Systems. We seek to increase the number of women in areas where they are underrepresented and therefore explicitly encourage women to apply. Furthermore, we are committed to increasing the number of individuals with disabilities in its workforce and therefore encourage applications from such qualified individuals. For further information please contact: Dr. Magdalena Seebauer at magdalena.seebauer at inf.ethz.ch (no application documents) or visit our website http://learning-systems.org We are looking forward to receiving your online application consisting of a complete CV (incl. a list of publications, talks and awards), a short mission statement (max. 1-2 pages) outlining the research interests of the candidate, and scanned transcripts of certificates (bachelor?s degree, master?s degree, other degrees). Please arrange for 2-3 reference letters to be sent directly per email to Dr. Magdalena Seebauer. Please send your application to: ETH Zurich, Human Resources, Mrs. Nadja Lang, CH-8092 Zurich. The deadline for applications is November 15, 2016. The selection interviews will take place on January 19 and January 20, 2017 at the Max Planck Campus in T?bingen, Germany. Apply now -- Max Planck ETH Center for Learning Systems Dr. Magdalena Seebauer Scientific Coordination CAB F 42.1 Universit?tsstrasse 6 8092 Zurich Switzerland -------------- next part -------------- An HTML attachment was scrubbed... URL: From antonior at ffclrp.usp.br Thu Oct 6 11:46:34 2016 From: antonior at ffclrp.usp.br (Antonio C. Roque) Date: Thu, 6 Oct 2016 12:46:34 -0300 Subject: Connectionists: PhD positions on stochastic modeling of neuronal biological data at University of Sao Paulo Brazil Message-ID: The doctoral program in Statistics (Statistics and Probability) of the Institute of Mathematics and Statistics, University of S?o Paulo, Brazil, has 3 fellowships for a full time PhD student without master's degree. These are full fellowships for a period of 48 months, starting February 2017. These positions are focused on research in probability theory and inference in stochastic processes with emphasis on stochastic modeling of neuronal biological data. The student will be part of the research group: The Research, Innovation and Dissemination Center for Neuromathematics, funded by FAPESP (S?o Paulo Research Foundation). See: http://neuromat.numec.prp.usp.br/content/who-we-are) The doctoral program in Statistics (Statistics and Probability) of Universidade de S?o Paulo-Brazil is well known for its innovative research in statistics and probability, besides its large experience with PhD advising. More than 300 PhD former students have successfully finished their projects in our doctoral program and are now leading research and applications in Statistics and Probability in several universities of Latin American countries. We invite you to visit our page: http://www.ime.usp.br/en/statistics/graduate Those interested should contact Ms. Regiane Guimar?es at secccpmae at ime.usp.br They should fill the Application Form, indicating interest in the fellowship FAPESP/Neuromat (http://www.ime.usp.br/mae/pos/edital). We will need also: - Academic transcripts of your previous studies; - Updated Curriculum Vitae; - An essay (maximum of five pages) reporting your academic experience, research experience, publications, unpublished results and a small scientific project; - At least 2 recommendation letters. Those should be mailed by the recommenders directly to secccpmae at ime.usp.br Remark: Candidates approved on either round will be requested to expand their five-page research plan to full four-year proposals. For the implementation of the fellowships, those proposals, together with all the application material received, will be submitted to FAPESP for final approval. Deadline: November 4th 2016 -- Dr. Antonio C. Roque Professor Associado Departamento de Fisica FFCLRP, Universidade de Sao Paulo 14040-901 Ribeirao Preto-SP Brazil - Brasil E-mails: antonior at ffclrp.usp.br aroquesilva at gmail.com URL: www.sisne.org Tels: +55 16 3315-3768 (sala/office); +55 16 3315-3859 (lab) FAX: +55 16 3315-4887 -------------- next part -------------- An HTML attachment was scrubbed... URL: From edragut at temple.edu Thu Oct 6 11:50:59 2016 From: edragut at temple.edu (Eduard Dragut) Date: Thu, 6 Oct 2016 11:50:59 -0400 Subject: Connectionists: Job posting: Temple University: Data Science Faculty Positions Message-ID: Data Science Faculty Positions (Assistant/Associate/Full Professor) Department of Computer and Information Sciences Temple University The Department of Computer and Information Sciences (CIS) invites applications for multiple tenured and tenure track data science faculty. We are interested in data scientists who are developing methods and systems to collect, process, and analyze large amounts of data, as well as techniques to extract and visualize knowledge for various application domains. Successful candidates will contribute to the newly introduced undergraduate and graduate programs in data science and join world-class investigators in the Center for Data Analytics and Biomedical Informatics, Center for Networked Computing, Institute for Computational Molecular Sciences, and Institute for Genomics and Evolutionary Medicine, co-located with the CIS Department in a state-of-the-art $140M building. Applicants for the Assistant Professor position should have the potential to excel in teaching and develop a significant, extramurally-funded research program. Applicants for Associate or Full Professor positions are expected to have demonstrated excellence in teaching and an outstanding track record of research and funding. Recently celebrating its 50th year anniversary, CIS is one of the oldest computer science departments in the country and is experiencing growth both in research and academic programs. Over the last seven years, the CIS annual research revenue has grown more than 300%, and both the undergraduate and graduate student enrolment has doubled. CIS is among the top 60 computer science departments in the country based on the ARWU Shanghai ranking. CIS offers a highly competitive salary and start-up package, low teaching load, and institutional support for an active doctoral program. Temple University is a Carnegie R1 (highest research activity) institution that serves more than 39,000 students and places among the top 55 public schools by the U.S. News ranking. It is the 26th largest university and 6th largest provider of graduate school education in the United States. Located in the heart of Philadelphia (the 5th largest city in U.S. known for its arts, culture and history, and affordable living), Temple University is in close proximity to many outstanding academic institutions, research centers, and industry partners in data science areas, including information technology, health care, biotechnology, and finance. Applications should be submitted electronically at https://academicjobsonline.org/ajo/jobs/8172. Submitted materials should include a curriculum vitae, description of research accomplishments, research statement, teaching statement, and three letters of recommendation (names of referees are sufficient for senior-level candidates). Review of candidates will begin immediately and continue until the positions are filled. Applicants are encouraged to meet the deadline for priority consideration. For more information, send an email to zoran.obradovic at temple.edu with "TT Position" as the subject. Temple University is an affirmative action/equal opportunity employer with a strong commitment to the quality of faculty life. -------------- next part -------------- An HTML attachment was scrubbed... URL: From cristian.rodriguezrivero at gmail.com Thu Oct 6 10:37:09 2016 From: cristian.rodriguezrivero at gmail.com (Cristian Rodriguez Rivero) Date: Thu, 6 Oct 2016 11:37:09 -0300 Subject: Connectionists: CFP - Advances in Computational Intelligence for applied Time Series Forecasting (ACIATSF) IJCNN 2017 Message-ID: Call for papers: special session on "Advances in Computational Intelligence for applied Time Series Forecasting (ACIATSF)" at IJCNN 2017 International Joint Conference on Neural Networks (IJCNN 2017). 14-19 May 2017, Anchorage, Alaska, USA - http://www.ijcnn.org/ DESCRIPTION: Over the past few decades, application of simple statistical procedures with considerable heuristic or judgmental input was the beginning of forecasting, then in the 80?s, sophisticated time series models started to be used by some of the dynamic system operators, and these approaches, were to become pioneering works in this field. Soft computing methods including support vectors regression (SVR), fuzzy inference system (FIS) and artificial neural networks (ANN) to time-series forecasting (TSF) has been growing rapidly in order to unify the field of forecasting and to bridge the gap between theory and practice, making forecasting useful and relevant for decision-making in many fields of the sciences. The purpose of this session is to hold smaller, informal meetings where experts in a particular field of forecasting can discuss forecasting problems, research, and solutions in the field of automatic control. There is generally a nominal registration fee associated with attendance. This session aims to debate in finding solutions for problems facing the field of forecasting. We wish to hear from people working in different research areas, practitioners, professionals and academicians involved in this problematic. Scope The session seeks to foster the presentation and discussion of innovative techniques, implementations and applications of different problems that are Forecasting involved, specially in real-world problems applied to control and automation. ? Time Series Analysis ? Time Series Forecasting ? Evaluation of Forecasting Methods and Approaches ? Forecasting Applications in Business, Energy and Price Demand, Hydrology and Rainfall ? Impact of Uncertainty on Decision Making ? Seasonal Adjustment ? Multivariate Time Series Modelling and Forecasting ? Marketing Forecasting ? Economic and Econometric Forecasting SUBMISSION: Prospective authors must submit their paper through the IJCNN portal following the instructions provided inhttp://www.ijcnn.org/paper-submission. Each paper will undergo a peer reviewing process for its acceptance. IMPORTANT DATES: Paper submission deadline : 15 November 2016 Notification of acceptance : 20 January 2017 Camera-ready submission: 20 February 2017 The IJCNN 2017 conference : 14-19 May 2017 SPECIAL SESSION ORGANISERS Prof. Cristian Rodriguez Rivero, Universidad Nacional de C?rdoba, Argentina, crodriguezrivero at ieee.org, IEEE CIS Argentinian Chapter. Prof. Hector Daniel Pati?o, Universidad Nacional de San Juan, Argentina, dpatino at inaut.unsj.edu.ar. Prof. Julian Antonio Pucheta, Universidad Nacional de C?rdoba, Argentina, jpucheta at unc.edu.ar . Prof. Gustavo Juarez, Universidad Nacional de Tucum?n, Argentina, juarez.gustavo at ieee.org , IEEE CIS Argentinian Chapter chair. Prof. Leonardo Franco, IEEE CIS R8, Universidad de M?laga, Espa?a, lfranco at lcc.uma.es -------------- next part -------------- An HTML attachment was scrubbed... URL: From gluck at pavlov.rutgers.edu Thu Oct 6 17:19:23 2016 From: gluck at pavlov.rutgers.edu (Mark Gluck) Date: Thu, 6 Oct 2016 17:19:23 -0400 Subject: Connectionists: Dear Learning and Memory Colleagues: Park City Winter Conference on the Neurobiology of Learning and Memory: Thursday, January 5th through Sunday, January 8th, 2017. Great SKIING and SCIENCE. References: Message-ID: <67C7B5E3-B927-4090-A359-200A6B26DDCB@pavlov.rutgers.edu> Dear Learning and Memory Colleagues, Whether you work in animal learning or human memory, the best conference of the year in this integrated area of research is the annual Park City Winter Conference on the Neurobiology of Learning and Memory, from Thursday, January 5th through Sunday, January 8th, 2017. If you ski, this is some of the best lightest powder skiing in the world and since the conference does not start until 4:30pm each day, you can get in 3 or 4 good solid days of skiing while also attending stimulating and informative conference sessions. Even if you don?t ski (and many attendees come just for the scientific interactions, even if they don?t ski) there are plenty of opportunities for cross-country skiing, winter hikes, snow-cat tours as well as exploring and shopping in historic Park City (originally a silver mining town). It is very much a bring-the-family event and many attendees come and make this a family winter vacation for skiing and more. Children welcome at the banquet and social events. There are two sessions an evening, one before dinner (at 4:30pm) and another after dinner (at 8pm). This year, I will be chairing a symposium on Friday at 4:30pm on ?SLEEP & MEMORY? with presentations by Itamar Lerner and myself (Rutgers), Jessica Payne (Notre Dame), Sara Mednick (UC Riverside), and Gina Poe (Michigan). Many other exiting symposia are offered as well. See below. There is also a ?open mic? data blitz session on the first evening for those who want to present brief bits of a talk for 5 minutes. Registration is moderately priced and the conference gets a very very good rate on hotel rooms because early January is a brief post Xmass/New Year?s week refractory period during which ski resorts are less crowded and prices lower. For more information - see links below and key information from conference web page including program below. - Mark Gluck For more information and to pre-register, see http://stark-labs.com/winterconference/meeting-logistics/ Key Info and Program Follows: Date and Location January 5-8, 2017 Park City Marriott Hotel Park City, Utah The scientific sessions are held in the late afternoon and evening, leaving the day free for recreation and informal discussions. The program information is available below. Registration and Lodging $225 for regular participants ? Payable online with a credit card or PayPal account (you don?t need an account ? just enter your CC info) or at registration on January 5 from 3-4pm in the hall outside of Ballroom 1 at the Park City Marriott Hotel. There is a reduced fee of $125 for graduate students and postdoctoral fellows. Banquet on Tuesday, January 6th. The banquet will cost $50.00 per person. The Pizza Party will be free for participants and guests. We have a block of rooms at the Marriott hotel at a discounted rate (Book your group rate for Learning & Memory 2017 Annual Winter Conference link updated to allow 1/5 ? 1/9 stays). If you plan to stay at the Marriott Hotel, they can be contacted directly at (435) 615-4547 or 1-800-228-9290. Please make your reservation by Nov 17 and request a room booked by the Neurobiology of Learning and Memory Conference for the rate of $229.00 per night. In order to avoid paying higher prices for the hotel room, please make the reservation before November 17. Furthermore, we have booked a certain set of rooms and if they are not reserved by November 30, the conference will have to pay for the rooms, resulting in higher conference registration costs in the future. Transportation Transportation from Salt Lake City International Airport to Park City (approximately 40 miles) is available in all forms: bus, limousine, cab, rental car, etc. Park City Marriott Hotel provides a courtesy shuttle bus during peak periods to the ski area and downtown Park City. The fare is free and times vary with demand. Inquire at the hotel desk for further information. Park City offers a ski shuttle service from the ski area to area hotels. The fare is free and the shuttle departs the ski area on the hour and every 20 minutes with the exception of no run at 2:00 pm. Park City Marriott Hotel also provides for discount tickets for the three ski resorts in Park City. If desired, ski rental and ski repair (e.g. waxing, tuning, and sharpening) are available at the hotel. Talks For the Data Blitz session (only), please give the title, presenter, and ppt slide (no more than one slide) to the session organizer. No animations that change the size of elements, occlude elements, etc. are allowed (i.e., you may slowly uncover bits, but that is all). Got something to share? Looking for a roomate or a ride? Want to get a group to do something fun during the day? Try the Discussion Board 2017 Program Thursday January 5, 2017 Registration 3:00 -4:00 p.m. (Just outside Prospector 1-2) Session 1: Dave Olton Data Blitz Time: 4:00 to 6:00 p.m. Location: Prospector 1-2 Organizer: Rebecca Burwell Description: If you would like to present at this session, please e-mail Rebecca Burwell at rebecca_burwell at brown.edu with the title of your presentation. Presentations are limited to 5 minutes including discussion. Presentations are strictly limited to 1 slide with a single panel. Pizza Party Time: 6:30 -8:00 p.m. Location: Atrium Session 2: Hyperactive or hypoactive? Medial Temporal Lobe Imbalance in Amnestic Mild Cognitive Impairment Time: 8:00-10:00 p.m. Location: Prospector 1-2 Organizer: Arnold Bakker (JHU) Increased hippocampal activation in the context of decreasing memory function is observed in aging and considered a characteristic feature of the early stages of Alzheimer?s disease. However, the entorhinal cortex, which serves as the primary relay for both input and output to and from the hippocampus, is the site of the earliest pathological changes including neuronal, synaptic and volume loss. This session will discuss recent evidence from animal models and human subjects for the role of medial temporal lobe dysfunction and particularly focus on the role of the entorhinal cortex in age- and disease related memory decline. Speakers: Arnold Bakker (JHU): ?Lateral entorhinal cortex hypoactivation in amnestic mild cognitive impairment? Willem Huijbers (DZNE): ?TBD? Michela Gallagher (JHU): ?Age-related medial temporal lobe network dysfunction: Contributions from animal models? Friday January 6, 2017 Session 3: Sleep and Memory Time: 4:00-6:00 p.m. Location: Prospector 1-2 Organizers: Mark Gluck (Rutgers-Newark) Over the last two decades, sleep has been repeatedly implicated in a wide array of learning and memory processes, with specific sleep stages and their corresponding neurophysiological characteristics differentially contributing to specific types of cognitive abilities. Ongoing research in both humans and animals is honing in on the precise nature of these relations and is attempting to decipher their underlying mechanisms. In our session, we will present a sample of contemporary work in the field covering a variety of methods and theories. Itamar Lerner and Mark Gluck (Rutgers-Newark) will present a recently developed computational model, based on studies of compressed memory replay during Slow-Wave-Sleep (SWS), to explain how sleep facilitates insight learning through a ?temporal scaffolding? mechanism. Jessica Payne (Notre Dame) will describe the unique interaction between stress and sleep and how it influences emotional memory. Sara Mednick (UC Riverside) will speak about the role of autonomic changes during sleep and their impact on memory consolidation. Lastly, Gina Poe (U. Michigan) will show how the specific neurochemical and electrophysiological features of Rapid-Eye-Movement (REM) sleep alter hippocampal-neocortical networks, based on rodent studies Speakers: Itamar Lerner & Mark Gluck (Rutgers U Newark): ?Effects of sleep on insight learning is explained by a ?temporal scaffolding? mechanism based on compressed memory-replay? Jessica Payne (U Notre Dame): ? Sleep-stress interactions in emotional memory consolidation? Sara C. Mednick (UC Riverside): ?What is the role of the autonomic nervous system during sleep-dependent memory consolidation? Gina Poe (U Michigan): ?How REM sleep neurochemistry and electrophysiology alters hippocampal and neocortical memory networks? Dinner Check out the new eateries in town. 6:00-8:00 p.m. Session 4: Systems consolidation and memory transformation ? From neurons to networks Time: 8:00-10:00 p.m. Location: Prospector 1-2 Organizer: Melanie Sekeres (Baylor U) and Paul Frankland (U Toronto) Memory consolidation is a dynamic process occurring over the lifetime of a memory, yet the underlying mechanisms are not well understood. The hippocampus is considered to be a critical structure for the acquisition, initial storage, and retrieval of a memory, but there is considerable debate over the continuing role of the hippocampus in representing a memory as it ages and loses precision. Do the same neurons involved in the initial acquisition of a memory continue to support its retrieval as the memory transforms over time? What are the broader networks beyond the hippocampus and prefrontal cortex that become increasingly engaged as a memory ages and forms distributed traces in the cortex? In this session, we propose to explore the contribution of neuronal ensembles involved in memory acquisition and retrieval, as well as broader memory networks in rodents and humans. We will consider the degree to which evidence related to the mechanistic basis of memory consolidation in rodents applies to complex human memory. Speakers: Paul Frankland (U Toronto): ?TBD? Melanie Sekeres (Baylor U): ?TBD? Brian Wiltgen (UC Davis): ?TBD? Kiriana Cowansage (UCSD): ?TBD? Saturday January 7, 2017 Session 5: The Role of the Medial Temporal Lobe in Sensory Discrimination and the Relationship with Memory Time: 4:00-6:00 p.m. Location: Prospector 1-2 Organizer: Sara Burke (U Florida) The extent to which the hippocampus and rhinal cortical areas participate in high-level sensory perception is actively debated. Recent data from studies in human subjects as well as animal models have highlighted that working memory may support discrimination abilities and that perceptual difficulty modulates memory performance. Speakers in this session will highlight current evidence that sensory discrimination across modalities is tightly related to memory performance. Discussion will focus on the potential mechanisms that link these cognitive processes and the extent to which perception and memory can be parsed into distinct cognitive domains. Speakers: Jennifer Bizon (U Florida): ?Using olfactory discrimination to understand mechanisms of age-related cognitive decline? Andrew Maurer (U Florida): ?Lateral entorhinal cortical activation during exploration predicts object discrimination performance? Michael Yassa (UC Irvine): ?Extrahippocampal contributions to mnemonic discrimination and implications for age-related cognitive decline? Lee Ryan (U Arizona): ?Hippocampal-perirhinal interactions in aging? Dinner Check out the new eateries in town. 6:00-8:00 p.m. Session 6: Critical role of the nucleus reuniens in hippocampus and medial prefrontal cortex dependent memory systems Time: 8:00-10:00 p.m. Location: Prospector 1-2 Organizer: Timothy A. Allen (FIU) and Aaron Mattfeld (FIU) The nucleus reuniens of the ventral midline thalamus (RE) has been the focus of several recent studies which collectively implicate RE as critical for memory. Anatomically, the nucleus reuniens bi-directionally connects the medial prefrontal cortex (mPFC) and hippocampus (HC) in rodents and primates placing it at a critical nexus for modulating memory. In this session the speakers will (1) discuss the anatomical basis for understanding the role of RE in memory, (2) provide behavioral evidence that RE is critical to memory, (3) describe neural representations in and dependent on RE, and (4) relate these findings in a larger framework of an HC-RE-mPFC mnemonic system. Speakers: Robert P. Vertes (FAU): ?Anatomical connections of nucleus reuniens with the hippocampus and medial prefrontal cortex and their functional significance? Timothy A. Allen (FIU): ?The role of the nucleus reuniens in the temporal organization of memories? Amy Griffin (UD): ?The nucleus reuniens orchestrates hippocampal-prefrontal synchrony during working memory? Aaron Mattfeld (FIU): ?Identification and function of nucleus reuniens in the humans? Sunday January 8, 2017 Session 7: Learning and Memory in Neuropsychiatric Disorders Time: 4:00-6:00 p.m. Location: Prospector 1-2 Organizers: Pam Kennedy (UCLA) A major impediment in the treatment of substance use disorders (SUDs) and anxiety/depression is the chronic relapsing nature of the diseases. Accumulating evidence suggests a critical role for altered function in brain circuits mediating learning and memory processes in the maintenance of maladaptive behaviors associated with these disorders. In this session we will present data from animal models describing molecular and circuit-level adaptations that may contribute to the persistence of SUDs and anxiety/depression. Speakers: Pamela Kennedy (UCLA): Memory system bias following withdrawal from drugs of abuse A.J. Robison (MSU): Projection-specific hippocampal gene editing in emotional learning Courtney Miller (Scripps, FL): Nonmuscle myosin IIB as a therapeutic target for the prevention of relapse to methamphetamine use Business Meeting: Time: 6:00-6:30 pm Location: Prospector 1-2 Banquet Time: 7:30-11:00 pm Location: Prospector 1-2 Special Event: Returning members of the original organizers of this meeting (Ray Kesner, James McGaugh, Larry Squire and Aryehy Routtenberg) will discuss what they see as the future of learning and memory research. Social Activities Dinners January 5rd ? Pizza Party ? For registrants or guests, no extra cost. January 6th ? Dinner (on your own) January 7th ? Dinner (on your own) January 8th ? Banquet ? $40 for registrants and guests Cash Bar (Timbers) Friday, Saturday, Sunday evenings 10:00 pm-12:00 am For Families: Gorgoza Park (http://www.gorgoza.com ): Tubing, mini-snowmobiles, learn to ski/ride, etc. Tanger Outlets (http://www.tangeroutlet.com/parkcity ): Shopping Ice skating (http://www.resortcentericerink.com ) Alpine Coaster @ Park City (http://www.parkcitymountain.com/summer/alpine-coaster.aspx ) Utah Olympic Park (https://www.visitparkcity.com/visitors/resorts/utah-olympic-park/ ): ski jump, bobsled, ropes course ___________________________________ Dr. Mark A. Gluck, Professor Center for Molecular & Behavioral Neuroscience Rutgers University ? Newark 197 University Ave. Newark, New Jersey 07102 Web: http://www.gluck.edu Email: gluck at pavlov.rutgers.edu Ph: ( 973) 353-3298 -------------- next part -------------- An HTML attachment was scrubbed... URL: From dhallabhinav at gmail.com Thu Oct 6 14:00:35 2016 From: dhallabhinav at gmail.com (abhinav dhall) Date: Thu, 6 Oct 2016 14:00:35 -0400 Subject: Connectionists: [CFP] IEEE ISBA 2017 submission deadline extension Message-ID: [Apologies for cross-postings] New submission deadline - October 31 2016 ----------------------------------------------- IEEE International Conference on Identity, Security and Behavior Analysis (ISBA 2017) Location: New Delhi, India Dates: February 22-24 2017 http://ieee-biometrics.org/isba2017/ ----------------------------------------------- The third ISBA is a unique conference series initiated by the IEEE Biometrics and will be held in New Delhi, India. This conference is intended to meet the emerging need for a winter meeting, especially for the Asian participants where the introduction of large scale biometrics programs have attracted significant increase in research and development efforts. It will be a forum that brings together experts in biometrics, security, and human behavior to consider research issues and solutions that are robust, comprehensive, and broader than currently considered in each of these individual research areas. This conference serves to provide a new form for such broad areas defining human side of security and user behavior as well as social influence in the biometrics security. Topics of interest include, but are not limited to: ? Anti-Spoofing, Behavioral Biometrics, Biometric System Evaluation, Biometrics in Law Enforcement, Cybercrime ? De-identification, Detection and Tracking, Device Identification, Digital Forensics ? Human Behavior Analysis, Human Activity Understanding, Identity Management, Information Security, Person Re-identification ? Performance Evaluation, Privacy-preserving Computing, Predictive Analytics, Single and Multi-modal Biometrics ? Social Biometrics, Social and Criminal Network Inference, Surveillance Identification, Template Protection and Data Privacy ? Usability and Performance, User-centric Biometric Security Submitted papers may not be accepted or under review elsewhere. Submissions may be up to eight pages in conference format (double blind reviewing). Papers accepted and presented at ISBA2017 will be published in conference proceedings and made available in IEEE Xplore library. Important dates Submission deadline: October 31, 2016 Decision to authors: December 10, 2016 Camera ready submission: December 20, 2016 Conference: February 22-24, 2017 General Chair Rama Chellappa (University of Maryland, USA) General Co-chairs Ajay Kumar (PolyU, Hongkong) Richa Singh (IIIT-Delhi, India) Program Co-chairs M. Ehsan Hoque (University of Rochester, USA) Nitesh Saxena (University of Alabama at Birmingham, USA) Vishal M. Patel (Rutgers University, USA) Mayank Vatsa (IIIT-Delhi, India) Publication Chair Soma Biswas (Indian Institute of Science, India) Finance Chair Angshul Majumdar (IIIT-D, India) Publicity Chair Abhinav Dhall (University of Waterloo, Canada) Industry Liaison Sameer Shah (HCL, India) http://ieee-biometrics.org/isba2017/ -- Abhinav Dhall, PhD (ANU) Postdoctoral Research Fellow, University of Waterloo -------------- next part -------------- An HTML attachment was scrubbed... URL: From M.Gillies at gold.ac.uk Fri Oct 7 05:48:25 2016 From: M.Gillies at gold.ac.uk (Marco Gillies) Date: Fri, 7 Oct 2016 09:48:25 +0000 Subject: Connectionists: Movement and Computing (MOCO) 2017 Call for Papers Message-ID: Call for Papers MOCO 2017 ??????????????????????????????????????? International Conference on Movement and Computing (MOCO17) > Intersecting Art, Meaning, Cognition, Technology ??????????????????????????????????????? 28-30th June, London UK Goldsmiths University of London http://moco17.movementcomputing.org We would like to invite submissions for paper presentations, performances, workshops and more to the 4th International Conference on Movement and Computing (MOCO) which is to be held in London. MOCO is an interdisciplinary conference that explores the use of computational technology to support and understand human movement practice (e.g. computational analysis) as well as movement as a means of interacting with computers (e.g. movement interfaces). This requires a wide range of computational tasks including modeling, representation, segmentation, recognition, classification, or generation of movement information but also an interdisciplinary understanding of movement that ranges from biomechanics to embodied cognition and the phenomenology of bodily experience. We therefore invite submissions from a wide range of disciplines including (but not limited to): Human-Computer Interaction, Psychology, Dance, Artificial Intelligence, Neuroscience, Sports Science, Machine Learning, Cognitive Science, Visual Arts, Robotics, Philosophy, Anthropology, Music, Affective Computing, Games, Healthcare and Animation. MOCO is open to a wide range of ways of presenting your work. As well as papers for oral and poster presentations, we invite submission of a wide range of practice work such as demos, performances, games, artistic works and movement workshops (in which participants take part in a guided movement activity). We encourage submitters to be creative in proposals for practice sessions and are open to novel formats. ???????????? Suggested Topics ???????????? ? Expressive movement-based interaction ? Movement analysis and analytics ? Machine learning for movement ? Movement representation ? Somatic practice and design ? Modeling movement qualities and expressive movement ? Mechatronics and creative robotics ? Design for movement in digital art ? Gesture Interaction ? Movement generation ? Movement and sound interaction ? Movement computation in ergonomics, sports, and health ? Sensori-motor learning with audio/visual feedback ? Embodied cognition and movement ? Visualizing and sonifying movement ? Modeling kinaesthetic empathy ? Embodied and whole body interaction ? Expressive movement analysis and synthesis ? Design for movement in digital art ? Semantic models for movement representation ? Movement Notation Systems (e.g. Laban or Eshkol-Wachman) and computation ? Dance and technology ? Biosensing, biocontrol and movement ? Movement expression in avatar, artificial agents, virtual humans or robots. ? Music and movement ? Philosophical perspectives and reflection on movement and computing ?????????? Submission ?????????? The conference is an opportunity to present a research or study or details of collaborative work. Participants will have the opportunity to offer a presentation of the results of their research on one of the themes of the symposium and to interact with their scientific/ artistic peers, in a friendly and constructive environment. We encourages submission of a wide range of formats, the submission categories are: Long paper with oral presentation (8 pages maximum) Short paper with oral presentation (4 pages maximum) Extended abstract with poster presentation (6 pages maximum in the extended abstract format) Extended abstract for practice work with presentation format to be suggested by the author for example demonstration, performance, art work, movement workshop, game or other practice presentation (2 pages maximum + Demo proposal form). - please note that we are an academic conference with a low fee which means we cannot pay for commissioned performances and art work. Also, we cannot guarantee facilities for all possible sessions, so please give full details of your needs in the proposal form so we can judge whether it is possible. Doctoral papers with oral presentation at a doctoral symposium and poster (4 pages maximum) All submissions should be in pdf format and should use the ACM proceedings format: http://www.acm.org/publications/proceedings-template It is possible for participating authors to submit a demonstration proposal in addition to their regular paper submission by completing the Demo proposal form and sending it along with their submission. Together with the demo proposal form, authors have to provide a link to a video about their work. The demo proposal form is mandatory for all demo submissions and must include details about technical set-up and space requirements. Online submission: All submissions must be made through EasyChair https://easychair.org/conferences/?conf=moco2017 All submissions must be anonymous and will be peer-reviewed. The MOCO proceedings will be indexed and published in the ACM digital library. ???????????? Important Dates ???????????? Submission deadline: 23 January 2017 Notification: 23 March 2017 Camera ready papers: 30 April 2017 ???????????? Contact ???????????? If you have any questions please contact us on moco2017 at easychair.org ???????????? Committee ???????????? Conference Chair Marco Gillies, Goldsmiths Organising Committee Kirk Woolford, University of Surrey Sarah Whatley, Coventry University Frederic Fol Leymarie, Goldsmiths Phoenix Perry, Goldsmiths Simon Katan, Goldsmiths Perla Maiolino, Goldsmiths Local organisers Steph Horak, Goldsmiths Nicky Donald, Goldsmiths Phoenix Fry, Goldsmiths Steering Committee Fr?d?ric Bevilacqua, IRCAM Sarah Fdili Alaoui, LRI-Universit? Paris-Sud 11 Jules Fran?oise, Simon Fraser University Philippe Pasquier, Simon Fraser University Thecla Schiphorst, Simon Fraser University -------------- next part -------------- An HTML attachment was scrubbed... URL: From geri at robot-learning.de Fri Oct 7 05:47:23 2016 From: geri at robot-learning.de (Gerhard Neumann) Date: Fri, 7 Oct 2016 10:47:23 +0100 Subject: Connectionists: [jobs] Lecturer / Senior Lecturer Positions in Machine Learning and Robotics (Learning for Autonomous Systems), University of Lincoln, UK Message-ID: *LECTURER/SENIOR LECTURER in Machine Learning and Robotics (Learning for Autonomous Systems)* *Location: University of Lincoln, UK* College of Science - School of Computer Science *Position: *Lecturer or Senior Lecturer *Salary: * From ?32,004 per annum *Please note that these are fully tenured (permanent) faculty positions. The post of Lecturer in UK is equivalent to Assistant Professor in US. We are hoping to recruit up to THREE persons at either lecturer or senior lecturer level.* *Closing Date: * Thursday 03 November 2016 *Interview Date: * Friday 18 November 2016 *Reference: *COS277 We seek to appoint two permanent Lecturers or Senior Lecturers with established research expertise in Learning for Autonomous Systems or a related field. You should hold a PhD or be near to completion, and should be able to demonstrate a good track record in these research fields. Once in post, you are expected to develop your own research portfolio, acquire external funding, publish in the highest quality journals and conferences, contribute to real-world applications with positive impacts on the wider society and economy, and to conduct, direct and supervise research in line with the targets set by the School. You will be a key part of the Lincoln Centre for Autonomous Systems (L-CAS),which specialises in the integration of perception, learning, decision-making, control and interaction capabilities in autonomous systems and the application of this research in fields such as personal robotics, agri-food, healthcare, security, and intelligent transportation. The L-CAS is one of the fastest growing robotics groups in the UK. We provide a highly-dynamic inter-disciplinary research environment with a broad range of collaboration opportunities and a large variety of robots to work with. We are looking to recruit new people ? from early careers researchers to senior professionals - who share our ambition to become one of the world?s leading robotics labs. Your research interests will form an integral part of a new research focus on Learning for Autonomous Systems, working together with the newly appointed Professor of Computational Learning for Autonomous Systems. As a successful candidate, your research areas should be focused on applying machine learning techniques, such as (but not limited to)reinforcement learning, learning from demonstration, deep learning or Bayesian methods, to robotics and autonomous systems with applications such as (but not limited to) dexterous manipulation, humanoid robots, human-robot collaboration, swarm robotics or autonomous driving. You will be expected to take an active part in the activities of the School of Computer Science, to contribute to its teaching activity at undergraduate and postgraduate levels, and to demonstrate a commitment to maintaining the University?s high standards in teaching and learning. The School of Computer Science at the University of Lincoln has scored highly in the recent independent performance measures of UK university computing departments; in the top 20% for student satisfaction (NSS 2015), the top 50 for research excellence in its publications (REF 2014) and approximately 10% above the sector average for graduate employability (DLHE 2014). In the most recently published subject league tables (Sunday Times 2015; Complete University Guide 2016) the School is the highest ranked ?new? (post 1992) computer science department in the country. The University of Lincoln is a forward-thinking, ambitious institution and you will be working in the heart of a thriving, beautiful, safe and friendly city. The School provides a stimulating environment for academic research, and is located on the picturesque waterfront campus in the historic and vibrant city of Lincoln. The University has just announced a ?130M investment programme, a significant part of which is being invested in new, purpose-built facilities for the School of Computer Science. If you would like to know more about this opportunity, please contact either Prof Gerhard Neumann (Professor of Computational Learning for Autonomous Systems, geri at robot-learning.de), Prof Tom Duckett (Director of L-CAS, tduckett at lincoln.ac.uk) or Dr Kevin Jacques (Acting Head of School, kjacques at lincoln.ac.uk). As a member of the Athena SWAN Charter we are committed to advancing gender equality in STEM, therefore female applicants are strongly encouraged to apply. To apply online, please visit our website at https://jobs.lincoln.ac.uk/vacancy.aspx?ref=COS277 If you have any queries please email jobs at lincoln.ac.uk or telephone 01522 886 775. Please quote the job reference number and title in all correspondence. -- --------------------------------------------- Gerhard Neumann Chair of Computational Learning for Autonomous Systems (starting Nov. 2016) University of Lincoln -------------- next part -------------- An HTML attachment was scrubbed... URL: From v.steuber at herts.ac.uk Fri Oct 7 15:42:29 2016 From: v.steuber at herts.ac.uk (Steuber, Volker) Date: Fri, 7 Oct 2016 19:42:29 +0000 Subject: Connectionists: Lecturer/Senior Lecturer in Computer Science (Machine Learning / Biocomputation) (Closing Date 21 October) Message-ID: <1475869344617.95858@herts.ac.uk> Lecturer/Senior Lecturer in Computer Science (Machine Learning / Biocomputation) School of Computer Science University of Hertfordshire, UK Salary ?32,004 to ?48,327 per annum depending on qualifications and experience Full time position working 37 hours per week (1.0 FTE) Closing date 21 October 2016 Applications are invited for a Lecturer or Senior Lecturer in the School of Computer Science, 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 a computer scientist with background in machine learning or data science related to biocomputation (including computational neuroscience). By Data Science we broadly mean the extraction of meaning from large quantities of data. The successful candidate will also have 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 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 as outlined above. Applicants 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. Applications should be made through http://www.herts.ac.uk/contact-us/jobs-and-vacancies/academic-vacancies (reference 014050). Informal enquiries may be addressed to Dr Volker Steuber (Head of the Biocomputation Research Group, v.steuber at herts.ac.uk) or Professor William Clocksin (Dean of School, w.clocksin at herts.ac.uk). Please note that applications sent directly to these email addresses will not be accepted. We are committed to providing a supportive environment. The university also provides an onsite childcare facility and child-centred holiday clubs. 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. ? -------------- next part -------------- An HTML attachment was scrubbed... URL: From sml at essex.ac.uk Fri Oct 7 12:20:03 2016 From: sml at essex.ac.uk (Lucas, Simon M) Date: Fri, 7 Oct 2016 16:20:03 +0000 Subject: Connectionists: EPSRC Funded PhD Studentships in AI and Games Message-ID: EPSRC Centre for Doctoral Training in Intelligent Games and Game Intelligence (IGGI) 11 fully-funded studentships to start September 2017 Covers fees at Home/EU rate and a stipend for four years IGGI is an exciting opportunity for you to undertake a four-year PhD in Intelligent Games and Game Intelligence, working with top games companies and world-leading academics in games research. We currently have 34 students conducting research in areas such as: * Artificial Intelligence (AI) to create interesting, fun, believable game agents, * emotion and immersion in games, * interaction design for games, * Machine Learning (ML) to understand player psychology * using games for learning and wellbeing, * game audio, graphics and animation * game design, citizen science and gamification, * procedural content generation. IGGI is a collaboration between the University of York, the University of Essex and Goldsmiths College, University of London. The programme trains PhD researchers who will become the next generation of leaders in research, design, development and entrepreneurship in digital games. We have 11 studentships available for 2017/18 entry, which will fund full fees (for UK/EU students) plus a tax-free living stipend, for a 4-year PhD programme. Could you join our large and growing group of games researchers in the world's largest games research programme? Why IGGI? IGGI gives you the opportunity to work with our industry partners, allowing you the possibility to contribute directly to the future of games. You will have the opportunity to undertake industrial placements during the IGGI programme, giving you first-hand experience of the games industry. These placements will contribute to your research, ensuring its relevance, as well as giving you the skills needed to succeed in a career in the games industry or games research. Our students have completed placements with partner companies such as Sony Interactive Entertainment Europe, Bossa Studios, Google, MediaMolecule, SplashDamage, and MindArk. Other partners include organisations such as Creative Assembly, Rebellion, UKIE, the Digital Catapult, BT and over 50 games companies and organisations which use games in creative ways (see http://www.iggi.org.uk/industry-partners/) Your research work with partners like these will advance the creation of more fun and profitable games that exploit research advances, and help to increase the use of games as a tool for scientific research and societal good. You'll also learn through teamwork and inspiring events such as: * the IGGI Game Jam, a 48 hour Game Development Challenge to enhance your skills in game design and development, and teamwork. This is part of the Global Game Jam, so you will be jamming alongside teams from all over the world; * the IGGI Symposium, a student-led event that showcases student research alongside industry and academic speakers; * industry days, where practitioners from industry share insights into their business and present real-world problems for teams to solve. You'll receive focused skills training from a range of academic research leaders, covering topics including: Games Development, Games Design and Research Skills as well as a range of optional topics in areas such as AI, HCI, graphics, audio and design. Apply for IGGI We have 11 fully-funded studentships to award to outstanding students that cover fees and an annual tax-free stipend of ?14,296 (or ?15,726 with London weighting if studying at Goldsmiths) for four years (at 2016/17 rates - this is likely to increase slightly for September 2017 starters). An IGGI application should consist of a CV, a covering letter explaining your motivation and suitability for the IGGI programme, and a statement of your planned research and proposed supervisor(s). You will also be asked for evidence of your programming skills during the application process, either through your qualifications, previous employment or examples of games you have developed. You can contact potential supervisors directly (see http://www.iggi.org.uk/supervisors/ for a list), or contact us at the email address below and we can help you to choose a principal supervisor from York, Essex or Goldsmiths based on your interests and background. We expect substantial competition for IGGI studentships and we encourage good students to submit applications as early as possible. The deadline for applications is midnight (GMT) on Friday 27th January 2017. Interviews will take place at Goldsmiths, University of London on Friday 10th March 2017. Your CV, covering letter, supervisor information and statement of planned research should be emailed to apply at iggi.org.uk. Please send enquiries to the same email address Best wishes, Simon Lucas -------------- next part -------------- An HTML attachment was scrubbed... URL: From shyam at amrita.edu Sat Oct 8 04:36:29 2016 From: shyam at amrita.edu (Dr. Shyam Diwakar) Date: Sat, 8 Oct 2016 14:06:29 +0530 (IST) Subject: Connectionists: RAHA 2016 - Late Breaking Poster Session Message-ID: <1673267272.237045.1475915789857.JavaMail.zimbra@amrita.edu> Dear Colleagues, Apologies for cross-posting. Amrita University, India at its backwater-nestled campus in Kollam, Kerala is set for RAHA 2016 - International Conference on Robotics and automation for Humanitarian Applications to be held from December 18-20, 2016. The organizers are calling in for late-breaking posters in robotics, neurorobotics, societal and humanitarian applications and related topics. We welcome you to submit content and showcase new studies in the fields of robotics and humanitarian and societal applications. RAHA 2016 brings together top researchers, practitioners, and experts from the field of robotics for humanitarian applications. The conference will host 6 plenary and 16 keynote speakers from top universities and industry. Poster session Details: http://raha2016.org/call-for-abstracts-late-breaking-posters Conference website: http://raha2016.org Speakers: http://raha2016.org/speakers I look forward to meeting you in December. Shyam -- Shyam Diwakar, Ph.D. Amrita University http://www.amrita.edu/compneuro Disclaimer : The information transmitted in this email, including attachments, is intended only for the person(s) or entity to which it is addressed and may contain confidential and/or privileged material. Any review, retransmission, dissemination or other use of, or taking of any action in reliance upon this information by persons or entities other than the intended recipient is prohibited. Any views expressed in any message are those of the individual sender and may not necessarily reflect the views of Amrita University. If you received this in error, please contact the sender and destroy any copies of this information. -------------- next part -------------- An HTML attachment was scrubbed... URL: From Nicolas.Rougier at inria.fr Fri Oct 7 14:14:12 2016 From: Nicolas.Rougier at inria.fr (Nicolas P. Rougier) Date: Fri, 7 Oct 2016 20:14:12 +0200 Subject: Connectionists: New replication in ReScience: Robust timing and motor patterns by taming chaos in recurrent neural networks Message-ID: Dear all, It's my great pleasure to announce that the following article: * Robust timing and motor patterns by taming chaos in recurrent neural networks. Laje, R. and Buonomano, D.V., Nature Neuroscience 16(7) pp 925-33, 2013. has been successfully replicated in ReScience (using Python): * [Re] Robust timing and motor patterns by taming chaos in recurrent neural networks, J. Vitay, ReScience, volume 2, issue 1, 2016. You can read more at http://rescience.github.io/read. Article and code are available from https://github.com/ReScience-Archives/Vitay-2016 Nicolas P. Rougier From juergen at idsia.ch Sat Oct 8 10:41:23 2016 From: juergen at idsia.ch (Schmidhuber Juergen) Date: Sat, 8 Oct 2016 16:41:23 +0200 Subject: Connectionists: =?utf-8?q?PostDoc_at_the_Swiss_AI_Lab_IDSIA=3A_RN?= =?utf-8?q?NAIssance_=26_=22learning_to_think=E2=80=9D?= In-Reply-To: <31FBB059-0688-48FF-97A1-85CC36CDA4A0@idsia.ch> References: <31FBB059-0688-48FF-97A1-85CC36CDA4A0@idsia.ch> Message-ID: Most jobs of the RNNAIssance project are filled, but one postdoc position is still open. Next application deadline is Oct 31. The project is about reinforcement learning in realistic environments where traditional reinforcement learning (for board games etc) does not work well, where we need some sort of search for programs running on general purpose computers such as recurrent neural networks, and where a good reinforcement learning machine should learn to plan and reason in hierarchical and other abstract ways. Details and instructions: http://people.idsia.ch/~juergen/rnnai2016.html J?rgen Schmidhuber http://people.idsia.ch/~juergen/whatsnew.html ? From chriskanan at gmail.com Sat Oct 8 10:36:10 2016 From: chriskanan at gmail.com (Christopher Kanan) Date: Sat, 8 Oct 2016 10:36:10 -0400 Subject: Connectionists: Postdoc Position Available in Deep Learning at RIT Message-ID: *Topic*: Machine learning and deep learning for image attribute classification and image generation One postdoctoral position is available in the laboratory of Christopher Kanan at the Rochester Institute of Technology (RIT), in Rochester, NY. The lab specializes in applying machine learning algorithms to solve problems in computer vision and related fields. The candidate will be responsible for developing new algorithms for classifying image attributes as well as working on image generation using generative adversarial networks and related techniques. *Requirements:* Ph.D. in computer science or related field; A publication record in computer vision and/or machine learning; Familiarity with deep learning; Strong programming skills; Excellent written and oral English communication skills; The position is for two years. The salary is significantly above the typical postdoctoral market rate. Applications should include a CV, a list of references, and a one page cover letter explaining your background and why you want the position. Click here to apply online . Alternatively, go to http://careers.rit.edu/staff and use the Keyword Search 2782BR. Questions should be directed to christopher.kanan at rit.edu. *About Rochester, NY* Rochester is the third largest city in the U.S. state of New York. The quality of life in the area is excellent. It has a low cost of living and some of the best K-12 public schools in the United States. -- Christopher Kanan Assistant Professor Carlson Center for Imaging Science Rochester Institute of Technology http://www.chriskanan.com http://klab.cis.rit.edu/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From simon.d.levy at gmail.com Sun Oct 9 01:03:07 2016 From: simon.d.levy at gmail.com (Simon Levy) Date: Sun, 9 Oct 2016 01:03:07 -0400 Subject: Connectionists: Textbook announcement: Introduction to Scientific Computing and Programming in Python Message-ID: http://project-mosaic-books.com/?page_id=19 With Python taking over as the language of choice for connectionist modeling, we felt the need for a textbook that would give students and researchers a practical introduction to the NumPy and matplotlib packages, while also covering core concepts in software design. A chapter on sensors and signals shows you how to write your own data-acquisition code, and a chapter on graphical user interfaces shows you how to write software for use by non-programmers. >From the book's website : This book provides students with the modern skills and concepts needed to be able to use a computer expressively in scientific work. The authors take an integrated approach by covering programming, important methods and techniques of scientific computation (graphics, the organization of data, data acquisition, numerical issues, etc.) and the organization of software. Balancing the best of the teach-a-package and teach-a-language approaches, the book teaches general-purpose language skills and concepts, and also takes advantage of existing package-like software so that realistic computations can be performed. -- Simon D. Levy Professor Computer Science Department 407 Parmly Hall Washington & Lee University Lexington, VA 24450 540-458-8419 (voice) 540-458-8255 (fax) -------------- next part -------------- An HTML attachment was scrubbed... URL: From boracchi at elet.polimi.it Sun Oct 9 16:38:50 2016 From: boracchi at elet.polimi.it (Giacomo Boracchi) Date: Sun, 9 Oct 2016 22:38:50 +0200 Subject: Connectionists: "Concept Drift, Domain Adaptation & Learning in Dynamic Environments" SS @ IJCNN 2017 Message-ID: CALL FOR PAPERS Special Session on "Concept Drift, Domain Adaptation & Learning in Dynamic Environments" will be held within the INNS-IEEE IJCNN 2017, Anchorage Alaska in May, 14-19 2017. http://home.deib.polimi.it/boracchi/events/ijcnn2017_SS/index.html http://www.ijcnn.org/ ********************************************************** IMPORTANT DATES Paper submission: November 15th, 2016 Paper Decision notification: January 20th, 2017 Camera-ready submission: February 20th, 2017 Conference Dates: May 14 - 19th, 2017 *********************************************************** One of the fundamental goals in computational intelligence is to achieve brain-like intelligence, a remarkable property of which is the ability to incrementally learn from noisy and incomplete data, and ability to adapt to changing environments. The special session aims at presenting novel approaches to incremental learning and adaptation to dynamic environments both from the more traditional and theoretical perspective of computational intelligence and from the more practical and application-oriented one. This Special Session aspires at building a bridge between academic and industrial research, providing a forum for researchers in this area to exchange new ideas with each other, as well as with the rest of the neural network & computational intelligence community. *Topics* Papers must present original work or review the state-of-the-art in the following non-exhaustive list of topics: . Methodologies/algorithms/techniques for learning in dynamic/non-stationary environments . Incremental learning, lifelong learning, cumulative learning . Domain adaptation and covariate-shift adaptation . Semi-supervised learning methods for nonstationary environments . Ensemble methods for learning in nonstationary environments . Learning under concept drift and class imbalance . Learning recurrent concepts . Change-detection and anomaly-detection algorithms . Information-mining algorithms in nonstationary datastreams . Cognitive-inspired approaches for adaptation and learning . Applications that call for learning in dynamic/non-stationary environments, or change/anomaly detection, such as o adaptive classifiers for concept drift o adaptive/Intelligent systems o fraud detection o fault detection and diagnosis o network-intrusion detection and security o intelligent sensor networks o time series analysis . Benchmarks/standards for evaluating algorithms learning in non-stationary/dynamic environments *Keywords* Concept drift, nonstationary environment, change/anomaly detection, domain adaptation, incremental learning, data streams. *Paper Submission* THE DEADLINE FOR THE PAPER SUBMISSION TO THE SPECIAL SESSION IS THE SAME OF IJCNN 2017, November 15th 2017. All the submissions will be peer-reviewed with the same criteria used for other contributed papers. Perspective authors will submit their papers through the IJCNN 2017 conference submission system at http://www.ijcnn.org/ Please make sure to select the Special Session nr 5 "Concept Drift, Domain Adaptation & Learning in Dynamic Environments" from the "S. SPECIAL SESSION TOPICS" name in the "Main Research topic" dropdown list; Templates and instruction for authors will be provided on the IJCNN webpage http://www.ijcnn.org/ All papers submitted to the special sessions will be subject to the same peer-review procedure as regular papers, accepted papers will be published in the IEEE Conference Proceedings . Further information about IJCNN 2017 can be found at http://www.ijcnn.org/ For any question you may have about the Special Session or paper submission, feel free to contact Giacomo Boracchi *********************************************************** Special Session on "Concept Drift, Domain Adaptation & Learning in Dynamic Environments" @ IEEE IJCNN 2017 *Organizes* . Giacomo Boracchi (Politecnico di Milano, Dipartimento di Elettronica, Informazione e Bioingegneria, Italy) . Robi Polikar (Rowan University, Glassboro, NJ, USA) . Manuel Roveri (Politecnico di Milano, Dipartimento di Elettronica, Informazione e Bioingegneria, Italy) . Gregory Ditzler, (University of Arizona, AZ, USA) *********************************************************** -------------- next part -------------- An HTML attachment was scrubbed... URL: From bremeseiro at udc.es Mon Oct 10 05:16:56 2016 From: bremeseiro at udc.es (Beatriz Remeseiro =?utf-8?Q?L=C3=B3pez?=) Date: Mon, 10 Oct 2016 11:16:56 +0200 (CEST) Subject: Connectionists: CFP "Machine Learning Methods Applied to Medicine" SS @ IJCNN 2017 In-Reply-To: <1401908866.30874492.1476090992371.JavaMail.zimbra@udc.es> Message-ID: <1170668362.30874636.1476091016963.JavaMail.zimbra@udc.es> [Apologies if you receive multiple copies of this CFP] Call for papers: special session on "Machine Learning Methods Applied to Medicine" at IJCNN 2017 International Joint Conference on Neural Networks (IJCNN 2017) May 14-19, 2017 - Anchorage, Alaska (USA) - http://www.ijcnn.org/ Machine Learning Methods Applied to Medicine Organized by: Veronica Bolon-Canedo, Amparo Alonso-Betanzos (University of A Coru?a, Spain), Beatriz Remeseiro (University of Barcelona, Spain), Aur?lio Campilho (University of Porto, Portugal) Machine learning has been an active research area in the last decades finding success in many different applications, among them in medical problems. Since machine learning is capable of automating manual processes which practitioners have to carry out --usually time-consuming and subjective--, its use can save time for practitioners and provide unbiased and repeatable results. Furthermore, it is common that data in medicine have large dimensionality but reduced sample size, making even more necessary the use of advanced machine learning techniques for clinical interpretation and analysis. The aim of this special session is to investigate the use of different machine learning techniques or approaches applied to medical problems. Additionally, it provides a platform for academics and clinical researchers to present and share their cutting-edge methods to deal with medical applications, as well as discussing the new challenges that have recently emerged in this exciting cross-disciplinary field . The topics of interest include, but are not limited to: * New challenges in machine learning for medicine * Machine learning for personalized medicine * Artificial intelligence in medicine * Clinical interpretation and analysis * Computer-aided detection and diagnosis * Decision support systems * Feature selection and extraction in medicine * Big data in healthcare * Deep learning in large-scale datasets * Learning in uncertainty labeled data * Learning from sparse/missing/imbalanced data * Biomedical signal and image analysis * Bioinformatics and microarray analysis * Brain-computer interfaces Submitted papers will be reviewed according to the IJCNN reviewing process and will be evaluated on their scientific value: originality, correctness, and writing style. IMPORTANT DATES: Paper submission deadline: November 15, 2016 Paper decision notification: January 20, 2017 Camera-ready submission: February 20, 2017 IJCNN conference: May 14-19, 2017 -------------- next part -------------- An HTML attachment was scrubbed... URL: From acanet at cvc.uab.es Tue Oct 11 02:16:44 2016 From: acanet at cvc.uab.es (Alexandra Canet) Date: Tue, 11 Oct 2016 08:16:44 +0200 (CEST) Subject: Connectionists: 6 Post Doc Positions open in Computer Vision in Barcelona Message-ID: <17031331.95518.1476166604752.open-xchange@srvopenx.cvc.uab.es> The Computer Vision Center, Barcelona, has currently available 6 P-Sphere (Marie Curie actions) Fellowships in Computer vision. They are 3 year fellowships within different Computer Vision topics and can be all found here: Application deadline: 9th December 2016. - - Alexandra Canet Communications Officer Computer vision centre acanet at cvc.uab.es + 34 93 581 30 73 Edifici O ? Campus UAB 08193 Bellaterra, Barcelona -------------- next part -------------- An HTML attachment was scrubbed... URL: From m.biehl at rug.nl Tue Oct 11 07:35:14 2016 From: m.biehl at rug.nl (Michael Biehl) Date: Tue, 11 Oct 2016 13:35:14 +0200 Subject: Connectionists: CFP: Special Session at IJCNN, Interpretable models Message-ID: First call for papers: *Special Session at IJCNN 2017 * *Interpretable models in machine learning for advanced data analysis* *Anchorage, Alaska, USA, May 2017* Organizers / contact: Michael Biehl (m.biehl at rug.nl), Thomas Villmann ( villmann at hs-mittweida.de) Technological progress leads to a tremendous growth of the amount of digital data in virtually all scientific and engineering disciplines. At the same time, the structural complexity of the acquired data is increasing steadily. As a consequence, it is instrumental to develop efficient methods for automated data analysis. However, good performance of the methods in terms of, for instance, classification or clustering is frequently not sufficient. Very often, deeper insight into the data processing and the problem at hand is desirable. For example, classifiers should be interpretable as to how the classification of a particular observation is obtained and which of the available information constitutes the basis of the decision. These additional properties of data processing methods can be summarized best by the term interpretability. The aim of the special session is to present and discuss new approaches for data analysis in terms of interpretable models, i.e. aiming at their added value beyond the mere clustering or classification itself. Interpretability of models is essential in nearly all areas of machine learning and data analysis. Hence, the topic of the session should be relevant for a large variety of research areas within the IJCNN community. Possible topics include, but are not restricted to: - prototype based models for unsupervised and supervised learning - analysis of interpretable data structures - interpretable feature extraction for improved performance - visualization of multi-dimensional data for knowledge extraction - integration of prior and expert knowledge - interpretable adaptive (dis-)similarities and relevance learning We encourage researchers interested in the theory and/or real world applications of interpretable models to contribute to the session. Theoretical models should be illustrated, whenever possible. Application oriented contributions should demonstrate how the interpretable models provide new, relevant insights into the data beyond the original task of, e.g., classification, prediction, or clustering. Please visit the conference homepage for practical information and submission guidelines. Important dates: Paper submission: November 15, 2016 Decision notification: January 20, 2017 Final version due: February 20, 2017 IJCNN conference: May 14-19, 2017 ---------------------------------------------------------- Prof. Dr. Michael Biehl Johann Bernoulli Institute for Mathematics and Computer Science P.O. Box 407, 9700 AK Groningen The Netherlands Tel. +31 50 363 3997 www.cs.rug.nl/~biehl m.biehl at rug.nl -------------- next part -------------- An HTML attachment was scrubbed... URL: From education at humanbrainproject.eu Tue Oct 11 04:37:40 2016 From: education at humanbrainproject.eu (HBP Education) Date: Tue, 11 Oct 2016 10:37:40 +0200 Subject: Connectionists: 1st HBP Student Conference: Extended Abstract Submission Deadline Message-ID: <789ECF19-70D8-40D9-9B18-84CFB14DD968@humanbrainproject.eu> Dear all, In February 2017, the Education Programme Office of the Human Brain Project will organise its 1st Student Conference in Vienna, Austria under the title ?Transdisciplinary Research Linking Neuroscience, Brain Medicine and Computer Science?. Please find some general information about the conference below and in the attached PDF files. Best regards, The Education Programme Office Medical University Innsbruck (MUI) Center of Psychiatry and Psychotherapy Experimental Psychiatry Unit Innrain 66a, 6020 Innsbruck, Austria Phone Office: +43 512 504 23710 Fax Office: +43 512 504 23716 Email: education at humanbrainproject.eu 1st HBP Student Conference: Transdisciplinary Research Linking Neuroscience, Brain Medicine and Computer Science Vienna, Austria, 8-10 February 2017 education.humanbrainproject.eu/web/studentconference Description In the context of the 1st HBP Student Conference, young researchers from the fields of neuroscience, brain medicine and computer science receive the possibility to exchange ideas and perspectives and discuss various aspects of their particular fields of expertise relevant to the Human Brain Project. The conference offers a variety of discussion sessions, lectures and social events. Through working across boundaries and linking the various fields, it serves as a platform for both intra- and interdisciplinary exchange and is a great opportunity for extensive scientific discussions among peers and faculty, and also a fertile soil for new, innovative ideas. Conference Structure Keynote Lectures Discussion Sessions Student Lightning Talks Poster Presentations Round Table Discussion Social Event We are looking for original high-quality submissions containing innovative research from all fields relating to the HBP research programme. Contributions emphasising theoretical and empirical foundations are just as welcome as new approaches to specific questions concerning the twelve subprojects of the HBP. Finally, we particularly encourage submissions introducing new and relevant problems, concepts and ideas with the potential to inspire the research community ? even if the approach is at an early stage of development. All participants may submit an extended abstract and will have the opportunity to present their work. Presentations will include a brief oral presentation, a poster, or both. Abstract submission deadline extended until 28 October 2016. The conference will start on Wednesday, 8 February 2017 in the early afternoon with registration and end the afternoon of Friday, 10 February 2017. Scientific Committee Nikola Simidjievski, chair | JSI Andrea Santuy | UPM Miriam Menzel | FZ JUELICH Jovan Tanevski | JSI Vitali Karasenko | UHEI Tara Mahfoud | KCL Organised by HBP Education Programme Office Upcoming Deadlines Extended abstract submission deadline: 28 October 2016 Online registration closes: 23 January 2017 Contact HBP Education Programme Office Medical University Innsbruck Center of Psychiatry and Psychotherapy Experimental Psychiatry Unit Innrain 66a, 6020 Innsbruck, Austria Phone: +43 512 504 23710 Fax: +43 512 504 23716 E-mail: education at humanbrainproject.eu Website: education.humanbrainproject.eu/web/studentconference The Venue The conference will take place at the Campus of the University of Vienna. It is a place of work for students and researchers, a place for the exchange of knowledge, and in its function as congress venue also serves as an important meeting point for students and researchers from all over the world. Vienna is the capital and largest city of Austria, located in the northeast of the country on the banks of the Danube River. As Austria's cultural, economic and political centre, the city unites the royal-imperial flair of the past with the latest trends. There are excellent museums, art collections, numerous theatres and operas. Vienna is also famous for its coffeehouses and cuisine. Keynote Lectures Christine Aicardi | KCL Anna Letizia Allegra | UFI Gaute Einevoll | NMBU Dragi Kocev | JSI Kai Kummer | MUI Mihai Petrovici | UHEI Florian R?hrbein | TUM Keywords Neuroscience Brain Medicine Computer Science -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: 1st HBP Student Conference 2017_161011_TR.pdf Type: application/pdf Size: 527397 bytes Desc: not available URL: -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: Programmheft_studentconference_extended_deadline_v3_small_160921_MG.pdf Type: application/pdf Size: 2099235 bytes Desc: not available URL: -------------- next part -------------- An HTML attachment was scrubbed... URL: From marcel.van.gerven at gmail.com Mon Oct 10 16:18:12 2016 From: marcel.van.gerven at gmail.com (Marcel van Gerven) Date: Mon, 10 Oct 2016 22:18:12 +0200 Subject: Connectionists: Extended Deadline Artificial Neural Networks as Models of Neural Information Processing Message-ID: <3B6B8597-D3B7-446E-86FA-4B6028615546@gmail.com> We are pleased to inform you that our Research Topic organized with Frontiers in Computional Neuroscience is still open, and has an extended deadline for article submission. As a reminder, our Research Topic is entitled: "Artificial Neural Networks as Models of Neural Information Processing? Extended Article Submission Deadline: December 1st, 2016 Submission details can be found here: http://journal.frontiersin.org/researchtopic/4817/artificial-neural-networks-as-models-of-neural-information-processing Research Topic Description: Artificial neural networks (ANNs) are computational models that are loosely inspired by their biological counterparts. In recent years, major breakthroughs in ANN research have transformed the machine learning landscape from an engineering perspective. At the same time, scientists have started to revisit ANNs as models of neural information processing in biological agents. From an empirical point of view, neuroscientists have shown that ANNs provide state-of-the-art predictions of neural responses to naturalistic stimuli. From a theoretical point of view, computational neuroscientists have started to address the foundations of learning and inference in next-generation ANNs, identifying the desiderata that models of neural information processing should fulfill. The goal of this Research Topic is to bring together key experimental and theoretical ANN research with the aim of providing new insights on information processing in biological neural networks through the use of artificial neural networks. We welcome contributions that are of direct relevance to neuroscientists that use ANNs as a model of neural information processing. This topic is timely given the recent exciting developments in the field and will be highly attractive to a wide community of brain researchers, as well as for the community at large. Topic Editors: Marcel van Gerven & Sander Bohte About Frontiers Research Topics: Frontiers Research Topics are designed to be an organized, encyclopedic coverage of a particular research area, and a forum for discussion and debate. Contributions can be of different article types (Original Research, Methods, Hypothesis & Theory, and others). Our Research Topic has a dedicated homepage on the Frontiers website, where contributing articles are accumulated and discussions can be easily held. Once all articles are published, the topic will be compiled into an e-book, which can be sent to foundations that fund your research, to journalists and press agencies, and to any number of other organizations. As the ultimate reference source from leading scientists, Frontiers Research Topic articles become highly cited. Frontiers is a Swiss-based, open access publisher. As such an article accepted for publication incurs a publishing fee, which varies depending on the article type. The publishing fee for accepted articles is below average compared to most other open access journals - and lower than subscription-based journals that apply page and color figure charges. Moreover, for Research Topic articles, the publishing fee is discounted quite steeply thanks to the support of the Frontiers Research Foundation. Details on Frontiers? fees can be found at http://www.frontiersin.org/about/PublishingFees. When published, your article will be freely available to visitors to the Frontiers site, and will be indexed in PubMed and other academic archives. As an author in Frontiers, you will retain the copyright to your own paper and all figures. -------------- next part -------------- An HTML attachment was scrubbed... URL: From fabian.soto at fiu.edu Mon Oct 10 19:18:08 2016 From: fabian.soto at fiu.edu (=?UTF-8?B?RmFiacOhbiBTb3Rv?=) Date: Mon, 10 Oct 2016 19:18:08 -0400 Subject: Connectionists: PhD Position in Computational Cognitive Neuroscience at FIU in Miami Message-ID: The Computational Cognitive Neuroscience Lab at FIU in Miami (PI Dr. Fabian Soto) is looking for a doctoral student to start in the Fall of 2017. The student will work in the development of new methods to test independent processing of stimulus dimensions in the brain, within a framework that combines general recognition theory (a multidimensional version of signal detection theory) and population encoding models. The developed methods will be applied to the analysis of EEG and fMRI studies on object categorization. Our lab's research focuses on understanding the interplay between learning and visual processes in object categorization. We use a combination of behavioral, computational, and brain imaging techniques. FIU is classified as an R1 (highest research activity) institution by the Carnegie Foundation. It is Florida?s fastest growing public research university, the fourth largest university in the US, and one of the nation?s largest hispanic-serving institutions. FIU has recently established a state-of-the-art neuroimaging center (the Cognitive Neuroscience and Imaging Center), which hosts a research-dedicated 3T Siemens MAGNETOM Prisma MRI scanner and a fully equipped mock scanner for pre-scan and movement training. If you know of any potentially interested candidates with a broad scientific background who are interested in neuroimaging, psychology, and computational modeling, please have them contact Dr. Fabian Soto at fabian.soto at fiu.edu. More information about FIU?s Cognitive Neuroscience doctoral program in Psychology is available at http://cn.fiu.edu. The deadline for application is December 1st of 2016. -- Fabian A. Soto Assistant Professor Department of Psychology Florida International University Modesto A. Maidique Campus 11200 SW 8th St, AHC4 460 Miami, FL 33199 Phone: 305-348-8423 Fax: 305-348-6670 Email: fabian.soto at fiu.edu -------------- next part -------------- An HTML attachment was scrubbed... URL: From dayan.eran at gmail.com Tue Oct 11 14:31:23 2016 From: dayan.eran at gmail.com (Eran Dayan) Date: Tue, 11 Oct 2016 14:31:23 -0400 Subject: Connectionists: Please post Message-ID: <26D9A264-1B51-46D7-80FF-564D7397946E@gmail.com> Title: Postdoctoral Research Associate Position at UNC Chapel Hill A Postdoctoral Scholar position is immediately open to work with the Network Neuroscience lab (dayanlab.web.unc.edu ) at the Biomedical Research Imaging Center, University of North Carolina School of Medicine. The position is open to accomplished and highly motivated candidates. The postdoctoral Scholar will collect and analyze brain connectivity data from healthy volunteers and neurological patients, and also work with large, pre-existing datasets. Our current focus is on neuromodulation of brain networks (e.g., pharmacological or electrical), as well as on early developmental changes in brain network connectivity. The duration of the appointment is 12 months (renewable). The position requires a Ph.D. or an MD/Ph.D. in Neuroscience, Computer Science, Biomedical Engineering, Physics, Psychology or other related fields. Excellent quantitative background, relevant programming experience (MATLAB, Python or R), experience analyzing functional and/or structural MRI data and a track record of first-author publications in peer-reviewed journals are essential. Experience in analyzing functional and/or structural connectivity data would be advantageous, as is experience in graph-theoretical methods, machine learning or multivariate pattern similarity methods. The University of North Carolina at Chapel Hill is an equal opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender, gender expression, gender identity, genetic information, race, national origin, religion, sex, sexual orientation, or status as a protected veteran. To apply, please visit https://unc.peopleadmin.com/postings/107413 . For informal inquiries about the position, please email Dr. Eran Dayan at: eran_dayan at med.unc.edu -------------- next part -------------- An HTML attachment was scrubbed... URL: From cer at google.com Tue Oct 11 13:49:21 2016 From: cer at google.com (Daniel Cer) Date: Tue, 11 Oct 2016 10:49:21 -0700 Subject: Connectionists: Call for Shared Task Participation - SemEval 2017 Task 1: Semantic Textual Similarity (STS) Message-ID: Call for Shared Task Participation SemEval 2017 Task 1 Semantic Textual Similarity (STS) Semantic Textual Similarity (STS) measures the degree of equivalence in the underlying semantics of paired snippets of text. While making such an assessment is trivial for humans, constructing algorithms and computational models that mimic human level performance represents a difficult and deep natural language understanding problem. STS evaluations have seen significant progress in methods targeted at a specific language such as English or Spanish. For the 2017 shared task, the emphasis is on building multilingual textual similarity models that are capable of assessing both same language and cross-lingual sentence pairs. The primary evaluation for the shared task assesses methods over a combination of same language pairs in Arabic, English and Spanish as well as cross-lingual Arabic-English and Spanish-English pairs. To encourage the development of methods that can be readily applied or adapted to new languages, we also provide an optional evaluation track with a surprise language that will only be announced at the beginning of the evaluation period. This optional track provides an opportunity to explore STS models capable of zero-shot learning via mechanisms such as multilingual embeddings. In addition to the multilingual primary evaluation and the surprise language track, a number of language and language pair specific tracks are also provided. We hope that these tracks will provide participants with particular linguistic expertise a chance to excel as well as provide an opportunity to compare performance differences between multilingual and language specific methods. Task Definition =============== Given two sentences, participants are asked to produce a continuous valued similarity score on a scale from 0 to 5, with 0 indicating that the semantics of the sentences are completely independent and 5 signifying semantic equivalence. Performance is assessed by computing the Pearson correlation between machine assigned semantic similarity scores and human judgments. Following the emphasis on building multilingual and cross-lingual models, the 2017 shared task is organized into the following seven multilingual and cross-lingual tracks: Track 0 - Primary: Combined evaluation of all announced monolingual and cross-lingual language pairings explored by the 2017 task: ar-ar, ar-en, en-en, es-en, and es-es. The primary track will not include the surprise language evaluation data. Track 1 - Arabic-Arabic: Evaluation only on ar-ar pairs. Track 2 - Arabic-English: Evaluation only on ar-en pairs. Track 3 - Spanish-Spanish: Evaluation only on es-es pairs Track 4 - Spanish-English: Evaluation only on es-en pairs. Track 5 - English-English: Evaluation only on en-en pairs. Track 6 - Surprise language track (announced during the evaluation period) For all language pairings, participants will be provided with two sentence length snippets of text, s1 and s2. The two snippets will then be used to compute and return a continuous valued semantic similarity score. The cross-lingual language pairings (ar-en, es-en) only differ from the monolingual language pairings (ar-ar, en-en, es-es) in that the two text snippets in each pair are written in different languages. The inclusion of cross-lingual STS pairs follows a successful pilot in 2016 that paired English and Spanish sentences. Depending on the approach being used to compute the similarity scores this may present different degrees of difficulty in adapting the underlying model to handle the cross-lingual pairs. Participants are encouraged to review the successful approaches to monolingual and cross-lingual STS from prior years of the STS shared task (Agirre et al. 2016; Agirre et al. 2015; Agirre et al. 2014; Agirre et al. 2013; Agirre et al. 2012) 2017 Data ========= This year's shared task includes one evaluation set for each of the seven tracks described above. Each evaluation set consists of between 200 to 250 sentence pairs. Within each evaluation set, we will attempt to approximately balance the distribution of STS scores. For training data, participants are encouraged to make use of all existing English, Spanish and cross-lingual English-Spanish data sets from prior STS evaluations. This includes all previously released trial, training and evaluation data. Since this is the first year that we will include Arabic as part of an STS evaluation, we will release training data for both monolingual Arabic and cross-lingual Arabic-English. Each training set will consist of approximately 14,000 pairs sourced from prior English STS evaluations. As with the 2016 evaluation, participants are allowed and very much encouraged to train purely unsupervised models and model components on arbitrary data (e.g., unsupervised word embeddings). Participation ============= [Register] To register, please complete the following form: https://docs.google.com/forms/d/e/1FAIpQLScXnt7qeioCPyxu6dv9wrSDYaF04bRgVBFCUbahxsAG6F43Sg/viewform [Website and trial data] For more details, including trial data, see the STS SemEval 2017 Task 1 webpage at: http://alt.qcri.org/semeval2017/task1/ [Mailing List] Join the mailing list for task updates and discussion at: http://groups.google.com/group/STS-semeval. Important dates =============== Trail data ready: Wed 21 Sep 2016 Training data ready: Mon 24 Oct 2016 Evaluation start: Mon 09 Jan 2017 Evaluation end: Mon 30 Jan 2017 Results posted: Mon 06 Feb 2017 Paper submissions due: Mon 27 Feb 2017 Author notifications: Mon 03 Apr 2017 Camera ready submissions due: Mon 17 Apr 2017 SemEval workshop: Summer 2017 Organizers (alpha. order) ========== Eneko Agirre, Daniel Cer, Mona Diab, Lucia Specia References ========== Eneko Agirre, Carmen Banea, Daniel Cer, Mona Diab, Aitor Gonzalez-Agirre, Rada Mihalcea, German Rigau, Janyce Wiebe. SemEval-2016 Task 1: Semantic Textual Similarity, Monolingual and Cross-Lingual Evaluation. Proceedings of SemEval 2016. Eneko Agirre, Carmen Banea, Claire Cardie, Daniel Cer, Mona Diab, Aitor Gonzalez-Agirre, Weiwei Guo, Inigo Lopez-Gazpio, Montse Maritxalar, Rada Mihalcea, German Rigau, Larraitz Uria and Janyce Wiebe. SemEval-2015 Task 2: Semantic Textual Similarity, English, Spanish and Pilot on Interpretability. Proceedings of SemEval 2015. Eneko Agirre, Carmen Banea, Claire Cardie, Daniel Cer, Mona Diab, Aitor Gonzalez-Agirre, Weiwei Guo, Rada Mihalcea, German Rigau and Janyce Wiebe. SemEval-2014 Task 10: Multilingual Semantic Textual Similarity. Proceedings of SemEval 2014. Eneko Agirre, Daniel Cer, Mona Diab, Aitor Gonzalez-Agirre and WeiWei Guo. *SEM 2013 shared task: Semantic Textual Similarity. Proceedings of *SEM 2013. Eneko Agirre, Daniel Cer, Mona Diab and Aitor Gonzalez-Agirre. SemEval-2012 Task 6: A Pilot on Semantic Textual Similarity. Proceedings of SemEval 2012. -------------- next part -------------- An HTML attachment was scrubbed... URL: From stefanos at cs.ntua.gr Wed Oct 12 07:29:27 2016 From: stefanos at cs.ntua.gr (Stefanos Kollias) Date: Wed, 12 Oct 2016 14:29:27 +0300 Subject: Connectionists: [jobs] up to 4 Lecturer / Senior Lecturer Positions in Machine Learning, University of Lincoln, UK Message-ID: <57FE1E97.40009@cs.ntua.gr> Dear Colleagues, We are looking for up to 4 Lecturers/Senior Lecturers in Computer Science with a focus on Machine Learning and related fields, at the University of Lincoln - College of Science - School of Computer Science, UK: Location: Lincoln Hours: Full Time Contract Type: Permanent Placed on: 11th October 2016 Closes: 6th November 2016 Job Ref: COS278 Lecturer Salary: ?32,004+ Senior Lecturer Salary: ?37,075+ The School of Computer Science at the University of Lincoln has scored highly in the recent independent performance measures of UK university computing departments; in the top 20% for student satisfaction (NSS 2014), the top 50 for research excellence in its publications (RAE 2014) and approximately 10% above the sector average for graduate employability (DLHE 2014). In the most recently published subject league tables (Sunday Times 2015; Complete University Guide 2016) the School is the highest ranked ?new? (post 1992) computer science department in the country. We are seeking to appoint up to Four (4) Lecturers/Senior Lecturers in Machine Learning. You will deliver modules in core computer science and contribute specifically to research in machine learning, both in theory and in practice, including related topics such as data science, artificial intelligence, knowledge representation & reasoning, NLP, multimedia analysis and applications. You will contribute to the University?s ambition to achieve international recognition as a research-intensive institution, conduct high quality research, seek external research income, encourage or facilitate commercial enterprise, supervise postgraduate research students and contribute to wider activities of the School. Candidates should possess a PhD or equivalent experience, ideally in computer or information science and preferably with a track record in the delivery of study modules at undergraduate and/or postgraduate level. You should be able to demonstrate a commitment to maintaining the University?s high standards in teaching and learning. Your research interests will form an integral part of a new research group in Machine Learning at the School of Computer Science, working together with the newly appointed Founding Professor of Machine Learning. It is envisaged that the new group will focus on research into theoretical aspects, methodologies and practical applications of machine learning, as well as providing fundamental expertise in core machine learning to the School?s other research areas. We are seeking a good team worker who will be able to both align with and complement our existing research activity. The University of Lincoln is a forward-thinking, ambitious institution and you will be working in the heart of a thriving, beautiful, safe and friendly city. The School provides a stimulating environment for academic research, and is located on the picturesque waterfront campus in the vibrant city of Lincoln. In 2017 the School will move into new, purpose built facilities. If you would like to know more about this opportunity, please contact Professor Stefanos Kollias (skollias at lincoln.ac.uk) or Acting Head of School Dr Kevin Jacques (kjacques at lincoln.ac.uk). To apply online, please visit the website at http://jobs.lincoln.ac.uk/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From pierre-yves.oudeyer at inria.fr Wed Oct 12 10:06:05 2016 From: pierre-yves.oudeyer at inria.fr (Pierre-Yves Oudeyer) Date: Wed, 12 Oct 2016 16:06:05 +0200 Subject: Connectionists: [call for paper] IEEE IJCNN 2017 Special Session on COGNITION AND DEVELOPMENT Message-ID: =========================== CALL FOR PAPERS ============================ IEEE IJCNN 2017 Special Session on COGNITION AND DEVELOPMENT May 14-19, 2017, Anchorage, Alaska, USA. sites.google.com/site/ijcnnsscognitiondevelopment Important Dates (same as main conference look on the website for updates): Paper submission: November 15, 2016 Paper decision notification: January 20, 2017 Camera-ready submission: February 20, 2017 Notes: Dates are the same as main conference, please check the IJCNN website for updates: www.ijcnn.org All papers submitted to the special sessions will be subject to the same peer-review procedure as regular papers, accepted papers will be published in the conference proceedings. Templates and instruction for authors are provided on the IJCNN submission webpage http://www.ijcnn.org/paper-submission Please make sure to select the Special Session "Cognition and Development" (under "S. SPECIAL SESSION TOPICS") as the "Main Research topic" of your submission. Aim and Scope The special session aims at the presentation of the latest models and results in the investigation of developmental issues in cognitive development and their application to computational and robotics models. In particular it encourages submissions on neural computation and cognitive robotics models of sensorimotor, cognitive and social development inspired by our understanding of human development, or used to improve this understanding in interaction with psychology and neuroscience. These include evolutionary and developmental models of the origins of intrinsic motivation, perceptual and motor development, social learning and interaction, imitation, acquisition of communicative and linguistic skills, and reasoning. Scientific challenges addressed by these models include: What are the mechanisms that allow a child (and a robot) to develop autonomously cognitive capabilities? How does the social and physical environment, with which the child interacts, shape and scaffold the child?s developing cognitive skills and knowledge? What are the constraints and the cognitive primitives that are needed to bootstrap development? What do qualitative stages during development, and body and brain maturational changes, tell us about the mechanisms and principles supporting development? The special session also encourages submissions from the empirical developmental science disciplines, such as child psychology, developmental linguistics and neuroscience, and interdisciplinary approaches to cognition and development. List of Main Topics * Developmental robotics * Epigenetic robotics * Neuro-robotics * Bio-inspired and cognitive robotics * Cognitive modelling * Intrinsic motivation * Sensorimotor development * Cognitive development * Social development * Language acquisition * Novel tools for cognition and development in robots Organizers: Alessandro Di Nuovo, Sheffield Hallam University, UK Pierre-Yves Oudeyer, INRIA, Bordeaux, France Angelo Cangelosi, University of Plymouth, UK From eb-ballester at bournemouth.ac.uk Wed Oct 12 09:40:15 2016 From: eb-ballester at bournemouth.ac.uk (Emili Balaguer-Ballester) Date: Wed, 12 Oct 2016 13:40:15 +0000 Subject: Connectionists: =?windows-1252?q?PhD_position_in_Computational_Ne?= =?windows-1252?q?uroscience_=91Metastable_Cortical_Dynamics_Underlying_Co?= =?windows-1252?q?gnition=92_=28Bournemouth_University-IDIBAPS_Barcelona?= =?windows-1252?q?=29?= In-Reply-To: References: Message-ID: PhD position in Computational Neuroscience ?Metastable Cortical Dynamics Underlying Cognition? (Bournemouth University-IDIBAPS Barcelona) A PhD position is available in the 3-years fully-funded project ?Metastable Cortical Dynamics Underlying Cognition?; based at Bournemouth University (UK) https://research.bournemouth.ac.uk/centre/interdisciplinary-neuroscience-research/ and at the Biomedical Research Institute August Pi I Sunyer (IDIBAPS, http://www.idibaps.org/en_index.htm, University of Barcelona, Spain). Do we have analysis tools for discerning neuronal dynamics underlying cognition? This is a fundamental question, touching the very basics of our understanding of neural computation and hence one of the most exciting topics in neuroscience. However, it is a major challenge for current theoretical approaches. The aim of this project is to provide new theoretical ideas which enables us to discern metastable dynamics in high cognitive areas; this is important for deciding among competing models of cognitive decisions and would be a significant advance in computational and systems neuroscience. The training possibilities that this interdisciplinary project offers are multiple and relevant in building-up a high-profile as a computational neuroscientist. The student will benefit from the vibrant scientific environment of neural computation and neurosciences at BU https://research.bournemouth.ac.uk/centre/interdisciplinary-neuroscience-research/ and at the cortical networks lab; embedded in the systems neuroscience network in Barcelona http://www.sanchez-vives.org/. Applicants with enthusiasm for developing new theories and a strong mathematical background are very welcome. Qualifications in either Physics, Computer Science, Engineering, Mathematics or in any similar degree would be very advantageous; as well as previous knowledge or interest in neuroscience, or lab experience. The researcher would be based at the Faculty of Science, Bournemouth University, working closely with Dr Balaguer-Ballester at the Computational Neuroscience laboratory in the context of the interdisciplinary group for neurosciences; and would spend prolonged periods of time in the Cortical Networks Lab (IDIBAPS, Barcelona) led by Prof Maria Victoria Sanchez-Vives. Thus, this position provides a good opportunity to gain a diverse experience of both neuro-computational and experimental approaches. For applying and more information please visit https://www1.bournemouth.ac.uk/study/courses/phd-studentship-metastable-cortical-dynamics-underlying-cognition The deadline is on the 28th of November, 2016 For further questions, please contact: eb-ballester at bournemouth.ac.uk: Twitter: @emilibalball BU is a Disability Two Ticks Employer and has signed up to the Mindful Employer charter. Information about the accessibility of University buildings can be found on the BU DisabledGo webpages This email is intended only for the person to whom it is addressed and may contain confidential information. If you have received this email in error, please notify the sender and delete this email, which must not be copied, distributed or disclosed to any other person. Any views or opinions presented are solely those of the author and do not necessarily represent those of Bournemouth University or its subsidiary companies. Nor can any contract be formed on behalf of the University or its subsidiary companies via email. -------------- next part -------------- An HTML attachment was scrubbed... URL: From mcallester at ttic.edu Wed Oct 12 06:35:01 2016 From: mcallester at ttic.edu (David McAllester) Date: Wed, 12 Oct 2016 05:35:01 -0500 Subject: Connectionists: Announcing a Workshop on Symbolic-Neural Learning (SNL) in Nagoya Japan, July 7-8, 2017 Message-ID: We are pleased to announce a Workshop on Symbolic-Neural Learning (SNL) to be held July 7-8, 2017 in Nagoya Japan. Submission deadline March 15, 2017. Symbolic-neural learning involves deep learning methods in combination with symbolic structures. A "deep learning method" is taken to ?be any method for ?non-convex optimization of a large number of real-valued model parameters. ? See the web site for more discussion.? ?K eynote speakers ? will include? Yoshua Bengio (invited) Universit? de Montr?al, Montr?al, Canada William Cohen (invited) Carnegie Mellon University, Pittsburgh, USA Masashi Sugiyama RIKEN and University of Tokyo, Tokyo, Japan Jun'ichi Tsujii AI Center, AIST, Tokyo, Japan Other details can be found at the web site. David McAllester, Yutaka Sasaki Program co-chairs -------------- next part -------------- An HTML attachment was scrubbed... URL: From gluck at pavlov.rutgers.edu Thu Oct 13 17:04:26 2016 From: gluck at pavlov.rutgers.edu (Mark Gluck) Date: Thu, 13 Oct 2016 17:04:26 -0400 Subject: Connectionists: =?utf-8?q?Three_new_papers_on_the_cognitive_neuro?= =?utf-8?q?science_of_learning_and_memory_as_affected_by_sleep_=28Lerner_e?= =?utf-8?b?dCBhbC4sIDIwMTYpLCBhbW5lc2lhIChP4oCZQ29ubmVsbCBldCBhbC4sIDIw?= =?utf-8?b?MTYpLCAmIGFueGlldHkgKEtoZG91ciBldCBhbCwgMjAxNiku?= Message-ID: <91B558C5-2923-44DD-A14C-74A5E68EADF1@pavlov.rutgers.edu> Re: Three new papers on the cognitive neuroscience of learning and memory as affected by sleep (Lerner et al., 2016), amnesia (O?Connell et al., 2016), & anxiety (Khdour et al, 2016). Dear Colleagues, We are pleased to share with you reprints of three new papers from our lab covering the cognitive neuroscience of learning and memory as it is impacted by sleep, amnesia, and anxiety. The citations, abstracts and links to the papers? full PDFs are given below. As always, we welcome any and all feedback, comments, ideas, or pointers to relevant or related current or past work. ______________________________________ Lerner, I., Lupkin, S., Peters, S., Corter, J., Peters, S., Cannella, L., & Gluck, M.A. (2016). The influence of sleep on emotional and cognitive processing is primarily trait- (but not state-) dependent. Neurobiology of Learning and Memory. 134, 275-286. DOI: 10.1016/j.nlm.2016.07.032 http://www.gluck.edu/pdf/Lerner_etal_2016_FINAL.pdf ? Human studies of sleep and cognition have established that different sleep stages contribute to distinct aspects of cognitive and emotional processing. However, since the majority of these findings are based on single night studies, it is difficult to determine whether such effects arise due to individual, between-subject differences in sleep patterns, or from within-subject variations in sleep over time. In the current study, we investigated the longitudinal relationship between sleep patterns and cognitive performance by monitoring both in parallel, daily, for a week. Using two cognitive tasks ? one assessing emotional reactivity to facial expressions and the other evaluating learning abilities in a probabilistic categorization task ? we found that between-subject differences in the average time spent in particular sleep stages predicted performance in these tasks far more than within-subject daily variations. Specifically, the typical time individuals spent in Rapid-Eye Movement (REM) sleep and Slow-Wave Sleep (SWS) was correlated to their characteristic measures of emotional reactivity, whereas the typical time spent in SWS and non-REM stages 1 and 2 was correlated to their success in category learning. These effects were maintained even when sleep properties were based on baseline measures taken prior to the experimental week. In contrast, within-subject daily variations in sleep patterns only contributed to overnight difference in one particular measure of emotional reactivity. Thus, we conclude that the effects of natural sleep on emotional cognition and category learning are more trait-dependent than state-dependent, and suggest ways to reconcile these results with previous findings in the literature.  ______________________________________ O'Connell, G., Myers, C.E., Hopkins, R.O., McLaren, R.P., Gluck, M.A., & Wills, A.J. (2016, July 21; Epub). Amnesic patients show superior generalization in category learning. Neuropsychology. DOI: 10.1037/neu0000301 http://www.gluck.edu/pdf/oconnell.Myers.Gluck2016_pub.pdf ? Questions remain about the precise role of the hippocampus in this facet of learning, but a connectionist model by Gluck and Myers (1993) predicts that generalization should be enhanced following hippocampal damage. In a two-category learning task, a group of amnesic patients (n=9) learned the training items to a similar level of accuracy as matched controls (n=9). Both groups then classified new items at various levels of distortion. The amnesic group showed significantly more accurate generalization to high distortion novel items, a difference also present when compared to a larger group of unmatched controls (n=33). The model prediction of a broadening of generalization gradients in amnesia, at least for items near category boundaries, was supported by the results. Our study shows for the first time that amnesia can sometimes improve generalization. ______________________________________ Khdour, H.Y., Imam, A.F., Mughrabi, I.T., Myers, C.E., Gluck, M.A., Herzallah, M.M., & Moustafa, A.A. (2016). Generalized anxiety disorder and social anxiety disorder, but not panic anxiety disorder, are associated with higher sensitivity to learning from negative feedback: behavioral and computational investigation. Frontiers in Integrative Neuroscience. 10:20. doi: 10.3389/fnint.2016.00020 http://www.gluck.edu/pdf/Khdour-Gluck(FrontiersIN).GAD.2016.pdf ? Anxiety spectrum disorders, including generalized anxiety disorder (GAD), social anxiety disorder (SAD) and panic anxiety disorder (PAD), are a group of common psychiatric conditions. In this study, we tested the cognitive correlates of medication-free patients with GAD, SAD, and PAD, along with matched healthy participants, using a probabilistic category-learning task that allows the dissociation between positive and negative feedback learning. We also fitted all participants? data to an actor-critic model that examines learning rate parameters from positive and negative feedback to investigate effects of valence vs. action on performance. SAD and GAD patients were more sensitive to negative feedback than either PAD patients or healthy participants. PAD, SAD and GAD patients did not differ in positive-feedback learning compared to healthy participants. Computational analysis revealed that participants? behavioral results are better explained by the critic?s learning from negative feedback variable. These findings argue that (a) not all anxiety spectrum disorders share the same cognitive correlates, but are rather different in ways that do not link them to the hallmark of anxiety (higher sensitivity to negative feedback); and (b) perception of negative consequences is the core feature of GAD and SAD, but not PAD. ________________________________________ - Mark ___________________________________ Dr. Mark A. Gluck, Professor Center for Molecular & Behavioral Neuroscience Rutgers University ? Newark 197 University Ave. Newark, New Jersey 07102 Web: http://www.gluck.edu Email: gluck at pavlov.rutgers.edu Ph: ( 973) 353-3298 -------------- next part -------------- An HTML attachment was scrubbed... URL: From ted.carnevale at yale.edu Thu Oct 13 12:51:02 2016 From: ted.carnevale at yale.edu (Ted Carnevale) Date: Thu, 13 Oct 2016 12:51:02 -0400 Subject: Connectionists: High Performance Computing Workshop at SFN 2016 Message-ID: <28b8197d-26c5-36ab-ef86-0e9c3b6af18c@yale.edu> A few seats remain available in the workshop Using the Neuroscience Gateway Portal (NSG) for Parallel Simulations Saturday, Nov. 12 from 9 AM to noon which we are presenting in downtown San Diego as a satellite to this year's SFN meeting. This workshop will show you how to use this NSF-supported resource in your computationally-intensive modeling and data analysis projects. It will also feature presentations from several research teams about how they are using NSG in their own research. The registration fee is $25, but if you have already signed up for the NEURON course on Friday, Nov. 11, you may register for the NSG workshop for only $15. For a description of the workshop and its application form, see http://www.neuron.yale.edu/neuron/static/courses/nsg2016/nsg2016.html The registration deadline is Friday Oct. 28. --Ted From g.lever at cs.ucl.ac.uk Thu Oct 13 11:23:54 2016 From: g.lever at cs.ucl.ac.uk (guy lever) Date: Thu, 13 Oct 2016 16:23:54 +0100 Subject: Connectionists: Multi-Agent Workshop at NIPS - Call for submissions Message-ID: <57FFA70A.1000908@cs.ucl.ac.uk> NIPS 2016 Workshop on Learning, Inference and Control of Multi-Agent Systems 9 December 2016, Barcelona, Spain https://sites.google.com/site/malicnips2016 Submission deadline: 21 October 2016 Organizers: Thore Graepel, Marc Lanctot, Joel Leibo, Guy Lever, Janusz Marecki, Frans Oliehoek, Karl Tuyls Multi-agent learning is of crucial importance to the future of computational intelligence and poses difficult and fascinating problems that need to be addressed across disciplines. The paradigm shift from single-agent to multi-agent systems will be pervasive and will require efforts across different fields including machine learning, cognitive science, robotics, natural computing, and (evolutionary) game theory. In this workshop we aim to bring together researchers from these different fields to discuss the current state of the art, future avenues and visions for work regarding theory and practice of multi-agent learning, inference, and decision-making. 1. Call for Papers Authors can submit a 2-6 pages paper (excluding references) that will be reviewed by the organization committee. The papers can present new work or give a summary of recent work of the author(s). All papers will be considered for the poster sessions. Outstanding long papers (4-6 pages) will also be considered for a 20 minutes oral presentation. Topics considered for contribution include: * Multi-agent reinforcement learning * Deep multi-agent learning * Theory of Mind * Multi-agent communication * POMDPs, Dec-POMDPS and partially observable stochastic games * Multi-agent robotics, human-robot collaboration, swarm robotics * Game theory, mechanism design, algorithms for computing Nash equilibria and other solution concepts * Bioinspired approaches, swarm intelligence and collective intelligence * Co-evolution, evolutionary dynamics and culture * Ad hoc teamwork * Learning from demonstrations, apprenticeship learning, and inverse reinforcement learning Submissions can be madehere ; NB you will need an EasyChair account to do so. Please use the standard NIPS style-file for the submissions. Your submission should be anonymous, so please do not add the author names to the PDF. 2. Format The workshop will serve as a platform to bring researchers from the different relevant communities together and foster discussions about the next necessary developments for multi-agent systems. The workshop will consists of six invited talks, a few contributed talks and a poster session. 3. Confirmed Speakers * Chris Amato * Michael Bowling * Josh Tenenbaum * Manuela Veloso * Shimon Whiteson * Richard Watson 4. Program Committee * Daan Bloembergen * Sander Bohte * Chrisantha Fernando * Vicen? G?mez * Bert Kappen * Michael Littman * Gerhard Neumann * Ann Now? * Olivier Pietquin * Matt Taylor * Kagan Tumer * Gerhard Weiss -------------- next part -------------- An HTML attachment was scrubbed... URL: From osporns at indiana.edu Thu Oct 13 13:31:24 2016 From: osporns at indiana.edu (Sporns, Olaf) Date: Thu, 13 Oct 2016 13:31:24 -0400 Subject: Connectionists: Network Neuroscience Message-ID: <936da078-c801-6a67-55ce-2e6de6c6d951@indiana.edu> *NETWORK NEUROSCIENCE* A new MIT Press Journal: http://www.mitpressjournals.org/netn CALL FOR PAPERS Network Neuroscience aims to publish innovative scientific work that significantly advances our understanding of network organization and function in the brain across all scales, from molecules and neurons to circuits and systems. Positioned at the intersection of brain and network sciences, the journal covers empirical and computational studies that record, analyze or model relational data capturing connections and interactions among elements of neurobiological systems. Examples include neuronal signaling and information flow in circuits, patterns of functional connectivity recorded with electrophysiological or imaging methodology, studies of anatomical connections among neurons and brain regions, and interactions among biomolecules or genes. The journal aims to cover studies carried out in all neurobiological systems and all species, including humans. Articles addressing developmental, evolutionary, social and clinical/translational aspects of neurobiological networks as well as articles describing significant new network data, tools and methods are welcome. Network Neuroscience publishes Research, Methods, Data, Review and Perspective Articles. Editor: Olaf Sporns (Indiana University, USA) ? Senior Editors: Danielle Bassett (University of Pennsylvania, USA), Ed Bullmore (University of Cambridge, UK), Alex Fornito (Monash University, Australia), Dan Geschwind (UCLA, USA), Claus Hilgetag (UMC Hamburg Eppendorf, Germany) *NOW OPEN FOR SUBMISSIONS* (single pdf upload) - http://netneuro.edmgr.com/ -- Olaf Sporns -- @spornslab Department of Psychological and Brain Sciences Programs in Neuroscience and Cognitive Science Indiana University Bloomington, IN 47405 -------------- next part -------------- An HTML attachment was scrubbed... URL: From asymptotics at googlemail.com Thu Oct 13 19:29:27 2016 From: asymptotics at googlemail.com (Costas Anastassiou) Date: Thu, 13 Oct 2016 16:29:27 -0700 Subject: Connectionists: =?utf-8?q?Opening_in_computational_modeling_of_ce?= =?utf-8?q?llular_and_circuit_mechanisms_in_human_epilepsy_=E2=80=93_Allen?= =?utf-8?q?_Institute_for_Brain_Science?= In-Reply-To: <7E495256-CB1E-423F-840A-1D532DED597D@gmail.com> References: <7E495256-CB1E-423F-840A-1D532DED597D@gmail.com> Message-ID: Dear colleagues: I?d like to draw your attention to an opening in my lab (Scientist 2-level equivalent to senior postdoc) at the Allen Institute for Brain Science in Seattle (USA) focusing on computational modeling of cellular and circuit mechanisms in human epilepsy (please find the job ad attached below). While the position is computational, this is a joint computational-experimental effort in collaboration with in-house experimental colleagues, neurologists and neurosurgeons. This is part of an exciting new translational neuroscience effort at the Allen Institute. Interested parties can apply at this link under the position ?scientist II ? translational neuroscience?. Let me know if you have questions. Many thanks, Costas ? Costas Anastassiou Assistant Investigator T: 206.547.8434 E: costasa at alleninstitute.org alleninstitute.org Professor (adj.) of Neurology University of British Columbia, Vancouver BC, CA http://neuroscience.ubc.ca/people/Anastassiou Our mission at the Allen Institute for Brain Science is to accelerate the understanding of how the human brain works in health and disease. By implementing a team science approach on a large scale we strive to generate useful public resources, drive technological innovations and discover fundamental brain properties through integration of experiments, modeling and theory POSITION SUMMARY We are seeking to fill a position at the level of Scientist II to work on an exciting new translational neuroscience effort at the Institute focusing on cellular and circuit mechanisms of epileptogenesis in human hippocampus. To address these questions, computational modeling of the human epileptogenetic hippocampus will be pursued utilizing existing state-of-the-art modeling, simulation and visualization capabilities at the Institute (e.g. see [Schomburg, Anastassiou et al, J Neurosci, 2012; Reimann, Anastassiou et al, Neuron, 2013; Taxidis, Anastassiou et al, Neuron, 2015]). The aim is to understand how synaptic, cellular and connectivity properties of pathological brain tissue give rise to pathophysiological network dynamics, and identify intervention targets to suppress pathological activity. Importantly, the computational effort will occur in parallel with novel in vitro experiments in human brain slices derived from pharmacoresistant patients undergoing surgery for treatment of refractory mesial temporal lobe epilepsy. This effort will be pursued in collaboration with in-house experimental colleagues as well as neurologists and neurosurgeons. RESPONSIBILITIES Computational modeling of neurons and circuits. Design, implement and analyze large-scale network simulations. Publish/present findings in peer-reviewed journals/scientific conferences. Preparation of both written and oral reports on a regular basis. Maintain clear and accurate communication with supervisor and team members. QUALIFICATIONS PhD degree in computational neuroscience, physics, biology, bioengineering or related fields. Strong background in scientific computing; experience in computational neuroscience is preferred, but other strong applicants will be considered (with background in computational physics, biophysics, and related disciplines). Experience with parallel computing is a plus as well as familiarity with high-level programming languages such as python. Ability to meet aggressive timelines and deliverables in a collaborative environment. Strong publication record. Experience in pursuing research projects in collaborative fashion. Proven independent thinking and flexibility. Familiarity with in vitro and in vivo electrophysiological monitoring techniques and data analyses. Strong written and verbal communication skills. -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image001.png Type: image/png Size: 6905 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image002.png Type: image/png Size: 8067 bytes Desc: not available URL: From rogilmore at psu.edu Thu Oct 13 13:10:17 2016 From: rogilmore at psu.edu (Rick Gilmore) Date: Thu, 13 Oct 2016 13:10:17 -0400 Subject: Connectionists: Open science developer positions with Databrary.org Message-ID: ?The Databrary digital data library project based at NYU is seeking developers (front end and back end) who are interested in building infrastructure that fosters video data sharing, analysis, and reuse? in the social and behavioral sciences. Feel free to contact me with questions. Rick Gilmore Associate Professor, Penn State Co-Director, Databrary.org ========================================== FRONT END DEVELOPER @ DATABRARY POSITION SUMMARY The Databrary project is looking for a smart and motivated front end developer to join its technical team. The developer will combine the art of design with the art of programming and act as the primary owner of the user interaction and experience of our service. Working closely with the managing director, the PIs, the backend programmer and the service team, the developer will design, develop and modify tools, including web applications and interfaces as well as mobile apps to enable behavioral researchers to collaborate, store, discover, explore and access video-based research datasets. (S)he will maintain existing code base and build new features, enhancements and integrations in modern web frameworks. Databrary (databrary.org) is the leading open source video data-sharing system for developmental science. Datavyu (datavyu.org) is a free, open source, multi-platform video coding tool. This position provides a unique opportunity to play a central role in advancing open science through data sharing and reuse. The ideal candidate has a great design sense, is a self starter who is not afraid of learning new technologies, thinks out of the box, takes initiative, has excellent attention to detail and can work to bring tasks to fruition both collaboratively in a team and independently. The developer will adapt to the evolving and growing needs of the project. ESSENTIAL RESPONSIBILITIES/FUNCTIONS Documentation, research and evaluation. The developer will analyze and understand current application architecture and front end code base (written in AngularJS, CoffeeScript, Node.js), document it thoroughly and make recommendations to the managing director on future strategic directions. Design and development. The developer will maintain the existing website and application front end code base as well as troubleshoot bugs to improve application usability. (S)he will take lead of the redesign and upgrade effort of the current front end, define user experiences, build mockups, rapid prototype, test and QA end-to-end solutions. (S)he will develop and release dynamic, modular and responsive experiences by implementing clean, reusable, well-designed and well-tested code to add new enhancements, features and integrations to the current platform. Feedback and innovation. The applicant will work closely with UI experts and researchers (end users) in the field to understand usability issues. (S)he will be responsive to their feedback and become a force of innovation in designing new features to facilitate the collection, processing, describing, transformation, analysis, retention, and reuse of research data. S(he) will design, develop, implement, test and validate existing and new data management and web-based tools to facilitate research. PREFERRED SKILLS, KNOWLEDGE, AND ABILITIES - Hands-on experience with modern web frameworks and video technologies. - Knowledge of JavaScript, Angular2, ReactJS or other front end technologies. - Understanding of best practices in SDLC (Software Development Life Cycle). - Knowledge of HTML, CSS and UI and UX design principles. - Good understanding of security and cross browser design issues. - Understanding of TDD (Test driven development) and design patterns. - Experience with version control, unix scripting, automation and DevOps practices. - Familiarity with CRM, project management and task management systems. - Passion for open source projects and building high quality experiences. - Strong written and oral communication skills. - Superior listening and analytical skills and a knack for tackling tough problems. - Ability to multitask and juggle multiple priorities and projects. - Adaptability and openness to learn and change. REQUIRED EXPERIENCE - Track record of developing responsive websites in modern client side web frameworks. - Exceptional understanding of design principles, web technologies, REST API and MVC design patterns. - Extensive experience with JavaScript frameworks (CoffeeScript, AngularJS, ReactJS), HTML5 (audio/video API), and CSS3 (Stylus). - Basic knowledge of scientific practices and research tools. PREFERRED EDUCATION BS, or MS in Computer Science, Information Technology or relevant field. TO APPLY Send a one page cover letter (PDF) and resume (PDF) to jobs at databrary.org: We will review applications beginning immediately and consider candidates until the position is filled. For more information, visit our website at https://databrary.org/about/jobs.html. New York University is an Equal Opportunity Employer. New York University is committed to a policy of equal treatment and opportunity in every aspect of its hiring and promotion process without regard to race, color, creed, religion, sex, pregnancy or childbirth (or related medical condition), sexual orientation, partnership status, gender and/or gender identity or expression, marital or parental status, national origin, ethnicity, alienage or citizenship status, veteran or military status, age, disability, predisposing genetic characteristics, domestic violence victim status, unemployment status, or any other legally protected basis. Women, racial and ethnic minorities, persons of minority sexual orientation or gender identity, individuals with disabilities, and veterans are encouraged to apply for vacant positions at all levels. ========================================== BACK END DEVELOPER @ DATABRARY POSITION SUMMARY The Databrary project is looking for a smart, energetic and flexible back end developer to join its technical team. The developer will act as the primary owner of the code base of our service. Working closely with the managing director and the service team, the developer will design, develop and maintain tools to enable behavioral researchers to collaborate, store, discover, explore and access video-based research datasets. (S)he will maintain an existing code base and build new features, enhancements and integrations. Databrary (databrary.org) is the leading open source video data-sharing system for developmental science. Datavyu (datavyu.org) is the leading free, open source, multi-platform video coding tool. This position provides a unique opportunity to play a central role in advancing open science through data sharing and reuse. The ideal candidate is a self starter who is not afraid of learning new technologies, thinks out of the box, takes initiative, has excellent attention to detail and can work to take tasks to fruition both collaboratively in a team and independently. The developer will adapt to the evolving and growing needs of the project. ESSENTIAL RESPONSIBILITIES AND JOB FUNCTIONS Research and evaluation. The developer will analyze and understand current system and application architecture, logical and physical data models, security and storage implementation as well as the code base, document it thoroughly, formulate high level architectural and call graph diagrams and make recommendations to the managing director on a future strategic direction. Development and maintenance. The developer will maintain existing code base and troubleshoot to improve application reliability and performance. (S)he will lead development, manage releases, deploy code, and track bug and QA progress. (S)he will build dynamic, modular and responsive web applications by implementing clean, reusable, well designed and well tested code to add enhancements, features and new integrations to the platform in current technologies (Haskell, PostgreSQL, AngularJS) or any other secure, modern, sustainable web frameworks. Innovation in data management. The developer will work closely with experts in the field to understand the complete data lifecycle and management for researchers. (S)he will advocate for and become a force of innovation at each step of activities undertaken in relation to the collection, processing, description, transformation, retention and reuse of research data. (S)he will design, develop, implement, test and validate existing and new data management and web-based tools to facilitate research. PREFERRED SKILLS, KNOWLEDGE, AND ABILITIES - Hands-on experience with functional languages like Haskell, OCaml, F#, or Scala. - Knowledge of modern web frameworks in high-level languages such as Java, Ruby, Python or PHP and video technologies. - Knowledge of JavaScript, JS frameworks, HTML, CSS and other front end technologies. - Understanding of best practices in SDLC (Software Development Life Cycle). - Understanding of TDD (Test-driven development), security and design patterns. - Experience with version control, unix scripting, automation and DevOps practices. - Familiarity using CRM, project management and task management systems. - Passion for open source projects and building high quality software. - Strong written and oral communication skills. - Superior listening and analytical skills and a knack for tackling tough problems. - Ability to multitask and juggle multiple priorities and projects. - Adaptability and openness to learn and change. REQUIRED EXPERIENCE - Track record of designing scalable software for web applications in modern web frameworks. - Exceptional understanding of system architecture, object oriented principles, web technologies, REST API and MVC patterns. - Solid knowledge of SQL and RDBMS like PostgreSQL. - Basic knowledge of scientific practices and research tools, such as Matlab, SPSS, or R. PREFERRED EDUCATION BS, MS or Ph.D in Computer Science, Information Technology or other relevant field. TO APPLY Send a one page cover letter (PDF) and resume (PDF) to jobs at databrary.org: We will review applications beginning immediately and consider candidates until the position is filled. For more information, visit our website at https://databrary.org/about/jobs.html. New York University is an Equal Opportunity Employer. New York University is committed to a policy of equal treatment and opportunity in every aspect of its hiring and promotion process without regard to race, color, creed, religion, sex, pregnancy or childbirth (or related medical condition), sexual orientation, partnership status, gender and/or gender identity or expression, marital or parental status, national origin, ethnicity, alienage or citizenship status, veteran or military status, age, disability, predisposing genetic characteristics, domestic violence victim status, unemployment status, or any other legally protected basis. Women, racial and ethnic minorities, persons of minority sexual orientation or gender identity, individuals with disabilities, and veterans are encouraged to apply for vacant positions at all levels. -------------- next part -------------- An HTML attachment was scrubbed... URL: From avellido at lsi.upc.edu Thu Oct 13 05:11:50 2016 From: avellido at lsi.upc.edu (Alfredo Vellido) Date: Thu, 13 Oct 2016 11:11:50 +0200 Subject: Connectionists: CFP: IJCNN'17 Special Session: ML for ENHANCING BIOMEDICAL DATA ANALYSIS Message-ID: <6fe7d0e0-aaf8-9c6e-d085-68d5a12bc1aa@lsi.upc.edu> Apologies for cross-posting =================== 1st CALL FOR PAPERS =================== IEEE IJCNN 2017 Special Session on MACHINE LEARNING for ENHANCING BIOMEDICAL DATA ANALYSIS May 14-19, 2017, Anchorage, Alaska, USA. www.cs.upc.edu/~avellido/research/conferences/IJCNN2017-ssEnhancedBiomed.html Aims & Scope ------------ The pursuit of precision medicine has led to an explosive growth in the amount of data now available. Ever-increasing advances in technology and greater levels of granularity have also resulted in an increase in the amount of data and complexity of knowledge surrounding disease. The increased demand for skilled analysts in systems medicine and engineering has, unfortunately, outpaced the supply. In spite of these shortcomings, productivity in systems medicine and engineering is nevertheless growing. Results of these efforts will enable practitioners to improve diagnoses and treatments, and allow health care systems to better manage patients and reduce costs. Central Data analysis is also crucial to get closer to a real personalized medicine, one of the main goals of modern society in terms of healthcare. This special session aims at bringing together researchers from the fields of Biomedicine and Machine Learning (ML) in order to exploit the synergies between them, thus taking advantage of the modeling capabilities of ML and the expert knowledge in Biomedicine to make progresses truly relevant to the medical community by focusing on the solution of real problems, whose results hopefully lead to palpable enhancements in clinical routine practice and in increasingly personalized medicine. The proposal of any method useful for medical data analysis, even if it does not fall completely within ML (e.g., biostatistics or biomedical signal processing), is also welcome in this special session. In particular, we welcome papers which present novel algorithms or refined classical methods applied to biomedical problems. These include but are not limited to: - Proposals of new ML algorithms that outperform previous approaches in clinical problems. - Practical applications of computational intelligence and ML for mining health-related data. - Structure finding, including efficient derivation of directed graphs with applications to extract probabilistic graphical relationships between features in biomedical problems. - Integration of expert clinical knowledge in graphical models. - Methodologies for fusion of heterogeneous data: clinical tests, subjective assessments, molecular biomarkers, histology, imaging, electrophysiological measurements, etc. - Models of time-to-event data to characterize prognostic outcomes and treatment effects. - Methodologies for medical decision aid and treatment planning. - Telemedicine and proposals for a remote healthcare system. Important Dates --------------- Paper submission: November 15, 2016 Paper decision notification: January 20, 2017 Camera-ready submission: February 20, 2017 Session Chairs -------------- Jos? D. Mart?n-Guerrero (Universitat de Valencia, Spain) Paulo J.G. Lisboa (P.J.Lisboa at ljmu.ac.uk , Liverpool John Moores University, U.K.) Alfredo Vellido (Universitat Polit?cnica de Catalunya, Spain) Azzam F.G. Taktak (University of Liverpool, U.K.) Leif E. Peterson (Houston Methodist Biostatistics Core, TX, U.S.A.) From h.abbass at adfa.edu.au Fri Oct 14 03:52:55 2016 From: h.abbass at adfa.edu.au (Hussein Abbass) Date: Fri, 14 Oct 2016 07:52:55 +0000 Subject: Connectionists: =?windows-1252?q?A_prestigious_=93Scientia_PhD_Sc?= =?windows-1252?q?holarship=94_at_UNSW-Canberra=2C_Australia?= Message-ID: Scientia PhD Scholarship at UNSW-Canberra for 2017 The deadline for 2017 applications is 11th of November 2016 Topic: Can I Trust You, asked the AI: Learning Humans? Trustworthiness from EEG Description: Machine-intelligence is leaving the laboratory. The question of when an artificial intelligence agent/robot can trust a human is gaining a greater practical significance than ever before. This project will extend our work on EEG for human-machine teaming and trusted autonomous systems with novel real-time machine learning models to estimate a human?s trustworthiness level during the control of a swarm of robots. The project will use an augmented virtuality environment that streams a live swarm-robotics task inside a virtual environment operated by a human. You should have a degree in computer science, mathematics or electrical engineering, and an aptitude to innovate. About the Scientia Scholarship: UNSW Australia has launched a global drive to recruit 700 exceptional PhD students over the next 10 years. This prestigious scholarship offers $40,000 stipend per annum for four years. In addition, a travel and development support package up to $10,000. For International Students, the scholarship will also include a tuition scholarship which waves the fees. More Information: http://www.husseinabbass.net/ScientiaScholarship.htm Contact: Prof. Hussein Abbass at h.abbass at adfa.edu.au and cc hussein.abbass at gmail.com Prof. Hussein Abbass (Fellow ORS, Fellow ACS, Fellow AIM) | School of Engineering and Information Technology | University of New South Wales - Canberra at the Australian Defence Force Academy Campus | Canberra, ACT 2600, Australia | Web: http://www.husseinabbass.net/| Tel:+61-2-62688158 | Fax: +61-2-62688276 -------------- next part -------------- An HTML attachment was scrubbed... URL: From ab8556 at coventry.ac.uk Fri Oct 14 10:52:23 2016 From: ab8556 at coventry.ac.uk (Abdulrahman Altahhan) Date: Fri, 14 Oct 2016 14:52:23 +0000 Subject: Connectionists: IJCNN Special Session in Deep Reinforcement Learning In-Reply-To: References: Message-ID: Dear Colleagues we would like to cordially invite you to submit to the following special session in the coming IJCNN 2017 conference IEEE International Joint Conference on Neural Networks (IJCNN 2017) Special Session on: Deep and Reinforcement Learning (DRL) RL does not lend itself naturally to deep learning from an MDP framework perspective, and currently there is no uniformed approach to combine deep learning with realistic reinforcement learning despite very successful applications in virtual and gaming environments. Examples of important open questions are: - How to make the state-action learning process deep? - How to make the architecture of an RL system appropriate to deep learning without compromising the interactivity of the system? - How to make the learning suitable for a realistic scenario? - How to infuse a self-reflective process in the system? Although recently there have been important advances in dealing with these issues, they are still scattered and with no overarching framework that promote them in a well-defined and natural way. This special session will provide a unique platform for researchers from Deep Learning and Reinforcement Learning communities to share their research experience towards a uniformed Deep Reinforcement Learning (DRL) framework in order to allow this important interdisciplinary branch to take-off on solid grounds. It will touch on the potential benefits of the different approaches to combine RL and DL. The aim is to bring more focus onto the potential of infusing reinforcement learning framework with deep learning capabilities that could allow it to deal more effectively with present applications such as realistic robotics, online streamed data processing that involves actions. Contribution is invited from all deep learning, reinforcement learning and deep reinforcement learning research. Scope and Topics - Novel RL Techniques suitable for physical systems - Novel Deep and/or RL Algorithms - Novel Deep and RL Neural Architectures - Adaptation of existing RL Techniques for Deep Learning - Optimization and convergence proofs for DRL algorithms - Deeply Hierarchical RL - Deep and/or RL architecture and algorithms for Control - Deep and/or RL architecture and algorithms for Robotics - Deep and/or RL architecture and algorithms for Time Series - Deep and/or RL architecture and algorithms for Big Streamed Data Processing - Deep and/or RL architecture and algorithms for Optimizing Governmental Policy - Other Deep and/or RL theory and application... Important Dates - Paper submission: November 15, 2016 - Paper decision notification: January 20, 2017 - Camera-ready submission: February 20, 2017 Organizers Abdulrahman Altahhan(ab8556 at coventry.ac.uk), COVENTRY UNIVERSITY, UK. Vasile Palade, COVENTRY UNIVERSITY, UK. Roozbeh Razavi-Far, University of Windsor, Canada. -------------- next part -------------- An HTML attachment was scrubbed... URL: From costa at informatik.uni-freiburg.de Fri Oct 14 10:56:01 2016 From: costa at informatik.uni-freiburg.de (Fabrizio Costa) Date: Fri, 14 Oct 2016 16:56:01 +0200 Subject: Connectionists: [REMINDER & PRIZE]: NIPS 2016 Workshop on Constructive Machine Learning Message-ID: <784b74de-985e-5888-fa65-1a8d146bec46@informatik.uni-freiburg.de> Dear Colleagues, We are pleased to announce that the new edition of the Constructive Machine Learning workshop this year will be held at NIPS Barcelona, Spain, Sat Dec 10th. Please visit http://www.cs.nott.ac.uk/~psztg/cml/2016 for more details. Looking forward to seeing you there! Best Regards, Fabrizio Costa, Thomas G?rtner, Andrea Passerini, Fran?ois Pachet ============================================================== Call for Papers NIPS 2016 Workshop on Constructive Machine Learning (NIPS CML) http://www.cs.nott.ac.uk/~psztg/cml/2016 A workshop at the Twenty-Ninth Annual Conference on Neural Information Processing Systems (NIPS 2016) Barcelona, Spain Sat Dec 10th 08:00 AM -- 06:30 PM IMPORTANT DATES: ----------------------------------------------------------------------------------------------- Nov 3, 2016: Submission Deadline Nov 24, 2016: Acceptance Notification Dec 1, 2016: Final papers due Dec 10, 2016: Workshop date ============================================================== ABSTRACT: ----------------------------------------------------------------------------------------------- In many real-world applications, machine learning algorithms are employed as a tool in a ''constructive process''. These processes are similar to the general knowledge-discovery process but have a more specific goal: the construction of one-or-more domain elements with particular properties. In this workshop we want to bring together domain experts employing machine learning tools in constructive processes and machine learners investigating novel approaches or theories concerning constructive processes as a whole. Interesting applications include but are not limited to: image synthesis, drug and protein design, computational cooking, generation of art (paintings, music, poetry). Interesting approaches include but are not limited to: deep generative learning, active approaches to structured output learning, transfer or multi-task learning of generative models, active search or online optimization over relational domains, and learning with constraints. Many of the applications of constructive machine learning, including the ones mentioned above, are primarily considered in their respective application domain research area but are hardly present at machine learning conferences. By bringing together domain experts and machine learners working on constructive ML, we hope to bridge this gap between the communities. SUBMISSION INSTRUCTIONS: ----------------------------------------------------------------------------------------------- We welcome contributions on both theory and applications related to constructive machine learning problems. We also welcome submissions containing previously published content in fields related to machine learning, especially descriptions of real-world problems and applications. We welcome work-in-progress contributions, demo and position papers, as well as papers discussing potential research directions. Submission of previously published work or work under review is allowed. However, preference will be given to novel work or work that was not yet presented elsewhere. All double submissions must be clearly declared as such! Submissions will be reviewed on the basis of relevance, significance, technical quality, and clarity. All accepted papers will be presented as posters and among them a few will be selected for the oral presentation. Submissions should use the NIPS style file, with a maximum of 4 pages (excluding references). Accepted papers will be made available online at the workshop website, but the workshop proceedings can be considered non-archival. Submissions need not be anonymous. All papers should be submitted via easychair at the following link: https://easychair.org/conferences/?conf=cml2016 ** The winners of the best paper award will receive a new PS4Pro ** INVITED SPEAKERS AND PANELISTS: ----------------------------------------------------------------------------------------------- Ruslan Salakhutdinov (CMU, deep generative models) Thorsten Joachims (Cornell, coactive learning) Gisbert Schneider (ETH, de novo drug design) Simon Colton (Goldsmiths University of London, computational creativity) Douglas Eck (Google, music generation) Ross Goodwin (NYU ITP, computational creative writing) Florian Pinel (IBM, cognitive cooking) ORGANIZERS: ----------------------------------------------------------------------------------------------- Fabrizio Costa (University of Freiburg) Thomas Gaertner (University of Nottingham) Andrea Passerini (University of Trento) Francois Pachet (SONY Computer Science Laboratory Paris) From Roman.Bauer at newcastle.ac.uk Fri Oct 14 16:33:53 2016 From: Roman.Bauer at newcastle.ac.uk (Roman Bauer) Date: Fri, 14 Oct 2016 20:33:53 +0000 Subject: Connectionists: Reminder: Call for Abstracts - Computational Neurology Conference Message-ID: Reminder: Call for Abstracts Computational Neurology Conference 2017 This is a reminder for our invitation to submit abstracts for poster and oral presentations at the Computational Neurology conference in Newcastle upon Tyne (UK) on February 20-21, 2017. The deadline for abstract submission is 31 October 2016. The conference will gather international researchers and professionals interested in applying advances in computing and neuroscience for clinically relevant purposes. More information on the conference can be found on this website: http://conferences.ncl.ac.uk/compneurology/ Registration to the conference will be free, and lunch & refreshments will be provided. Authors of accepted abstracts will get the chance for a poster and oral presentation. The organizing committee will select submissions that will be given the opportunity to give a 20 min talk, and there will be a poster prize. We strongly encourage women and minority authors to send submissions. All accepted abstracts will be published online on the conference website. Currently confirmed speakers include: * Javier Escudero - Edinburgh * Marc Goodfellow - Exeter * Viktor Jirsa - Marseille * Marcus Kaiser - Newcastle * Dimitri Kullmann - University College London * Marco Manca - CERN * Florian Mormann - Bonn * Matthew Nolan - Edinburgh * Gregory Scott - Imperial College London * Evelyne Sernagor - Newcastle * Peter Uhlhaas - Glasgow Details for Abstract Submission: Deadline for abstract submission is October 31st, 2016. The length of the abstract should not exceed 250 words. In addition to the abstract, please add your contact information (name, degree/position and institution), and send these information by email to compneurology at ncl.ac.uk . Please note that the submission of an abstract does not replace the conference registration. Thanks and we are looking forward to welcoming you in Newcastle upon Tyne! On behalf of the organizers: Roman Bauer, Anupam Hazra, Luis Peraza Rodriguez, Peter Taylor, Yujiang Wang -- Roman Bauer, Ph.D. MRC Research Fellow Institute of Neuroscience Newcastle University Newcastle upon Tyne NE1 7RU, UK tel: +44 (0) 191 208 8933 -------------- next part -------------- An HTML attachment was scrubbed... URL: From nzhang at udc.edu Sat Oct 15 22:49:31 2016 From: nzhang at udc.edu (Zhang, Nian) Date: Sat, 15 Oct 2016 22:49:31 -0400 Subject: Connectionists: CFP: 14th International Symposium on Neural Networks (ISNN 2017) Message-ID: <32596A4A154B2442BF6312975C518D00048B8BAE180B@UDCMSGSTAFF-M.firebirds.udc.edu> The 14th International Symposium on Neural Networks (ISNN 2017), Sapporo, Hokkaido, Japan, June 21-23, 2017 Conference Website: https://conference.cs.cityu.edu.hk/isnn/ Following the successes of previous events, the 14th International Symposium on Neural Networks (ISNN 2017) will be held in Sapporo, Hokkaido, Japan. Located in northern island of Hokkaido, Sapporo is the fourth largest Japanese city and a popular summer/winter tourist venue. The Sponsors/Organizers are Hokkaido University and City University of Hong Kong. The Technical Co-sponsors are IEEE Computational Intelligence Society, International Neural Network Society, and Japanese Neural Network Society. The Publishers are Springer and Lecture Notes in Computer Science. ISNN 2017 aims to provide a high-level international forum for scientists, engineers, and educators to present the state of the art of neural network research and applications in related fields. The symposium will feature plenary speeches given by world renowned scholars, regular sessions with broad coverage, and special sessions focusing on popular topics. Call for Papers and Special Sessions Prospective authors are invited to contribute high-quality papers to ISNN 2017. In addition, proposals for special sessions within the technical scopes of the symposium are solicited. Special sessions, to be organized by internationally recognized experts, aim to bring together researchers in special focused topics. Papers submitted for special sessions are to be peer-reviewed with the same criteria used for the contributed papers. Researchers interested in organizing special sessions are invited to submit formal proposals to ISNN 2017. A special session proposal should include the session title, a brief description of the scope and motivation, names, contact information and brief biographical information of the organizers. Important Dates - Special session proposals: December 1, 2016 - Paper submission: January 1, 2017 - Notification of acceptance: February 1, 2017 - Camera-ready copy and author registration: March 1, 2017 - Conference: June 21-23, 2017 From r.jolivet at ucl.ac.uk Mon Oct 17 05:55:14 2016 From: r.jolivet at ucl.ac.uk (Jolivet, Renaud) Date: Mon, 17 Oct 2016 09:55:14 +0000 Subject: Connectionists: Fully funded postdoc position at the University of Geneva Message-ID: <51E8F8A4-BCC4-422C-8E33-823F84D19D62@ucl.ac.uk> The University of Geneva seeks one postdoc in computational neuroscience to investigate the relation between information transfer at synapses and in neural networks, and concomitant energy consumption. The starting date is May 2017. This position is fully funded by the Swiss National Science Foundation for 24 months. Initial appointment is for one year. Research will be conducted in the medical physics group of the physics section at the University of Geneva, under the supervision of Prof. Renaud Jolivet. * Summary Information transmission in the brain is energetically expensive, yet has to satisfy demands of speed and signal-to-noise reliability. We have recently shown that the strong retinogeniculate synapse relaying information from the retina to the thalamus resolves these competing constraints by maximizing energetic efficiency when transferring information. In their physiological state, these synapses are not set to transmit the maximum amount of information possible: information transmission increases when larger excitatory postsynaptic currents (EPSCs) are injected into the postsynaptic thalamic neuron. However, EPSCs that are larger or smaller than physiological EPSCs decrease the information transmitted per energy used. The physiological EPSC size therefore maximizes energy efficiency rather than pure information transfer across the synapse. In other words, the retinogeniculate synapse trades information for energy savings (http://dx.doi.org/10.1016/j.cub.2015.10.063; http://dx.doi.org/10.1016/j.neuron.2012.08.019). These findings suggest maximization of information transmission per energy used as a design principle in the brain. However, it is unclear how broadly this principle applies. Whether energy efficiency at excitatory synapses is a special property of strong relay synapses, or a more general principle also governing synaptic inputs that contribute more weakly to determining the output of the postsynaptic cell is an open question. These findings also raise the question of what mechanisms are in effect in order to achieve energetic efficiency of information transfer at synapses. This project will address these questions using information theory and simulations of biologically validated neuron models. Applicants must imperatively be self-sufficient programmers (MATLAB preferred) and have a strong background in computational neuroscience. They should be familiar with several of the following topics: information theory, Hodgkin-Huxley models, the NEURON simulation environment, signal processing, models of synaptic plasticity, models of neural networks. Please contact renaud.jolivet at unige.ch for additional information. * About the University of Geneva (UNIGE) UNIGE is a generalist French-speaking university located in Geneva, Switzerland. The QS World University Rankings 2016 and Times Higher Education World University Rankings 2016/17 respectively rank UNIGE as 95th and 131st worldwide. It ranks 41st worldwide for science (Shanghai Academic Ranking of World Universities in Natural Sciences and Mathematics 2016). It is Switzerland?s second largest university with more than 17000 students of 150 different nationalities and about 4000 researchers of 113 nationalities, who study and work in 9 different faculties. UNIGE trains a large number of PhD students and postdocs in neuroscience. The various research and teaching activities are listed at http://neurocenter.unige.ch/ and at https://www.unil.ch/ln/en/home.html. UNIGE is also developing with other institutions a new campus in Geneva (http://www.campusbiotech.ch/en/), focusing heavily on neuroscience and translational research. Geneva is at the heart of a conurbation with more than 1.25 million inhabitants. It is a global city, a financial center, and worldwide center for diplomacy and research. It has one of the highest quality of life in the world. It offers varied cultural activities and outdoor opportunities being located at one extremity of Lake Geneva, one of the largest lakes in Europe, on the western doorstep of the Alps. The University of Geneva offers competitive salaries and conditions at all levels in a young, dynamic, and multicultural environment. It is an equal opportunity employer and women are encouraged to apply. The official language of the laboratory is English. * How to apply Please send an e-mail to renaud.jolivet at unige.ch with your resume, list of publications, a one-page statement describing your research interests and career plan, and the names of at least three references. ? Prof. Renaud Jolivet CERN, Experimental Physics Department & University of Geneva, Physics Section +41 22 767 24 70 (CERN) +41 22 379 62 75 (UNIGE) +41 79 830 21 29 (mobile) renaud.blaise.jolivet at cern.ch https://sites.google.com/site/renaudjolivet/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From jamesdukephd at gmail.com Mon Oct 17 06:17:10 2016 From: jamesdukephd at gmail.com (James Duke) Date: Mon, 17 Oct 2016 13:17:10 +0300 Subject: Connectionists: Fwd: Building tools that can measure the mind In-Reply-To: References: Message-ID: Dear all, The ones of you interested in psychology and cognitive neuroscience, there is a great opportunity to participate in a Q&A session together with Dr. Joel Pearson (UNSW | School of Psychology). The session is based on his TEDx speak: "Hacking Psychology to Measure the Mind " *What is this video and Q&A about:* How can we accurately get information from people about their mind? Do we really say what we think? Can we build a tool to measure the mind? Yes. "Illusions are the microscopes of the mind." - claims Dr. Joel Pearson (UNSW | School of Psychology) *How to participate:* Visit his Ask Me More page here Watch his presentation video. And post your questions. He will be there to answer between *November 2nd - 3rd.* Br, James Duke -------------- next part -------------- An HTML attachment was scrubbed... URL: From daniele.marinazzo at ugent.be Mon Oct 17 08:29:33 2016 From: daniele.marinazzo at ugent.be (Daniele Marinazzo) Date: Mon, 17 Oct 2016 14:29:33 +0200 Subject: Connectionists: BrainModes Conference - Brussels Dec 1 and 2 - final call for abstracts Message-ID: Dear all Just a reminder and the final call for submitting an abstract for the poster presentation which will take place during the dinner at the BrainModes conference, that this year we will organize in Brussels, at the Royal Flemish Academy of Sciences (KVAB) on* Dec 1 and 2*. BrainModes (www.brainmodes.org) is an annual conference in which methods and models to interpret brain activity, and their applications are discussed. This year the theme will be: Coordinated brain activity: foundations and applications. We are proud of the lineup of speakers this year, including top experts in the field of computational, cognitive and clinical neuroscience. There will be also a workshop organized in Ghent on November 30 on methodological issues and demonstrations. The complete program, the info on registration, abstract submission and location are here http://www.da.ugent.be/brainmodes Please spread this information within your network of students and colleagues, and looking forward to see you. -- Daniele Marinazzo -- Department of Data Analysis Faculty of Psychology and Pedagogical Sciences, Ghent University Henri Dunantlaan 1, B-9000 Ghent, Belgium +32 (0) 9 264 6375 http://users.ugent.be/~dmarinaz/ https://twitter.com/dan_marinazzo BRAINMODES 2016 CONFERENCE http://www.da.ugent.be/brainmodes http://helpdesk.ugent.be/e-maildisclaimer.php -- Daniele Marinazzo -- Department of Data Analysis Faculty of Psychology and Pedagogical Sciences, Ghent University Henri Dunantlaan 1, B-9000 Ghent, Belgium +32 (0) 9 264 6375 http://users.ugent.be/~dmarinaz/ https://twitter.com/dan_marinazzo BRAINMODES 2016 CONFERENCE http://www.da.ugent.be/brainmodes http://helpdesk.ugent.be/e-maildisclaimer.php -------------- next part -------------- An HTML attachment was scrubbed... URL: From shelie at purdue.edu Mon Oct 17 09:31:50 2016 From: shelie at purdue.edu (Sebastien Helie) Date: Mon, 17 Oct 2016 09:31:50 -0400 Subject: Connectionists: Call for an Associate Editor Message-ID: Call for an Associate Editor The Quantitative Methods for Psychology (TQMP.org, ISSN: 2292-1354, doi prefix 10.20982) is seeking an Associate Editor, starting in March 2017 for a 3-year appointment. TQMP publishes papers describing quantitative methods for all areas of psychology and related disciplines. Many articles are tutorials but new and innovative techniques are also published in the journal. TQMP also publishes replications studies and companion articles. All TQMP papers are open access (Sherpa RoMEO code green). Job description The Associate Editor will process articles received for consideration to TQMP by reading the manuscript, finding reviewers if needed, and writing action letters. The Associate Editor may also be invited to take on additional projects such as drafting and disseminating calls for special issues. The Associate Editor will work with the Editor, Denis Cousineau. The position is for 3 years (including a 6-months probationary period). Applicants must have a position relevant to research in quantitative methods and psychology and have experience publishing articles. The Associate Editor must have a strong and demonstrable interest in quantitative methods and have published some papers on that subject. Having published in TQMP in the past is an asset but is not mandatory. Main Duties & Responsibilities 1. To engage in detailed editing of manuscripts submitted to the journal. The main purpose of TQMP is the transfer of technical knowledge and therefore, clarity of exposition must receive a strong focus from the Associate Editor. The Associate Editor may expect to receive one or two new manuscripts per month. A successful manuscript typically requires two rounds before it is accepted and is typically reviewed by two experts at least once. The rejection rate is currently 33%, 20% being rejected before being sent for reviews. An Associate Editor must be able to write clear action letters, summarizing the reviewers? main concerns as well as his or her own. The action letters must be constructive, so that the authors receive specific and detailed orientations. 2. The Associate Editor will also contact PsycINFO to engage the process by which TQMP will be indexed in this database. TQMP is already indexed by the Directory of Open Access Journals (DOAJ.org) and by CROSSREF through doi numbers. It is also member of the Open-Access Scholarly Publishers Association (OASPA.org). Rate of Pay All Editors of TQMP are unpaid volunteers. Application Please email the following items to Denis.Cousineau at uottawa.ca. ? A short cover letter with your statement of interest ? A copy of your CV ? A sample of relevant articles published on quantitative methods or where quantitative methods play an important role in the article. Closing Date 15th of December, 2016 For more information, contact Denis Cousineau, Editor, at denis.cousineau at uottawa.ca. -- ----------------------------------------------------------------- Sebastien Helie, Ph.D. Associate Professor of Psychological Sciences Associate Director of the Purdue Life Sciences Imaging Facility Co-Director of CEREBBRAL -- Department of Psychological Sciences Purdue University 703 Third Street West Lafayette, IN 47907-2081 -- Office: Peirce Hall, Room 359 Phone: (765) 496-2692 E-mail: shelie at purdue.edu Website: http://ccn.psych.purdue.edu/ ---------------------------------------------------------------- From Nicolas.Rougier at inria.fr Tue Oct 18 13:09:59 2016 From: Nicolas.Rougier at inria.fr (Nicolas P. Rougier) Date: Tue, 18 Oct 2016 19:09:59 +0200 Subject: Connectionists: Call for replication Message-ID: Dear all, ReScience (http://rescience.github.io) now accepts suggestions for replication. If you want to suggest a (computational) article for a replication, just open a new issue and give the reference of the original article and possibly the reason you would like to see this article replicated (for example, I tried myself and did not success). Please refrain from suggesting your own work. Note that you're also encouraged to register as a reviewer such that you can review the replication you've been proposing if someone actually takes up the challenge. The issue will be closed once someone declares he/she will do (or try to do) the replication. More information at: https://github.com/ReScience/call-for-replication Direct link for suggesting a replication: https://github.com/ReScience/call-for-replication/issues/new Nicolas P. Rougier From martaruizcostajussa at gmail.com Wed Oct 19 12:16:13 2016 From: martaruizcostajussa at gmail.com (Marta Ruiz) Date: Wed, 19 Oct 2016 18:16:13 +0200 Subject: Connectionists: 2nd Call for papers: special session on "Deep and kernel methods: best of two worlds" at ESANN 2017 Message-ID: Call for papers: special session on "Deep and kernel methods: best of two worlds" at ESANN 2017 European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2017) *26-28 April 2017*, Bruges (Belgium) Multilayer neural networks have experienced a rebirth in the data analysis field, displaying impressive results, extending even to classical artificial intelligence domains, such as game playing, computer vision, natural language and speech processing. The versatility of such methods have lead deep (semi)-parametric models to get over well-established learning methods, like kernel machines or classical statistical techniques. However, their training is a delicate and costly optimization problem that raises many practical challenges. On the other hand, kernel methods usually involve solving a tractable convex problem and are able to handle non-vectorial data directly, leading to a higher expressive power. Their main drawback is arguably their complexity being dependent on the number of data points, both at training and model evaluation times. A natural and emerging field of research is given by their hybridization, which can done in many fruitful ways. Many ideas from the deep learning field can be transferred to the kernel framework and viceversa. This special session aims at all aspects of deep architectures, be theoretical or methodological developments, comparative analyses, or applications. A special emphasis is given to new ideas to bridge the gap between the fields of deep and kernel learning, as well as the understanding of their respective weak and strong points. The topics of the session include, but are not limited to, - Applications of deep architectures in data representation and analysis, including structured or non-vectorial inputs or outputs - Natural language and speech processing; structured relationships among data; scalability/efficiency of deep neural networks and large-scale kernel machines - Heterogeneous data and meta-data; applications in neuroscience, computer vision, (bio)acoustic signals and mechanisms - Statistical or stability analysis, visualization of learning, generalization bounds - Novel deep(er) architectures/algorithms for data representation and learning (using kernels or not) - Recursive and iterative kernels and their relation to deep neural architectures - Emulation of multilayer machines by shallow architectures and vice versa - Randomized (approximate) feature maps to scale-up kernel methods - Derivation of efficient layer-by-layer algorithms for training such networks; reductions in the computational complexity - Comparisons of deep architectures to shallow architectures SUBMISSION INFO Submitted papers will be reviewed according to the ESANN reviewing process and evaluated on their scientific value: originality, technical correctness, and clarity. Tutorial-like contributions are also welcome provided they add a new perspective on the field. IMPORTANT DATES: Paper submission deadline : 19 November 2016 Notification of acceptance : 31 January 2017 ESANN conference : 26-28 April 2017 ORGANISERS Llu?s A. Belanche, Marta R. Costa-juss? Universitat Polit?cnica de Catalunya (Barcelona, Spain) -------------- next part -------------- An HTML attachment was scrubbed... URL: From dengdehao at gmail.com Thu Oct 20 01:12:29 2016 From: dengdehao at gmail.com (Teng Teck Hou) Date: Thu, 20 Oct 2016 13:12:29 +0800 Subject: Connectionists: [IJCNN 2017] NEW deadline for Workshop and Tutorial is Sunday, 30th October 2359hr UTC-10 Message-ID: <007801d22a90$91baa070$b52fe150$@gmail.com> [Apologies for cross-postings] International Joint Conference on Neural Networks May 14-19, 2017, Anchorage, Alaska, USA http://www.ijcnn.org/ ##################### Important Announcement ###################### Deadline for submitting Workshop and Tutorial proposal has been extended till October, 30. ##################### Important Dates ###################### * Tutorial and Workshop Proposals October 30, 2016 (Extended) * Paper Submission November 15, 2016 * Paper Decision Notification January 20, 2017 * Camera-Ready Submission February 20, 2017 CALL FOR WORKSHOPS http://www.ijcnn.org/call-for-workshops CALL FOR TUTORIALS http://www.ijcnn.org/call-for-tutorials CALL FOR PAPERS http://www.ijcnn.org/call-for-papers UPCOMING DEADLINES 2359hr UTC-10 on Saturday, 30 OCTOBER 2016] ############################################################# The 2017 International Joint Conference on Neural Networks (IJCNN 2017) will be held at the William A. Egan Civic and Convention Center in Anchorage, Alaska, USA, May 14-19, 2017. The conference is organized jointly by the International Neural Network Society and the IEEE Computational Intelligence Society, and is the premiere international meeting for researchers and other professionals in neural networks and related areas. It will feature invited plenary talks by world-renowned speakers in the areas of neural network theory and applications, computational neuroscience, robotics, and distributed intelligence. In addition to regular technical sessions with oral and poster presentations, the conference program will include special sessions, competitions, tutorials and workshops on topics of current interest For the latest updates, follow us on Facebook (https://fb.me/ijcnn2017/) and Twitter (@ijcnn2017). ########################## Call for Workshops ########################## Post-conference workshops offer a unique opportunity for in-depth discussions of specific topics in neural networks and computational intelligence. The workshops should be moderated by scientists or professionals who has significant expertise and /or whose recent work has had a significant impact within their field. IJCNN 2017 will emphasize emerging and growing areas of computational intelligence. Each workshop has a duration of 3 or 6 hours. The format of each workshop will be up to the moderator, and can include interactive presentations as well as panel discussions among participants. These interactions should highlight exciting new developments and current research trends to facilitate a discussion of ideas that will drive the field forward in the coming years. Workshop organizers can prepare various materials including handouts or electronic resources that can be made available for distribution before or after the meeting. Researchers interested in organizing workshops are invited to submit a formal proposal including the following information as a single file (pdf, doc, etc.) to the workshop chair: * Title * Organizers and their short bio * Brief description of the scope and impact of the workshop * Timeliness of the topic * Confirmed and/or potential speakers * Half day (3 hours) or full day (6 hours) * Link to organizer's web page and/or workshop web site (optional) For further details, please refer http://www.ijcnn.org/call-for-workshops. Any questions regarding this proposal can be asked to the Workshop Chair: Lazaros Iliadis, Democritus University of Thrace, Greece. E-mail: liliadis at fmenr.duth.gr ########################## Call for Tutorials ########################## IJCNN 2017 will feature pre-conference tutorials addressing fundamental and advanced topics in computational intelligence. Tutorial proposals should be emailed to the Tutorial Chair (see below). A tutorial proposal should include the * Title * Presenter/organizer name(s) and affiliations * Expected enrollment * Abstract (less than 300 words) * Additional outline if needed * Presenter/organizer biography * Links to the presenter/organizer web page or the tutorial page (optional) * The proposal should not exceed two pages in 1.5 space, Times 12 point font. The tutorial format (preliminary) is 1 hour and 45 minutes with a 10-minute break. Researchers interested in organizing workshops are invited to submit a formal proposal. For further details, please refer to http://www.ijcnn.org/call-for-tutorials. Any questions regarding this proposal can be asked to the Tutorials Chair: Asim Roy, Arizona State University, USA. E-mail: ASIM.ROY at asu.edu #################### Paper Submission is now Open #################### http://www.ijcnn.org/call-for-papers * Regular paper can have up to 8 pages in double-column IEEE Conference format * All papers are to be prepared using IEEE-compliant Latex or Word templates on paper of U.S. letter size. * All submitted papers will be checked for plagiarism through the IEEE CrossCheck system. * Papers with significant overlap with the authors own papers or other papers will be rejected without review. ##################### Topics and Areas of Interest ####################### The range of topics covered include, but is not limited to, the following. (See http://ijcnn.org for a more detailed list of topics). . Deep learning . Neural network theory & models . Computational neuroscience . Cognitive models . Brain-machine interfaces . Embodied robotics . Evolutionary neural systems . Neurodynamics . Neuroinformatics . Neuroengineering . Hardware, memristors . Neural network applications . Machine perception (vision, speech, ...) . Social media . Big data . Pattern recognition . Machine learning . Collective intelligence . Hybrid systems . Self-aware systems . Data mining . Sensor networks . Agent-based systems . Computational biology . Bioinformatics . Artificial life . Connectomics . Philosophical issues ################## Organizing Committee ###################### The full organizing committee can be found at: http://www.ijcnn.org/organizing-committee General Chair * Yoonsuck Choe, Texas A and M University, USA Program Chair * Christina Jayne, Robert Gordon University, UK Technical Co-Chairs * Irwin King, The Chinese University of Hong Kong, China * Barbara Hammer, University of Bielefeld, Germany ##################Sponsoring Organizations################## * INNS - International Neural Network Society * IEEE - Computational Intelligence Society * BSCS - Budapest Semester in Cognitive Science -------------- next part -------------- An HTML attachment was scrubbed... URL: From jose at rubic.rutgers.edu Wed Oct 19 16:48:37 2016 From: jose at rubic.rutgers.edu (Stephen Jose Hanson) Date: Wed, 19 Oct 2016 16:48:37 -0400 Subject: Connectionists: NIH Postdoc position Message-ID: <1476910117.4391.50.camel@rubic.rutgers.edu> Please see attachment. 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 -------------- A non-text attachment was scrubbed... Name: postdoc-ad.pdf Type: application/pdf Size: 75596 bytes Desc: not available URL: From t.hospedales at ed.ac.uk Wed Oct 19 16:11:20 2016 From: t.hospedales at ed.ac.uk (Timothy Hospedales) Date: Wed, 19 Oct 2016 21:11:20 +0100 Subject: Connectionists: CFP: Special Issue on Deep Learning in Computer Vision - IET Computer Vision Message-ID: Call For Papers: Special Issue on Deep Learning in Computer Vision - IET Computer Vision Aims and Scope The goal of IET-CV Special Issue on Deep Learning in Computer Vision is to accelerate the study of deep learning algorithms in computer vision problems. In 2012, deep learning became a major breakthrough in the computer vision community by outperforming, by a large margin, classical computer vision methods on ILSVRC challenge. Since then, it has been enjoying increasing popularity, growing into a de facto standard and achieving state-of-the-art performance in a large variety of tasks, such as object detection, image captioning and semantic segmentation. In this special issue, we encourage researchers to formulate original models and potential novel applications of end-to-end vision systems based on deep learning. We are soliciting original contributions or extensions of conference papers that address a wide range of theoretical and practical issues including, but not limited to: ? Large scale image and video understanding with deep models ? Learning with limited data, trends and training strategies ? Supervised learning in computer vision ? Unsupervised feature learning and feature selection ? Generative models ? Attention models and memory networks ? Reinforcement learning ? Model compression for mobile platforms and embedded systems ? Transfer learning ? Industrial and medical applications ? Real time applications Submission Instructions Papers should be submitted electronically using the IET ManuscriptCentral . Preparation of the manuscript must follow the IET Guide for Authors . To ensure that all manuscripts are correctly identified for inclusion into the special issue, it is important to select SI: Deep Learning in Computer Vision when you reach the ?Article Type? step in the submission process. Important Dates ? Submission deadline: 15th December 2016 ? First round decisions: 15th March 2017 ? Revisions deadline: 01th May 2017 ? Final round decisions: 31th July 2017 ? Publication: October 2017 Guest Editors Timothy Hospedales, University of Edinburgh, UK (t.hospedales at ed.ac.uk ) Adriana Romero, Montreal Institute of Learning Algorithms, Canada (adriana.romero.soriano at umontreal.ca ) David Vazquez, Autonomous University of Barcelona & CVC, Spain (dvazquez at cvc.uab.es ) -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- An embedded and charset-unspecified text was scrubbed... Name: not available URL: From dayan at gatsby.ucl.ac.uk Thu Oct 20 08:51:39 2016 From: dayan at gatsby.ucl.ac.uk (Peter Dayan) Date: Thu, 20 Oct 2016 13:51:39 +0100 Subject: Connectionists: Gatsby Unit PhD programme Message-ID: <20161020125139.GA9577@gatsby.ucl.ac.uk> Gatsby Computational Neuroscience Unit Training in theoretical and computational neuroscience and machine learning. Deadline: 15th November 2016. The Gatsby Unit is a centre for theoretical neuroscience and machine learning, focusing on unsupervised, semi-supervised and reinforcement learning, neural dynamics, population coding, Bayesian analysis, kernel methods, and deep learning; together with applications of these to the analysis of perceptual processing, neural data, signal processing, machine vision and bioinformatics. It provides a unique opportunity for a critical mass of theoreticians to interact closely with each other, with the Sainsbury Wellcome Centre for Neural Circuits and Behaviour (SWC, with which the Unit shares a new, purpose-designed building), with the cross-faculty Centre for Computational Statistics and Machine Learning (CSML), and with other world-class research groups in related departments at UCL, including: Computer Science; Functional Imaging;Neuroscience, Physiology and Pharmacology; Psychology; Neurology; Ophthalmology; The Ear Institute; Statistical Science; and the nearby Alan Turing Institute. Students at the Gatsby Unit study toward a PhD in either machine learning or theoretical neuroscience, with minor emphasis in the complementary field. Courses in the first year, taught in conjunction with colleagues from the SWC and CSML, provide a comprehensive introduction to theoretical and systems neuroscience and to machine learning; with further multidisciplinary training in other areas of neuroscience also available. Students are encouraged to work and interact closely with peers and faculty in the SWC and CSML throughout their PhD, providing a uniquely multidisciplinary research environment. Projects involving collaboration within or outwith UCL are welcome. The Unit has openings for exceptional PhD candidates. Applicants should have a strong analytical background, a keen interest in neuroscience and/or machine learning and a relevant first degree, for example in Computer Science, Engineering, Mathematics, Neuroscience, Physics, Psychology or Statistics. The PhD programme lasts four years, including the first year of intensive instruction in techniques and research in theoretical and systems neuroscience and machine learning. All students are fully funded, regardless of nationality. The Unit also welcomes applications from students with pre-secured funding or who are currently soliciting other scholarship/studentships. Applications (including a CV, statement of research interests, and letters from three referees) for 2017/18 admission must be sent directly to the Gatsby Unit admissions at gatsby.ucl.ac.uk. Applications must be completed by 15th November 2016. We will review applications as soon as they are complete (including a CV, statement of research interests and letters from three referees) until the positions are filled. Early application is thus advised. Full details of our programme, and how to apply, are available at: http://www.gatsby.ucl.ac.uk/teaching/phd For further details of research interests please see http://www.gatsby.ucl.ac.uk/research.html and the individual faculty webpages at http://www.gatsby.ucl.ac.uk/members.html If you require a visa to attend an interview, if selected, then please contact us directly as soon as your application is complete and your referees have submitted their recommendations. From osporns at indiana.edu Thu Oct 20 15:23:10 2016 From: osporns at indiana.edu (Sporns, Olaf) Date: Thu, 20 Oct 2016 15:23:10 -0400 Subject: Connectionists: NetSci 2017 - Call for Abstracts/Satellites Message-ID: <400313a7-b29e-0dad-7bb9-474ea929038a@indiana.edu> *NETSCI 2017 CALL FOR SATELLITE PROPOSALS AND ABSTRACTS* International School and Conference on Network Science June 19-23, Indianapolis, IN (JW Marriott Indianapolis) | http://netsci2017.net * * *SUBMISSION DEADLINES* December 15, 2016: Deadline for Satellite Symposia proposals January 15, 2017: Deadline for abstract submission of oral presentations, lightning talks, and posters March 1, 2017: Deadline for Erd?s?R?nyi Prize nomination *ABOUT NETSCI 2017* NetSci 2017, the International School and Conference on Network Science, will be held in Indianapolis, Indiana from June 19 to 23, 2017. NetSci 2017 aims to bring together leading researchers and practitioners working in the emerging area of network science. The conference fosters interdisciplinary communication and collaboration in network science research across computer and information sciences, physics, mathematics, statistics, the life sciences, neuroscience, environmental sciences, social sciences, finance and business, arts and design. NetSci 2017 is a combination of: - Satellite Symposia (June 19 & 20) - An International School for students and non-experts (June 19 & 20) - A 3-day Conference (June 21-23) featuring research in a wide range of topics and in different formats, including keynote and invited talks, oral presentations, posters, and lightning talks. *SATELLITE SYMPOSIA: CALL FOR PROPOSALS* Following the successful tradition of this conference, NetSci 2017 will host several Satellite Symposia on June 19 and 20 as precursors of the main Conference. These satellite events are one-day or half-day meetings with a focus on a specific topic of Network Science and its Applications. All subjects are welcome, but we would specifically support proposals on themes such as: Multilayer, Interdependent and/or Temporal Networks, Critical Infrastructures, Financial Networks, Biological Networks, Brain Networks, and Computational Social Sciences. Details for proposals, due December 15, can be found here: http://netsci2017.net/call/satellites *CALL FOR ABSTRACTS* To submit an abstract for an a oral presentation (15 mins, with 5 minute Q&A), lightning talk (5 mins), or poster, please prepare a one-page abstract including one mandatory descriptive figure and caption plus three keywords. The deadline for submission is Friday, January 15, 2017, with decisions issued by March 1. The abstract submission portal will be live on November 1, and will be available here: http://netsci2017.net/call/abstracts. You must use one of the two provided templates for preparing your abstract, also available at that page. *ERD?S?R?NYI PRIZE * The Erd?s?R?nyi Prize is awarded each year to a selected young scientist (under 40 years old on the day of the nomination deadline) for their achievements in research activities in the area of network science, broadly construed. While the achievements can be both theoretical and experimental, the prize is aimed at emphasizing outstanding contributions relevant to the interdisciplinary progress of network science. Candidate dossiers are due March 1, 2017 and self-nominations are not accepted. Details can be found at: http://netsci2017.net/erdos-renyi. SATELLITE CO-CHAIRS: R?ka Albert (Pennsylvania State University) & Filippo Radicchi (Indiana University Bloomington) PROGRAM COMMITEE CO-CHAIRS: Yong-Yeol Ahn (Indiana University Bloomington), Ciro Cattuto (ISI Foundation) & Tina Eliassi-Rad (Northeastern University) CONFERENCE CO-CHAIRS: Fil Menczer and Olaf Sporns (Indiana University Bloomington) /NetSci 2017 is hosted by the Indiana University Network Science Institute (http://iuni.iu.edu). It is the annual meeting of the Network Science Society (http://www.netscisociety.net)./ // /Questions? Email netsci17 at iu.edu and http://netsci2017.net / /Follow us on Twitter and Facebook: @NetSci2017/ -- Olaf Sporns -- @spornslab Department of Psychological and Brain Sciences Programs in Neuroscience and Cognitive Science Indiana University Bloomington, IN 47405 -------------- next part -------------- An HTML attachment was scrubbed... URL: From eliassi at cs.wisc.edu Fri Oct 21 03:36:07 2016 From: eliassi at cs.wisc.edu (Tina Eliassi-Rad) Date: Fri, 21 Oct 2016 03:36:07 -0400 Subject: Connectionists: Postdoc Position in Data and Network Sciences Message-ID: Postdoc Position in Data and Network Sciences A postdoctoral position is available for an outstanding individual to conduct research at the intersection of data and network sciences. The project involves research on network embedding, models of networked phenomena that are both predictive and descriptive, and enhancing incomplete networks. The mentor for this position is Professor Tina Eliassi-Rad at the Northeastern University?s Network Science Institute and College of Computer and Information Science in Boston, MA. Qualifications: * A recent Ph.D. in Computer Science, Network Science, Information Science, Statistics, or related fields. * Expertise in data mining and machine learning. * Experience working with complex networks. * Strong programming skills in Python, C, or Java, and R or MATLAB. Start date: January 9, 2017 Salary: Commensurate with experience. Duration: One year with the possibility of renewal for a second year. Deadline: The initial review date is November 15, 2016 (but sooner is better). Position will remain open until filled. Application: 1. Please email a cover letter and your curriculum vitae to t.eliassirad at northeastern.edu as one single PDF file; and make sure to include the string "[DNSci Postdoc]" at the beginning of your subject line. 2. Arrange for two letters of recommendation to be sent directly to t.eliassirad at northeastern.edu. From m.reske at fz-juelich.de Fri Oct 21 05:43:34 2016 From: m.reske at fz-juelich.de (Martina Reske) Date: Fri, 21 Oct 2016 11:43:34 +0200 Subject: Connectionists: Open position in Juelich, Germany: Data Analyst at Postdoctoral Level in Computational and Systems Neuroscience Message-ID: The Institute of Neuroscience and Medicine (INM) at Research Center J?lich, Germany, investigates the structure and function of the human brain on different spatial and temporal scales within the research program ?Decoding the Human Brain?. The organizational unit INM-6, Computational and Systems Neuroscience (www.csn.fz-juelich.de), develops mathematical models of neuronal dynamics and function. Model-driven analyses of brain activity and structure as well as simulation of biologically realistic models form the core of our work. The team Statistical Neuroscience develops statistical methods for the analysis of massively parallel experimental electrophysiological data and drives the development of the open source software tools for the analysis of electrophysiological data (e.g. Elephant). This team is seeking a data analyst at postdoctoral level for the workpackage WP4.5 "Linking Model Activity and Function to Experimental Data" of the EU flagship project Human Brain Project (HBP). The goal of the workpackage is to investigate mathematical principles and theoretical methods for integrating neuroscience data into models, and for comparing the results of the models with the existing data. Model predictions will in turn be used to suggest new experiments. The candidate will intensely collaborate with modelers and experimentalists, both within the institute as well as within the Human Brain Project. Task 4.5.1 in particular will develop strategies, principles and algorithms allowing comparative assessment of experimental data and different model approaches at different scales and description levels. Hence, it is the goal of this exciting project to get a better understanding of the neuronal processes by working in ?integrative loops? of model/theory, acquisition and analysis of experimental electrophysiological data, simulation, visualization and validation. We will build metrics and visualizations that quantitatively compare computational models to experimental data. Specifically, we will implement a ?use case?, that will serve as a template for other integrative loops developed in the HBP. Approaches from computational and statistical neuroscience will be used and applied to data from other HBP work packages. In particular, the project requires the comparison of previously described models with experimental data from complex behavioral studies. The candidate will develop and implement standardized data formats, apply computational and statistical tools for data analysis, use graphical visualization to display results and present reports/results to the PIs, collaborators, and the research group. For this project the Statistical Neuroscience group is seeking a Postdoc in Computational and Systems Neuroscience Your Job: * Development of methods for comparing different model implementations and for comparing experimental and simulated data * Participating in the further development of methods for the analysis of massively parallel data and for the comparison of experimental and simulated data sets * Collaboration with experimental partners and modelers * Close collaboration with project partners within the Human Brain Project * Involvement in the further development of the Electrophysiology Analysis Toolkit (Elephant, www.neuralensemble.org/elephant) * Representing project results at internationals conferences * Regular organization of and attendance of project meetings and videoconferences together with or substituting for the workpackage leader * Scientific and administrative project coordination * Supporting the drafting of scientific project reports * Supporting the supervision of PhD students Your Profile: * Completed study of physics, mathematics or computer science * PhD on computational neuroscience topic, applied mathematics, computational neuroscience, physics, engineering or computer science or related field * Detailed knowledge of neuroscience concepts, especially in neuronal dynamics, analysis of neuronal activity and dynamics and expertise in mathematical models of neuronal networks * Expertise in network modelling on different spatial levels, which requires substantial expertise in mathematics and physics * Experience with large-scale data-science activities * Experience in scientific programming, especially Python; basic knowledge of C++ and high level programming languages for scientific computing, e.g. Matlab * Extensive experience with statistical analysis concepts * Enthusiasm for models and analysis of neuronal activity and dynamic * Enthusiasm for working with PhD students and appreciation of scientific progress as a joint venture * High ability to work in interdisciplinary, international team * Ability to approach tasks with an eye toward efficiency and reproducibility * Fluent in English, spoken and written * Experience in publishing scientific results in a related field (e.g. proven by publication list) * Ability and willingness to work independently and on one?s own responsibility * Ability and willingness to compose project reports * Good interpersonal and communication skills in interdisciplinary work environment * Ability to work in an interdisciplinary team * Willingness to travel * Structured and systematic working style Our Offer: * Integration into a young, interdisciplinary, and international institute * High visibility through participation in and substitution for institute directors at international project meetings in the Human Brain Project * Participation in publications in state-of-the-art research in computational neuroscience * Job in world class science environment at the interface between neuroscience and technology on the most complex known systems * Possibility to get actively involved in an innovative interdisciplinary project * Exciting working environment on an attractive research campus, ideally situated between the cities of Cologne, D?sseldorf, and Aachen * Limited until 31.03.2018 with possible longer-term prospects * Salary and social benefits in conformity with the provisions of the Collective Agreement for the Civil Service (TV?D). Depending on the applicant's qualifications and the precise nature of the tasks, salary grade EG 13-14 TV?D-Bund * Publication: simultaneous internal and external publication Forschungszentrum J?lich aims to employ more women in this area and therefore particularly welcomes applications from women. We also welcome applications from disabled persons We look forward to receiving your application, preferably online via our online recruitment system (http://intranet.fz-juelich.de/SharedDocs/Stellenangebote/_common/dna/2016-233-EN-INM-6.html?nn=1368484) until 17.11.2016, quoting the reference number 2016-233. Contact Human Resource Development Kristin Lux Tel.:+49 2461 61 9700 Contact at INM-6 Prof. Dr. Sonja Gr?n, INM-6, s.gruen at fz-juelich.de Dr. Martina Reske, INM-6, scientific coordinato, m.reske at fz-juelich.de -- Dr. Martina Reske Scientific Coordinator Institute of Neuroscience and Medicine (INM-6) Computational and Systems Neuroscience & Institute for Advanced Simulation (IAS-6) Theoretical Neuroscience J?lich Research Centre and JARA J?lich, Germany Work +49.2461.611916 Work Cell +49.151.26156918 Fax +49.2461.619460 www.csn.fz-juelich.de ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ 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 ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ -------------- next part -------------- An HTML attachment was scrubbed... URL: From malin.sandstrom at incf.org Fri Oct 21 06:23:06 2016 From: malin.sandstrom at incf.org (=?UTF-8?Q?Malin_Sandstr=C3=B6m?=) Date: Fri, 21 Oct 2016 12:23:06 +0200 Subject: Connectionists: Call for seed funding applications | Deadline November 30 Message-ID: Dear all, INCF* invites applications for seed funding of collaborative brain research projects. The deadline for submission is no later than *November 30, 2016*. Projects must be completed within 2017. Seed funding grants should facilitate community work in collaborative brain research, promote the use of neuroinformatics solutions, and accelerate advances in understanding the brain and treating its illnesses.There are two types of funding available, project funding and travel grants. *Travel grants* will be used to support collaborative work. One of the collaborators (traveller or host) must be based in one of the 17 INCF network countries. The proposed travel should support one or more of the following: - exchange of information relevant to neuroinformatics between parties based in different countries - progression of work relevant to neuroinformatics requiring the participant to travel to another location, usually another country, for collaboration - participation in neuroinformatics training or education as a lecturer or participant (but not general attendance at scientific meetings) *Project funding *supports projects that will deliver tools, data, research, education, training or community development, for example: - driving forward delivery of a product that addresses a neuroscience use case - enable a project to develop to the stage of attracting larger-scale external funding, for example initial consortium meetings or pilot data collection - organisation and hosting of a scientific workshop - development of training or educational content The funding could facilitate, for example: initial consortia formation for the creation of a competitive funding proposal; work to demonstrate a proof of concept; tool development or integration; hosting of a workshop to explore and develop an area; or development of education and training content. The leader of a funded proposal must be based in one of the 17 countries in the INCF network. All participants of a funded proposal must commit to sharing all reports, data, code, and training/education materials from the final project, subject to any limitations imposed by any subsequent funder. Projects must be completed within 2017. More information and FAQ: https://www.incf.org/resources/funding-support *INCF is an international organization launched in 2005, following a proposal from the Global Science Forum of the OECD to establish international coordination and collaborative informatics infrastructure for neuroscience. The INCF international network currently spans North America, Europe, Australia and Asia. INCF fosters the global digital interconnectivity of data, methods and people engaged in brain research to catalyze insights into brain function in health and disease. -- 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 gemmar at mit.edu Fri Oct 21 16:49:54 2016 From: gemmar at mit.edu (Gemma Roig) Date: Fri, 21 Oct 2016 20:49:54 +0000 Subject: Connectionists: Call for Abstracts submission for the AAAI Spring Symposium Series | Science of Intelligence : Computational Principles of Natural and Artificial Intelligence Message-ID: <84365E1C-1D2E-4D31-AF42-34B7CFE6C30F@mit.edu> **REMINDER** DEADLINE ABSTRACT SUBMISSION: October 28, 2016 at 11:59pm (UTC-12) Call for Abstracts submission for the AAAI Spring Symposium Series | Science of Intelligence : Computational Principles of Natural and Artificial Intelligence **************************************************************************** AAAI Spring Symposium Series | Science of Intelligence: Computational Principles of Natural and Artificial Intelligence http://cbmm.mit.edu/Symposium-Science-of-Intelligence Organized by the Center for Brains Minds and Machines March 27?-29 2017 at Stanford University in Palo Alto, California **************************************************************************** OVERVIEW Science of Intelligence is a new emerging field dedicated to developing a computation-based understanding of intelligence -both natural and artificial-, and to establishing an engineering practice based on that understanding. The Center for Brains Minds and Machines is organizing this symposium as a unique opportunity to bring together experts in artificial intelligence, cognitive science, and computational neuroscience to share and discuss the advances and the challenges of the study of the computational principles of natural and artificial intelligence. **************************************************************************** KEYNOTE SPEAKERS ?James DiCarlo (MIT) ?Li Fei-Fei (Stanford) ?Surya Ganguli (Stanford) ?Samuel Gershman (Harvard) ?Kristen Grauman (University of Texas at Austin) ?Gabriel Kreiman (Harvard) ?Karen Livescu (Toyota Technological Institute at Chicago) ?Aude Oliva (MIT) ?Pietro Perona (Caltech) ?Tomaso Poggio (MIT) ?Lorenzo Rosasco (Italian Institute of Technology) ?Amnon Shashua (Hebrew University and CTO at Mobileye) ?Joshua Tenenbaum (MIT) ?Shimon Ullman (Weizmann Institute) ?Patrick Winston (MIT) ?Daniel Yamins (Stanford) ?Alan Yuille (Johns Hopkins) **************************************************************************** CALL FOR PARTICIPATION This will be a 3-day symposium consisting on keynote talks, oral and poster presentations, panel discussions and a doctoral consortium. Authors willing to participate are invited to submit an abstract following these guidelines: http://cbmm.mit.edu/Symposium-Science-of-Intelligence/submissions DEADLINE ABSTRACT SUBMISSION: October 28, 2016 at 11:59pm (UTC-12) Students that submitted an abstract will be eligible for the doctoral consortium. Selected students will be assigned a mentor from the keynote speakers to discuss their work and future career plans. **************************************************************************** Program Chairs and Organizing Committee: ?Gemma Roig (MIT) gemmar at mit.edu The Center for Brains Minds and Machines Istituto Italiano di Tecnologia@ MIT ?Xavier Boix (MIT) xboix at mit.edu The Center for Brains Minds and Machines Istituto Italiano di Tecnologia@ MIT **************************************************************************** **************************************************************************** -------------- next part -------------- A non-text attachment was scrubbed... Name: smime.p7s Type: application/pkcs7-signature Size: 1845 bytes Desc: not available URL: From arokem at gmail.com Fri Oct 21 18:41:54 2016 From: arokem at gmail.com (Ariel Rokem) Date: Fri, 21 Oct 2016 15:41:54 -0700 Subject: Connectionists: Postdoc in data science and neuroengineering at the University of Washington, Seattle Message-ID: Jason Yeatman (http://depts.washington.edu/bdelab/), and Ariel Rokem ( http://arokem.org/) are seeking scientists with a PhD in neuroscience, computer science, electrical engineering, statistics, psychology or related fields, for a collaborative postdoctoral position at the intersection of human neuroscience, data science and neuroengineering. Suitable candidates will have the opportunity to apply for the WRF postdoctoral fellowships in data science: http://escience.washington.edu/get-involved/postdoctoral-fellowships and/or in neuroengineering: http://uwin.washington.edu/post-docs/apply-post-docs/ Fellows appointed through these programs will be provided with annual salary support of $65,000 for up to two years and an additional stipend of $25,000 over the total period of the appointment that can be used for travel, equipment, software, undergraduate research assistants, or other research costs. The project focuses on the development of methods for analyzing multi-modal MRI data, and the application of these methods to questions pertaining to human brain development. The long-term goals of the project include development and maintenance of software for the analysis of large openly available datasets of human MRI, and the extraction of valuable information about the biological basis of human cognitive abilities from these data. This involves developing new algorithms for the analysis of diffusion MRI, tools for harnessing cloud-computing to analyze these datasets at scale, and interactive data visualizations (e.g., http://viz.afq-browser.org). The postdoc would have the opportunity to work within a large and international open-source development community (http://dipy.org), and would be encouraged to develop a portfolio of open and reproducible science. For inquiries please contact Prof. Yeatman (jyeatman at uw.edu) and Ariel Rokem (arokem at uw.edu). We will both be available to meet with potential candidates at the Society for Neuroscience meeting in San Diego. *The University of Washington is an affirmative action and equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, national origin, age, protected veteran or disabled status, or genetic information.* -------------- next part -------------- An HTML attachment was scrubbed... URL: From y.demiris at imperial.ac.uk Sun Oct 23 13:01:41 2016 From: y.demiris at imperial.ac.uk (Demiris, Yiannis) Date: Sun, 23 Oct 2016 17:01:41 +0000 Subject: Connectionists: Research Positions in Computational Modelling of Human Attention at Imperial College In-Reply-To: References: Message-ID: <99B35DB5-A004-4FF3-A303-D80347CD9780@ic.ac.uk> Dear colleagues, A researcher position at the postdoctoral or PhD level is available through a MURI (Multidisciplinary University Research Initiative) grant with USA partners at USC, Harvard, UC Berkeley, CSHL, NYU, and UK partners at UCL and U Essex. The grant is on ?Closed-Loop Multisensory Brain-Computer Interface for Enhanced Decision Accuracy?, and our role at Imperial is on computational modelling of human attentional processes for enhanced decision support and closed loop BCI in car driving tasks. It is scheduled to start in November 2016, and it is for 3+2 years. For this and additional positions, please see details and job/person specifications at: http://www.imperial.ac.uk/personal-robotics/join-us/research-positions/ With best wishes, Yiannis ---- Professor Yiannis Demiris, FIET, FBCS, FRSS Department of Electrical and Electronic Engineering, Rm 1014, Imperial College London, South Kensington Campus, Exhibition Road, London, SW7 2BT, UK Tel: +44-(0)2075946300, Fax: +44-(0)2075946274 Webpage: http://www.iis.ee.ic.ac.uk/yiannis Lab: http://www.imperial.ac.uk/PersonalRobotics -------------- next part -------------- An HTML attachment was scrubbed... URL: From mail at mkaiser.de Mon Oct 24 06:18:10 2016 From: mail at mkaiser.de (Marcus Kaiser) Date: Mon, 24 Oct 2016 11:18:10 +0100 Subject: Connectionists: PostDoc position: developing computational models of optogenetic stimulation in epilepsy patients Message-ID: Dear all, a 3-year PostDoc position for developing computational models of optogenetic stimulation in epilepsy patients is available within my lab as part of the CANDO project at Newcastle University. *** About CANDO *** CANDO (Controlling Abnormal Network Dynamics using Optogenetics, http://www. cando.ac.uk/) is a world-class, multi-site, cross-disciplinary project to develop a cortical implant for optogenetic neural control. The goal is to create a first-in-human trial in patients with focal epilepsy. This seven year, ?10M Innovative Engineering for Health Award, funded by the Wellcome Trust and the Engineering and Physical Sciences Research Council (EPSRC) involves a team of over 30 neuroscientists, engineers and clinicians based at Newcastle University , Imperial College London , University College London and The Newcastle Hospitals NHS Foundation Trust . *** Available RA position *** As part of this project, the lab of Prof. Marcus Kaiser (http://www.dynamic- connectome.org/ ) is seeking a talented and enthusiastic research fellow with a PhD awarded, or a PhD thesis about to be submitted, in computational biology or related subjects. Objectives of this position are, first, to extend simulations of human brain activity at the local and global level of epilepsy patients. Second, the effect of stimulation on ongoing activity will be studied. Third, dynamical systems theory, control theory, and extensive simulations will be used to find optimal stimulation approaches that can reach desired oscillation patterns with minimal stimulation. Simulations will be informed by invasive recordings and non-invasive brain connectivity measurements in human epilepsy patients. Good communication skills, very strong dynamics modelling skills, and a track record of previous peer-reviewed journal publications. You will have experience with modelling brain rhythms and dynamical systems. The position will include brief visits to our partners in the UK and abroad. *** Research Environment *** Neuroinformatics at Newcastle University in the UK covers a range of topics from electrophysiology to neuroimaging. We are among the pioneers in connectome analysis and the establishment of large-scale neuroscience data management and analysis platforms, e.g. through the ?4m EPSRC-funded CARMEN project. Our strength is a close collaboration between computational, experimental, and clinical researchers. We currently have a team of 14 faculty members in the areas of Neuroinformatics and Neurotechnology: http://neuroinformatics.ncl.ac.uk/ *** How to Apply *** To apply, follow the information at http://www.jobs.ac.uk/job/AUP845/d34374r2-research-assistant-associate-computational-models-of-epileptic-brain-tissue/ The deadline is Monday 31 October. For further information, contact Prof. Marcus Kaiser, Marcus.Kaiser at ncl.ac. uk Best, Marcus -- Marcus Kaiser, Ph.D. FRSB @ConnectomeLab Professor of Neuroinformatics Interdisciplinary Computing and Complex Biosystems (ICOS) Research Group School of Computing Science Newcastle University Claremont Tower Newcastle upon Tyne NE1 7RU, UK Lab website: http://www.dynamic-connectome.org/ Neuroinformatics at Newcastle: http://neuroinformatics.ncl.ac.uk -------------- next part -------------- An HTML attachment was scrubbed... URL: From odelia at cs.miami.edu Mon Oct 24 10:18:59 2016 From: odelia at cs.miami.edu (Odelia Schwartz) Date: Mon, 24 Oct 2016 10:18:59 -0400 Subject: Connectionists: Faculty position in Computational Neuroscience or Computational Cognitive Science - Developmental Message-ID: Faculty position in Computational Neuroscience or Computational Cognitive Science - Developmental The Department of Computer Science at University of Miami has openings for two tenure track faculty positions (see ad below). One of the positions is in Computational Neuroscience or Computational Cognitive Science. The emphasis is on developmental, as part of a cluster initiative at the university on developmental disorders. Please contact me if you have questions. Odelia --------- The Department of Computer Science at the University of Miami invites applications for two Assistant Professor faculty positions starting August 2017. Candidates must possess a Ph.D. in Computer Science or a closely related discipline. The first position requires research expertise in Complex Systems, including (but not limited to) biological and social systems. The hire will be a member of the College of Arts and Sciences? Complexity Group. The second position requires research expertise in computational neuroscience or computational cognitive science, related to the study of Neurodevelopmental Disorders. The hire will have opportunities to collaborate with researchers in the Department of Psychology, the Department of Biology, the College of Arts and Sciences? Complexity Group and Brain Initiative, and the Medical school. The hire will be expected to teach at both undergraduate and graduate levels, and to develop and maintain internationally recognized research programs. The department encourages innovative interdisciplinary work with other units in the university. Applicants should submit a cover letter, CV, research plan, statement of teaching philosophy, sample preprints or reprints, any teaching evaluations from the last two years, and the names of at least three references online at http://www.cs.miami.edu/search/. Review of applications will begin on the 15th October 2016, and will continue until the position is filled. The University of Miami offers competitive salaries and a comprehensive benefits package. The University of Miami is an Equal Opportunity Employer ? Females/Minorities/Protected Veterans/Individuals with Disabilities are encouraged to apply. Applicants and employees are protected from discrimination based on certain categories protected by Federal law. -------------- next part -------------- An HTML attachment was scrubbed... URL: From pascal.fua at epfl.ch Mon Oct 24 12:41:52 2016 From: pascal.fua at epfl.ch (Pascal Fua) Date: Mon, 24 Oct 2016 18:41:52 +0200 Subject: Connectionists: Post-doctoral Position in Computer Vision at EPFL Message-ID: <6644bc24-a0f1-9bb7-f80c-933738938173@epfl.ch> EPFL's Computer Vision Laboratory (http://cvlab.epfl.ch/) has an opening for a post-doctoral fellow. The position is initially offered for 1 year and can be extended for up to 4 years total. Description: EPFL's Computer Vision laboratory (http://cvlab.epfl.ch) is about to begin in a joint project with FLARM (http://flarm.com/), a Swiss Company that develops collision avoidance devices for light aircrafts. The current generation of such devices relies on GPS data and we intend to extend their capabilities by also using video cameras as proximity sensors. The post-doctoral fellow will be expected to develop Deep Learning algorithms that can exploit both real and synthetic data to this end. 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 for post-doctoral fellows start from CHF 81,400 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 Statistical Machine Learning, 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. Staudenmann (ariane.staudenmann at epfl.ch). They must contain a statement of interest, a CV, a list of publications, and the names of three references. -- -------------------------------------------------------------------- Prof. P. Fua (Pascal.Fua at epfl.ch) Tel: 41/21-693-7519 FAX: 41/21-693-7520 Url: http://cvlab.epfl.ch/~fua/ -------------------------------------------------------------------- From nowozin at gmail.com Tue Oct 25 04:31:30 2016 From: nowozin at gmail.com (Sebastian Nowozin) Date: Tue, 25 Oct 2016 09:31:30 +0100 Subject: Connectionists: Microsoft Research Cambridge (UK) - Artificial Intelligence, 2-year Postdoc Researcher positions Message-ID: Microsoft Research Cambridge (UK) 2-year Postdoc Researcher positions Application deadline: 20th November 2016 ============================================================================= Microsoft AI and Research works with the world's best researchers, moving with the current of technology as it rapidly evolves. Together we share the motivation to seek innovative solutions to the world's toughest challenges and improve the lives of people everywhere. Microsoft Research Cambridge (UK) is searching for exceptional postdoc candidates in the area of Artificial Intelligence and Machine Learning, or a related field. The Machine Intelligence and Perception (MIP) group at Microsoft Research Cambridge is active in these areas: * Artificial Intelligence * Deep Learning * Machine Learning * Computer Vision * Natural Language Processing The recent research focus of the group included: * Knowledge representation and reasoning * Conversation and text interaction modelling * Learning program synthesis * Rich agent environments and reinforcement learning The MIP group is part of the larger Microsoft Research Cambridge lab which hosts 120 full-time researchers and collaboratively pursues research on systems and networking, human experience and design, programming principles and tools, synthetic biology, and medical imaging. Postdoc positions provide the freedom to pursue own ambitious research ideas as well as to interact with ongoing research projects across the lab. About Microsoft Research Cambridge ---------------------------------- "At Microsoft Research in Cambridge, our open and unconstrained approach to research, coupled with the bold and inquisitive minds of our researchers and engineers, has seen our lab produce contributions to Microsoft's most successful products and services, as well as key contributions to the academic community. But, we have just scratched the surface of what technology can do for us. We are continuing to push the boundaries of computing to create ubiquitous technologies with the potential to transform our lives." -- Professor Christopher M. Bishop Laboratory Director, Microsoft Research Cambridge Deadlines --------- The postdoc position is for a term of two years and comes with a highly competitive compensation and benefits package. * Application deadline: 20th November 2016 * Position starting date: Flexible upon hire, starting date within 2017 How to apply: 1. Visit https://careers.research.microsoft.com/ 2. Choose "Apply" and provide all professional details, including the name of three references. 3. Indicate that your research area of interest is "Machine Intelligence and Perception" and that your location preference is "Cambridge". 4. Include "Sebastian Nowozin" as the name of a Microsoft Research contact. 5. Ensure that you have successfully submitted the application. The application should include a curriculum vitae (CV), summary of past research (2 pages maximum), three referees, and a research statement (approximately 2-4 pages) which takes into account the unique opportunities provided by the Microsoft Research environment. Reference letters can only be requested once the application has been submitted and may be only requested for some candidates and some referees. Microsoft is an equal opportunity employer and supports workforce diversity. At Microsoft, we believe that diversity enriches our performance and products, the communities where we live and work, and the lives of our employees. As our workforce evolves to reflect the growing diversity of our communities and the global marketplace, our efforts to understand, value, and incorporate differences become increasingly important. Women and minorities are encouraged to apply. Further information ------------------- Further information is available at the following websites. https://www.microsoft.com/en-us/research/careers/ https://www.microsoft.com/en-us/research/lab/microsoft-research-cambridge/ https://www.microsoft.com/en-us/research/group/machine-intelligence-and-percepti Contact ------- For informal questions regarding the position, please contact Sebastian Nowozin (Sebastian.Nowozin at microsoft.com). ============================================================================= From Eirini.Mavritsaki at bcu.ac.uk Tue Oct 25 06:52:34 2016 From: Eirini.Mavritsaki at bcu.ac.uk (Eirini Mavritsaki) Date: Tue, 25 Oct 2016 10:52:34 +0000 Subject: Connectionists: =?windows-1252?q?PhD_in_=91New_insights_into_ADHD?= =?windows-1252?q?_through_behavioural_and_modelling_studies=92?= Message-ID: <3FCD70F47E1E99449079BAD1F20D729C5E114C84@EXMBXCC.staff.uce.ac.uk> Dear connectionists team, I was wondering if you could please forward the information below to your list about a new PhD position in our lab for February 2017 start. Kind regards, Eirini Mavritsaki PhD available for February 2017 start in ?New insights into ADHD through behavioural and modelling studies? Applications are invited for a 3-year PhD studentship within the Department of Psychology, Faculty of Business Law and Social Sciences, Birmingham City University. Applicants need to demonstrate ability and commitment, including excellent communications skills in written and spoken English. Project Synopsis: There are many limitations on the behaviour of complex neural systems, but one primary constraint is to filter incoming input in order that actions can be programmed to behaviourally relevant stimuli. This is the limit of ?attention?. A major challenge for current-day researchers is to understand how (and why) these limitations arise, especially in conditions like attention deficit hyperactivity disorder (ADHD) where the attentional system is dysfunctional. Our application?s main aims is to access differences in visual attention between children diagnosed with ADHD and typically functioning children and the role of diet in this. This Ph.D. thesis aims to do this using a novel interdisciplinary approach, behavioural and computational modelling study together with a food diary. The Ph.D. is part of a bigger research project that is in collaboration with Dr Chrysavgi Tsakona in Russell Hall Hospital. The successful applicant will join the newly-established Centre for Applied Psychological Research (CAP Research) within the Department of Psychology at Birmingham City University. This centre is part of a vibrant and rapidly expanding research community, which offers applicants with an excellent opportunity to develop their research career. The applicant has the opportunity to have teaching experience, to participate to research seminars and to co-supervise undergraduate projects. Candidate Qualification and Specifications: Essential ? The applicant should hold a good undergraduate honours degree (First or 2:1) in psychology or a related social sciences subject. ? A demonstrated understanding of research methods is essential (as evidenced by degree transcript grades for research methods and dissertation modules). ? The applicant will be expected to undertake and pass Disclosure and Barring Service (DBS) checks. ? The applicant should enjoy working with children. ? The applicant should have experience in computational modelling. Desirable ? A Masters? degree in research methods, psychology or a related social sciences subject. ? Work experience (voluntary or paid) in schools or experience working with children. ? Experience in C++ and/or Matlab. ? Access to a car and a valid driving licence. For more information please contact Dr Eirini Mavritsaki (Eirini.mavritsaki at bcu.ac.uk) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Eirini Mavritsaki, Ph.D., CPsychol Senior Lecturer in Cognitive Psychology and Director of Research for the School of Social Sciences Department of Psychology Faculty of Business Law and Social Sciences Birmingham City University The Curzon Building 4 Cardigan Street Birmingham B4 7BD eirini.mavritsaki at bcu.ac.uk 0121 331 6361 Special Issue in Frontiers 'Neuropsychology through the lenses of computational modelling' http://fron.tiers.in/go/r2e3M4 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -------------- next part -------------- An HTML attachment was scrubbed... URL: From Eirini.Mavritsaki at bcu.ac.uk Tue Oct 25 07:01:21 2016 From: Eirini.Mavritsaki at bcu.ac.uk (Eirini Mavritsaki) Date: Tue, 25 Oct 2016 11:01:21 +0000 Subject: Connectionists: FW: PhD in 'Cultural and contextual differences in picture perception: building an ecological model of human visual perception' Message-ID: <3FCD70F47E1E99449079BAD1F20D729C5E114CC6@EXMBXCC.staff.uce.ac.uk> Dear connectionists team, I was wondering if you could please forward the information below to your list about a new PhD position in our lab for February 2017 start. Kind regards, Eirini Mavritsaki Cultural and contextual differences in picture perception: building an ecological model of human visual perception Full time PhD funding available for February 2017 start For further details contact Dr P. Rentzelas (Panagiotis.rentzelas at bcu.ac.uk) and Dr E Mavritsaki (Eirini.mavritsaki at bcu.ac.uk). Short description: The proposed postgraduate research project aims to investigate the cross-cultural differences on visual attention. This will be achieved by employing a ground breaking research methodology that will involve social and cognitive psychology research techniques and the use of EEG and eye-tracking equipment. This approach will enable the more detailed understanding of the underlying brain processes on human visual perception and its cross-cultural and ecological differences. Applicant requirements: The ideal candidate should be a Psychology or Neuroscience graduate with a 2:1 or above BSc (Hons) with a strong interest and experience in behavioural and psychophysiological research. A postgraduate qualification in the area will be desirable. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Eirini Mavritsaki, Ph.D., CPsychol Senior Lecturer in Cognitive Psychology and Director of Research for the School of Social Sciences Department of Psychology Faculty of Business Law and Social Sciences Birmingham City University The Curzon Building 4 Cardigan Street Birmingham B4 7BD eirini.mavritsaki at bcu.ac.uk 0121 331 6361 Special Issue in Frontiers 'Neuropsychology through the lenses of computational modelling' http://fron.tiers.in/go/r2e3M4 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -------------- next part -------------- An HTML attachment was scrubbed... URL: From mathying at gmail.com Tue Oct 25 11:24:08 2016 From: mathying at gmail.com (Yiming Ying) Date: Tue, 25 Oct 2016 11:24:08 -0400 Subject: Connectionists: faculty job at SUNY albany Message-ID: Hi, Could you post the following job information, Thank you. --------------------------- *Job Description:* The Department of Mathematics and Statistics at the University at Albany, State University of New York, invites applications for a tenure-track position at the rank of Assistant Professor. The term of the position begins in Fall 2017 and the targeted area in the search is "machine learning". We are looking for a candidate who will significantly contribute to the department's research, closely collaborate with current members of the department, and enhance our undergraduate and graduate programs. In particular, we are seeking a person capable of teaching Statistics courses in our Actuarial Program, directing PhD students, and with potential for collaboration with our newly developing group in Data Science. *Requirements:* Minimum Requirements: - Candidates are required to have a PhD or an equivalent doctoral degree in Mathematics from a university accredited by the U.S. Department of Education or an internationally recognized accrediting organization. - Candidates should possess excellent research credentials as demonstrated by their PhD dissertation, publications, external funding, and as supported by letters of recommendation from experts in the field. - Also of great importance are teaching credentials demonstrated by student evaluations and teaching awards and supported by letters of recommendation. - All applicants must address in their applications their ability to work with a culturally diverse population. Preferred Qualifications: - Some postdoctoral experience and a successful record of external funding are highly desirable. *Additional Information:* Professional Rank and Salary Range: Assistant Professor, salary competitive and commensurate with qualifications and experience Start date: September 1, 2017 The closing date for receipt of applications is December 1, 2016. The Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act, or Clery Act, mandates that all Title IV institutions, without exception, prepare, publish and distribute an Annual Security Report. This report consists of two basic parts: disclosure of the University's crime statistics for the past three years; and disclosures regarding the University's current campus security policies. The University at Albany's Annual Security Report is available in portable document format [PDF] by clicking this link http://police.albany.edu/ASR.shtml *THE UNIVERSITY AT ALBANY IS AN EO/AA/IRCA/ADA EMPLOYER* *Please apply online* via http://albany.interviewexchange.com/candapply.jsp?JOBID=77747 More details, please https://albany.interviewexchange.com/jobofferdetails.jsp?JOBID=77747&CNTRNO=1&TSTMP=1477407390662 ----------- ---------------------- Dr. Yiming Ying Associate Professor Department of Mathematics and Statistics State University of New York at Albany 1400 Washington Avenue Albany? New York, 12222, USA Email: yying at albany.edu Tel: +1 518 442-4613 -------------- next part -------------- An HTML attachment was scrubbed... URL: From vicen.gomez at upf.edu Tue Oct 25 16:35:39 2016 From: vicen.gomez at upf.edu (=?UTF-8?B?VmljZW7DpyBHw7NtZXo=?=) Date: Tue, 25 Oct 2016 22:35:39 +0200 Subject: Connectionists: EWRL 2016: registration open Message-ID: <3ca63e4a-9f2b-355d-375e-6a05cdc5dbee@upf.edu> ************************************************************************************************* The 13th European Workshop on Reinforcement Learning (EWRL 2016) Dates: December 3-4 2016 Location: Pompeu Fabra University, Barcelona, Spain (co-located with NIPS) http://ewrl.wordpress.com/ewrl13-2016/ ************************************************************************************************* We are pleased to announce that the registration for the 13th European workshop on reinforcement learning (EWRL 2016) is now open. Please follow this link to register: https://goo.gl/forms/g5P9yQTnSBx92qSB3 Registration is free of charge, but please note that we have limited space. Thus, we kindly ask you to register only if you are really planning to participate. About the workshop ================== The 13th European workshop on reinforcement learning (EWRL 2016) invites reinforcement-learning researchers to participate in the newest edition of this world class event. We plan to make this an exciting meeting for researchers worldwide, not only for the presentation of top quality papers, but also as a forum for ample discussion of open problems and future research directions. EWRL 2016 will consist of 12 invited talks, 10 contributed paper presentations, discussion sessions, and two poster sessions spread over a two day period. Reinforcement learning is an active field of research which deals with the problem of sequential decision making in unknown (and often) stochastic and/or partially observable environments. Recently there has been a wealth of both impressive empirical results, as well as significant theoretical advances. Both types of advances are of significant importance and we would like to create a forum to discuss such interesting results. For more information, please see https://ewrl.wordpress.com/ewrl13-2016/ Organizing Committee ================== Gergely Neu Vicen? G?mez Csaba Szepesv?ri From ilya.nemenman at emory.edu Tue Oct 25 22:11:02 2016 From: ilya.nemenman at emory.edu (Nemenman, Ilya) Date: Wed, 26 Oct 2016 02:11:02 +0000 Subject: Connectionists: Submit to Neuroscience and Machine Learning sessions at the 2017 American Physical Society annual March Meeting Message-ID: <6B5A2E8F-A596-47B6-B446-E8CDABD032A7@emory.edu> Dear Colleagues: The 2017 American Physical Society (APS) March meeting (March 13-17, 2017; New Orleans, LA) will again emphasize ?Physics of Neural Systems? in its program; in addition, multiple sessions will be held to discuss the interface between physics and machine learning. Invited and Focus sessions of relevance to neuroscientists and machine learning researchers will include, among others, 1. Robot scientists and machine learning for the modeling and control of biological systems 2. Patterns and control in animal behavior 3. Physics of neural network dynamics for the brain 4: Photoreceptor and signal transduction. 5: Neural control of behavior 6: Non-equilibrium dynamics of neural circuits 7: Machine learning for modeling and control You can also submit to the following related general DBIO sorting categories: 4.10: Physics of Neural Systems 4.11: Physics of Behavior 4.13: Methods in Biological Physics Some of the invited / confirmed speakers include: Misha Ahrens (Janelia Research Campus) Gordon Berman (Emory University) Andre Brown (Imperial College) Steve Brunton (University of Washington) Giancarlo La Camera (Stony Brook University) Hod Lipson (Columbia University) Michale Fee (MIT) Ross King (University of Manchester) Andrew Leifer (Princeton University) Bo Li (CSHL) Kenneth Miller (Columbia University) Leslie Osborne (University of Chicago) David Schwab (Northwestern University) Sara Solla (Northwestern University) Charles Stevens (Salk Institute) Anthony Zador (CSHL) and others We are now accepting abstract submissions for contributed talks on a broad range of topics on the intersection of physics, neuroscience, and machine learning, such as quantitative experimental protocols, modeling of neural dynamics, statistical physics of deep learning, analysis of collective computation in neural circuits, and others. March meeting abstract submission website: https://www.aps.org/meetings/march/index.cfm Abstract submission deadline: November 11, 2016, 5:00pm EST APS March meeting is the largest physics meeting in the world, attracting about 10,000 physicists. At the meeting, the APS Division of Biological Physics supports one of the largest and scientifically diverse programs on the interface of physics and biology, from molecular and cellular biophysics, to computational neuroscience and population dynamics, featuring over 700 talks last year. We are looking forward to receiving your abstracts. If you have any questions about neuroscience at the March Meeting, please don?t hesitate to contact Ilya Nemenman (ilya.nemenman at emory.edu). Sincerely, Ilya Nemenman Professor of Physics and Biology Emory University, Atlanta, GA and Chair, Division of Biological Physics (DBIO) American Physical Society (APS) http://nemenmanlab.org ________________________________ This e-mail message (including any attachments) is for the sole use of the intended recipient(s) and may contain confidential and privileged information. If the reader of this message is not the intended recipient, you are hereby notified that any dissemination, distribution or copying of this message (including any attachments) is strictly prohibited. If you have received this message in error, please contact the sender by reply e-mail message and destroy all copies of the original message (including attachments). From dan.navarro at unsw.edu.au Tue Oct 25 18:59:42 2016 From: dan.navarro at unsw.edu.au (Dan Navarro) Date: Wed, 26 Oct 2016 09:59:42 +1100 Subject: Connectionists: Scientia Ph.D. Scholarship at UNSW Sydney, Australia Message-ID: *SCIENTIA PhD SCHOLARSHIPS ($40,000 AUS p.a. tax-free over 4 years)* *Sydney Thinking and Reasoning (STAR) lab, SCHOOL OF PSYCHOLOGY* *UNIVERSITY OF NEW SOUTH WALES, SYDNEY, AUSTRALIA* *Project Area: On the origins of data ? Information sampling, reasoning, and decision-making by human learners* (Leaders: Professor Brett Hayes & Associate Professor Dan Navarro) Expressions of interest are sought from outstanding graduates with a strong academic record including Honors Class I or equivalent for 4-year PhD scholarships that include a living allowance of $40,000 AUS per annum (tax-free) and $10,000 per annum in additional project support costs (e.g. relocation, travel, etc). Graduates with a strong background in cognitive psychology, cognitive science, cognitive development, decision science, or other relevant discipline are particularly encouraged to apply. Graduates with additional past experience working as a research scientist or assistant are also strongly encouraged to apply. *Project Description*: Learning how to generalize from data is a fundamental inductive task facing any intelligent agent. Psychologists have traditionally focused on how human reasoning depends on similarity - people are more willing to generalize from a familiar entity to a novel one when the two are similar. Our work has shown, however, that human reasoning can be remarkably subtle. Using recent developments in computational cognitive modelling, this project will develop new models of human inductive reasoning. Our focus is on how people rely on intuitive theories about the world and other minds, and how such reliance shapes the generalizations we make. The School of Psychology at UNSW is recognised nationally and internationally for its excellence in research and teaching. It is a leading Australian Psychology department on quality measures such as research publications and competitive grant funding. If you are interested in learning more about this scholarship opportunity, please send an email (including curriculum vitae) to: b.hayes at unsw.edu.au before 11th November. -- A/Prof Dan Navarro School of Psychology University of New South Wales dan.navarro at unsw.edu.au compcogscisydney.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From yulia.sandamirskaya at ini.rub.de Wed Oct 26 05:52:57 2016 From: yulia.sandamirskaya at ini.rub.de (Yulia Sandamirskaya) Date: Wed, 26 Oct 2016 11:52:57 +0200 Subject: Connectionists: EUCog 2016: Registration is OPEN! Message-ID: <5FCCB7E3-3311-4DF8-90EE-03108EE09E51@ini.rub.de> REGISTRATION FOR THE EUCOG CONFERENCE IS OPEN: http://www.eucognition.org/index.php?page=2016-vienna-event-registration-form We are looking forward to welcome you at the event! >>>>>>>>>>>>>>>>>>>>>>>>> Updated event Information: ?Cognitive Robot Architectures? EUCog 2016 - ?European Society for Cognitive Systems? December 8th-9th, 2016 TU Vienna, Karlsplatz 13, 1040 Vienna http://www.eucognition.org/index.php?page=2016-vienna-general-info Abstract submission date: 01.Oct 2016 (CLOSED) For over a decade, the EUCognition network (EUCog) has brought together academic researchers and industrial partners with a common interest in the design and construction of artificial cognitive systems in ways that are informed by, or attempt to explain, biological cognition. The emphasis is on systems that are autonomous, robust, flexible and self-improving in pursuing their goals in real environments. EUCog not only includes researchers who use insights from natural cognition in creating artificial cognitive systems for robotic and other technical applications but also those interested in using artificial cognitive systems to understand natural cognition. The field includes computer science, robotics, cognitive science, neuroscience, and philosophy as its core disciplines. EUCog will hold its next meeting this coming December in Vienna. The focus of the event will be community building, as well as presenting cutting-edge research in the field of artificial cognitive systems. The meeting is open to all: one need not be a past or current member of the EUCog network to attend. ========================================= INVITED SPEAKERS: David Vernon (Sk?vde) http://www.vernon.eu Paul F.M.J. Verschure (UPF Barcelona) http://specs.upf.edu/people/paul-fmj-verschure ========================================= ORGANISERS Ron Chrisley (University of Sussex) Vincent C. M?ller (Anatolia College/ACT & University of Leeds) Yulia Sandamirskaya (University of Zurich & ETH Z?rich) Markus Vincze (Technical University of Vienna) ========================================= THEME: COGNITIVE ARCHITECTURES The theme of this meeting will be cognitive architectures, raising such questions/debates as: ? What makes an architecture a cognitive architecture? A good cognitive architecture? ? Implementation-independent architectures vs strongly embodied architectures ? Should/could there be a common framework for comparing cognitive architectures? ? What are the tradeoffs of various architectural features? ? What are the best examples of architecture-based designs of cognitive systems? ? What is the role of architecture in the design-implement-evaluate cycle? Key issues to be explored at the meeting include: ? The role of cognitive architectures in robotic systems ? The role of neural networks in the design of cognitive architectures ? The role of cognitive science in the design of robotic architectures ? Embodiment and robotic architectures ? Architectures for robotic perception (esp. vision, audition, haptics, proprioception, kinaesthesia, interoception) ? Architectures for motor control and behavioural organisation ? Architectures for planning and mapping ? Architectures for HRI ? Machine learning and robotic architectures ? Architectures for developmental robotics ? Embodied deliberative architectures ? Embodied reflective architectures ========================================= ABSTRACTS We invite submissions for papers and posters. For papers, we invite anonymous long abstracts of 600-1000 words (excluding references) in plain text or PDF. For posters, we require a short abstract of 120 words. Accepted papers and posters will be presented at the conference and published in the proceedings. All submissions will be double-blind reviewed by at least two members of the programme committee. Please, submit online at EasyChair: https://easychair.org/conferences/?conf=eucog2016 (please submit your long abstract as ?paper? on that site). ========================================= PUBLICATION The proceedings of the meeting will be published in the ?Springer Series in Cognitive and Neural Systems?. The best papers will be invited to contribute to a Special Issue "Cognitive Robot Architectures? of the Cognitive Systems Research (CSR) journal, subject to peer review. ========================================= REGISTRATION Online registration is open now: http://www.eucognition.org/index.php?page=2016-vienna-event-registration-form Participation fee - including lunch & coffee breaks, and conference dinner range from ?220 (full payers) to ?75 (privately paying students). ========================================= KEY DATES Deadline for submission of abstracts and long abstracts: 01.10.2016 (CLOSED) Decisions announced: 04.11.2016 Conference: 08.-09.12.16 Deadline for submission of posters/papers for publication: 01.12.16 Early registration deadline: 30.11.2016 ========================================= We look forward to seeing you in Vienna in December! ? Dr. Yulia Sandamirskaya Neuroscience Center Zurich (ZNZ) Institute of Neuroinformatics University and ETH Zurich Winterthurerstrasse 190, 8057 Zurich E-mail: yulia.sandamirskaya at ini. uzh.ch Tel: +41 77 97 46613, +41 44 63 53066 -------------- next part -------------- An HTML attachment was scrubbed... URL: From elizabeth.wiesman at wright.edu Wed Oct 26 09:42:41 2016 From: elizabeth.wiesman at wright.edu (Wiesman, Liz) Date: Wed, 26 Oct 2016 13:42:41 +0000 Subject: Connectionists: Position Annoucement for job list Message-ID: SUBJECT: Position Announcement Wright State Research Institute Post-Doctoral Cognitive Neuroscientist Postdoctoral Cognitive Neuroscientist Position in the Research Services Division of Wright State Research Institute, Wright State University, Dayton, Ohio, USA This Neuroscientist will join a team conducting research involving high-level cognition, including executive functions such as attentional control, working memory and cognitive inhibition, as well as related cognitive functions such as decision making and learning & memory. The ideal candidate possess a PhD in Neuroscience, Cognitive Science, or related discipline; a minimum of 2 year's research experience and publications; experience with one or more non-invasive neuroimaging modalities, in particular EEG and/or fMRI. We anticipate a start date of 1 December 2016, but are flexible in this regard. Interested candidates should submit a formal application to Wright State University's HR website at the following link: https://jobs.wright.edu/postings/10811 Elizabeth Wiesman Resource Manager Wright State Research Institute 4035 Colonel Glenn Highway Beavercreek, OH 45431 PH: 937.705.1006 SECURE FAX: 937.705.1302 EMAIL: elizabeth.wiesman at wright.edu -------------- next part -------------- An HTML attachment was scrubbed... URL: From mm at pdx.edu Wed Oct 26 12:03:30 2016 From: mm at pdx.edu (Melanie Mitchell) Date: Wed, 26 Oct 2016 09:03:30 -0700 Subject: Connectionists: machine learning faculty position at Portland State University Message-ID: <1AB23ED6-0FD1-4F60-B476-4E4CE69AE661@pdx.edu> The Computer Science Department at Portland State University (in Portland, Oregon) invites applications for a tenure-track faculty position in machine learning / data science. On the machine learning side, we are looking for applicants in neural networks, probabilistic modeling, optimization, reinforcement learning, or any other area of modern ML. We are a growing, research-oriented department with low teaching loads, an active PhD program, and excellent collaborations with local tech industry, including Intel. Portland is a beautiful, liveable city with vast opportunities for cultural and outdoor recreation. For more information, and instructions on applying, go to http://www.pdx.edu/computer-science/open-faculty-positions ? Melanie Mitchell -------------- next part -------------- An HTML attachment was scrubbed... URL: From JAPlatt at northwell.edu Wed Oct 26 12:15:18 2016 From: JAPlatt at northwell.edu (Platt, Jo Ann) Date: Wed, 26 Oct 2016 12:15:18 -0400 Subject: Connectionists: Onsite interviews at SfN for Neural Data Analytics - Post Docs, Staff Scientists and Electrical Engineers Message-ID: <786DD4B977A6024B9520062297C8A8DFC8CCB2CE0C@SYKECHXVS10.nslijhs.net> Join our team to revolutionize medicine. The Center for Bioelectronic Medicine at the Feinstein Institute for Medical Research is conducting interviews at the 2016 Neuroscience Meeting in San Diego for multiple positions in the fields of machine learning, neural engineering, neural decoding and data analytics, microfabrication, bioelectronics and biosensing, and neurophysiology. Each successful candidate will work as part of a multidisciplinary team to determine the nature of neural control over molecular, cellular and organ functions of the body, the parts of the brain that regulate those nerves, and the signals that the brain receives to monitor cell and organ function. The candidates will work on projects involving development of novel signal processing and machine learning methods to gain insights into decoding and encoding mechanisms of the brain and peripheral nerves, reinforcement learning approaches used to optimize neural stimulation, techniques to directionally transmit or receive neural signals and numerical and biophysical modeling of neural circuits. Submit your resume to japlatt at northwell.edu for consideration and to arrange an onsite interview. Jo Ann Platt The Feinstein Institute for Medical Research Cell: (415) 265-0441 350 Community Drive Manhasset, NY 11030 The information contained in this electronic e-mail transmission and any attachments are intended only for the use of the individual or entity to whom or to which it is addressed, and may contain information that is privileged, confidential and exempt from disclosure under applicable law. If the reader of this communication is not the intended recipient, or the employee or agent responsible for delivering this communication to the intended recipient, you are hereby notified that any dissemination, distribution, copying or disclosure of this communication and any attachment is strictly prohibited. If you have received this transmission in error, please notify the sender immediately by telephone and electronic mail, and delete the original communication and any attachment from any computer, server or other electronic recording or storage device or medium. Receipt by anyone other than the intended recipient is not a waiver of any attorney-client, physician-patient or other privilege. From travis.e.baker.phd at gmail.com Wed Oct 26 12:32:23 2016 From: travis.e.baker.phd at gmail.com (Travis Baker) Date: Wed, 26 Oct 2016 12:32:23 -0400 Subject: Connectionists: Fwd: Multiple PhD Studentships available at the Center for Molecular and Behavioral Neuroscience, Rutgers University In-Reply-To: References: Message-ID: ---------- Forwarded message ---------- From: Travis Baker Date: Tue, Oct 25, 2016 at 1:29 PM Subject: Multiple PhD Studentships available at the Center for Molecular and Behavioral Neuroscience, Rutgers University To: connectionists at cs.cmu.edu PhD Studentships available *Deadline: December 15, 2016* The Center for Molecular and Behavioral Neuroscience (CMBN) at Rutgers University ? Newark is inviting students to apply to its *Behavioral and Neural Sciences*Graduate Program for the 2017 admissions cycle. CMBN?s mission is to advance understanding of the brain?s structure and function through excellence in neuroscience research and training. We believe this goal can only be reached through an integrative approach that cuts across the boundaries of traditional disciplines. Thus, CMBN researchers combine molecular, electrophysiological, optogenetics, neurochemical, anatomical and functional neuroimaging, behavioral, pharmacogenetics, and neuropsychological methods to analyze how the brain works, develops, interacts with the environment, and is modified by experience in health and disease. The program trains students for scientific research careers in neuroscience and prepares students to take positions in academic, medical and industrial research settings. Our focus is on multidisciplinary training of students across the domains of neuroscience. Students are trained to conduct independent research and to present and discuss research ideas and results both orally and in written form. Students also gain experience in both undergraduate and graduate teaching. The program benefits from the active participation of the graduate faculties of Rutgers University-Newark from the CMBN, the Department of Biological Sciences, and the Department of Psychology. CMBN benefits from on-site access to Rutgers University Brain Imaging Center, a research-dedicated facility equipped with a 3T fMRI scanner (Siemens TRIO) for imaging both humans and animals ( http://rubic.rutgers.edu). For those with an interest in working with clinical populations, we have superb cooperation with our medical school faculty in neurology, psychiatry, and neurosurgery, as well as collaborations with several medical centers in nearby New York City. The PhD program lasts four to five years. Starting in year one, students do semester-long research rotations in laboratories of one or more faculty members to learn about different aspects of neuroscience research. Dissertation research can also be completed under the supervision of more than one faculty member, to broaden student training. The course curriculum has been developed to bring students with diverse backgrounds (neuroscience, psychology, cognitive neuroscience, mathematics, neuroimaging, and engineering) up to speed on the topics they will need for their research projects. Most classes involve extensive discussions with faculty, hands-on learning, critical thinking, and scientific writing. Interested students are encouraged to contact potential supervisors in advance to learn more about their research program. All students are fully funded, regardless of nationality. The program also welcomes applications from students with pre-secured funding or who are currently soliciting other scholarship/studentships. PhD students receive a 12-month renewable graduate assistantship of $29,605 plus tuition remission and a medical benefits plan. Further, the President of Rutgers, The State University of New Jersey, invites outstanding candidates to apply to Ph.D. programs for consideration as Presidential Fellows ($35,000 annual fellowship stipends for 2 years). Applications (including a CV, statement of research interests, and letters from three referees) for 2017/18 admission must be sent directly to the BNS program. Full details of our program, and how to apply, are available at: *bns.rutgers.edu * For further details of research interests please see individual CMBN faculty webpages at CMBN: *cmbn.rutgers.edu * Informal enquiries may be addressed to Dr. Travis Baker (*travis.e.baker at rutgers.edu *) or Dr. Juan Mena-Segovia (*juan.mena at rutgers. * -------------- next part -------------- An HTML attachment was scrubbed... URL: From travis.e.baker.phd at gmail.com Wed Oct 26 12:32:56 2016 From: travis.e.baker.phd at gmail.com (Travis Baker) Date: Wed, 26 Oct 2016 12:32:56 -0400 Subject: Connectionists: Fwd: Doctoral position in multimodal neuroimaging of decision making and memory In-Reply-To: References: Message-ID: PhD Studentships available *Deadline: December 15th, 2016* The Center for Molecular and Behavioral Neuroscience (CMBN) at Rutgers University ? Newark is inviting students to apply to its *Behavioral and Neural Sciences *Graduate Program for the 2017 admissions cycle. A fully-funded doctoral position is available in the laboratory of Dr. Travis Baker based at the Center for Molecular and Behavioural Neuroscience (CMBN), Rutgers University, http://cmbn.rutgers.edu . CMBN is located in Newark NJ, a short commute from New York City. The laboratory of Dr. Baker employs multimodal neuroimaging techniques (e.g. EEG, ERPs, fMRI, diffusion MRI, and transcranial magnetic stimulation), involving both typical and atypical populations, to characterize the spatiotemporal dynamics and the computational principles underlying reinforcement learning, cognitive control, and spatial navigation, as mediated by a network of brain systems including anterior cingulate cortex, the midbrain dopamine system, the basal ganglia, and parahippocampal cortex. The clinical goal of the laboratory is to understand how these functions are disrupted in psychiatric populations (e.g. addictions, affective disorders, neurodegenerative disorders), and to identify image-based biomarkers (e.g. EEG/ERPs, fMRI) and neurostimulation procedures aimed to alleviate their cognitive and behavioral impairments. This position offers an excellent opportunity to develop research expertise in a new state-of-the art neuroimaging and neurostimulation laboratory which houses an Adept Viper s850 robotic arm used for robot-assisted image-guided repetitive transcranial magnetic stimulation (Ri-rTMS), two parallel systems for recording EEG/ERPs, an eyetracking and virtual reality system, and has the capabilities of recording and analyzing simultaneous EEG and fMRI, and simultaneous EEG and Ri-rTMS. CMBN benefits from on-site access to Rutgers University Brain Imaging Center, a research-dedicated facility equipped with a 3T fMRI scanner (Siemens TRIO) for imaging both humans and animals (http://rubic.rutgers.edu ). For those with an interest in working with clinical populations, we have superb cooperation with our medical school faculty in neurology, psychiatry, and neurosurgery, as well as collaborations with several medical centers in nearby New York City. Candidates must have an undergraduate degree (or Masters) in neuroscience, psychology, cognitive science or in a related discipline. The successful candidate will show evidence of research productivity in the form of peer-reviewed publications and conference proceedings, have excellent quantitative skills, and demonstrate effective oral and written communication skills. Recording and analysis experience with EEG/ERP (e.g., Brainvision, EEG/ERPLAB), MRI (e.g., FSL, SPM), as well as experience with stimulus presentation programs (e.g., E-prime, PsychoPy, Psychtoolbox), and statistical analysis (e.g., MATLAB, R, SPSS), is advantageous. Proficiency in MATLAB and computational modeling is highly desirable. The position is fully-funded (plus medical benefits, 4 weeks vacation, tuition remission, and yearly travel funds) for a period of 5 years. Informal enquiries may be addressed to Dr. Travis Baker at travis.e.baker at rutgers.edu no later than December 1st, 2016 and should include the following: 1) cover letter summarizing research interests and qualifications for the position, 2) a curriculum vita, and 3) the names of two references who may be contacted. Further details about Dr. Baker?s research interests can be found at www.travisedwardbaker.com. Rutgers University is an equal opportunity educator and employer. -------------- next part -------------- An HTML attachment was scrubbed... URL: From bwyble at gmail.com Wed Oct 26 23:26:58 2016 From: bwyble at gmail.com (Brad Wyble) Date: Wed, 26 Oct 2016 23:26:58 -0400 Subject: Connectionists: PhD Studentship available in the lab of Brad Wyble, Penn State University Message-ID: Call for PhD student applicants, Penn State University, Laboratory of Brad Wyble The lab of Brad Wyble at PSU is looking to recruit graduate students in the fall semester of 2016 for a starting date of August, 2017. The topics of research will be decided in conjunction with the student, but are likely to involve the neural mechanisms underlying visual attention and memory function, broadly construed. Lab Research Synopsis Our lab attempts to understand the nature of mental representations that are constructed from recent visual experience by building computational models of the neural mechanisms underlying attention and memory. These models are constrained by data from our lab, including psychophysics, electrophysiology, and eye-tracking. We have dedicated facilities for EEG and eyetracking within the building, a 100-core supercomputer in the lab, and larger on-campus computing resources. Our lab also manages four testing booths for rapid psychophysical testing. Details about ongoing projects can be found at http://wyblelab.com/research, however we strongly emphasize student independence in project development and authorship. Students are encouraged to play a key role in the construction and evaluation of computationally formalized models of neural mechanisms. Our lab advocates as well the principles of open science, with data and method sharing using the Open Science Framework among other tools. A background in programming (MATLAB, Python, etc) and/or statistics is preferred but more important is a curiosity about the neural circuitry that enables attention and memory systems to build an understanding of the external world. Interested applicants should apply to the Psychology department at http://psych.la.psu.edu/graduate/prospective-students/how-to-apply-to-graduate-school-in-psychology and should note that the deadline for applications is December 1st. Informal inquires can be directed to Brad Wyble at bwyble at gmail.com. Brad Wyble Associate Professor Psychology Department Penn State University -------------- next part -------------- An HTML attachment was scrubbed... URL: From kagan.tumer at oregonstate.edu Wed Oct 26 20:45:34 2016 From: kagan.tumer at oregonstate.edu (Kagan Tumer) Date: Wed, 26 Oct 2016 17:45:34 -0700 Subject: Connectionists: Faculty Positions in Robotics at Oregon State University Message-ID: <58114E2E.5000002@oregonstate.edu> Oregon State University (OSU) Robotics program invites applications for one or more full-time tenure-track and/or tenured faculty positions to begin Fall 2017. All areas relating to robotics will be considered. As one of the nation?s leading Robotics programs, OSU seeks top-quality candidates who will help us continue to grow (http://robotics.oregonstate.edu). Candidates should hold a Ph.D. in robotics, mechanical engineering, electrical and computer engineering, computer science, or other relevant discipline by the start date of employment, have a demonstrated record of scholarship, and have experience working with real robots. The successful candidates will have office and laboratory space physically located with the existing Robotics group, and will have an administrative home most appropriate to their area of expertise within the College of Engineering?s School of Electrical Engineering and Computer Science (EECS) or School of Mechanical, Industrial and Manufacturing Engineering (MIME). As a Land/Sea/Air/Space/Sun Grant institution, with strong ties to oceanography and the NOAA fleet, as well as the host of an FAA UAV test site, OSU offers many opportunities to collaborate across disciplines and utilize Robotics as an enabling technology. Appointment is anticipated at the Assistant Professor rank, but candidates with exceptional qualifications may be considered for appointment at the rank of Associate Professor or Professor. Applicants should demonstrate a strong commitment and capacity to initiate new funded research as well as to expand, complement, and collaborate with existing research programs within and outside of the OSU College of Engineering. Further, applicants should demonstrate a strong commitment to graduate and undergraduate teaching, including developing new courses related to their research expertise. Oregon State is located in Corvallis, at the heart of Oregon?s Willamette Valley. Surrounded by forests and mountains, Corvallis combines the amenities of a college town with ample opportunity for outdoor recreation and fresh local food. Portland, the Cascade mountain range, and the Oregon Coast are all within easy reach. Oregon State University has a strong institutional commitment to diversity and multiculturalism, and provides a welcoming atmosphere with unique professional opportunities for leaders from underrepresented groups. OSU seeks diversity as a source of enrichment for our university community. We are an Affirmative Action/Equal Opportunity employer, and particularly encourage applications from members of historically underrepresented racial/ethnic groups, women, individuals with disabilities, veterans, LGBTQ community members, and others who share our vision of an inclusive community. The College of Engineering ranks high nationally in terms of the percentage of women faculty, and the university supports dual-career applications. Apply online at http://jobs.oregonstate.edu/postings/34121 (posting: P00825UF) with the following documents: A letter of interest; vita; a two-page statement of research interests; a one-page statement of teaching interests; a one-page statement on past efforts and future plans to promote equity and inclusion; and names and contact information for at least three references. To be assured full consideration, applications should be received by December 15, 2016. From luigi.malago at gmail.com Thu Oct 27 02:08:56 2016 From: luigi.malago at gmail.com (=?UTF-8?Q?Luigi_Malag=C3=B2?=) Date: Thu, 27 Oct 2016 09:08:56 +0300 Subject: Connectionists: Postdocs in Riemannian Manifold Optimization, Deep Learning and Information Geometry at RIST, Romania Message-ID: [Our apologies for cross postings] The Romanian Institute of Science and Technology (RIST) has an opening for 3 postdoc positions, in the context of the DeepRiemann project ?Riemannian Optimization Methods for Deep Learning?, funded by European structural funds through the Competitiveness Operational Program (POC 2014-2020). The appointments will be for 2 years, with possible extensions up to 4 years. The DeepRiemann project aims at the design and analysis of novel training algorithms for Neural Networks in Deep Learning, by applying notions of Riemannian optimization and differential geometry. The task of the training a Neural Network is studied by employing tools from Optimization over Manifolds and Information Geometry, by casting the learning process to an optimization problem defined over a statistical manifold, i.e., a set of probability distributions. The project is highly interdisciplinary, with competences spanning from Machine Learning to Optimization, Deep Learning, Statistics, and Differential Geometry. The objectives of the project are multiple and include both theoretical and applied research, together with industrial activities oriented to transfer knowledge, from the institute to a startup or spin-off of the research group. The positions will be part of the new Machine Learning and Optimization group, which will be performing research at the intersection of Machine Learning, Stochastic Optimization, Deep Learning, and Optimization over Manifolds, from the unifying perspective of Information Geometry. The group is one of two newly-formed groups in Machine Learning at RIST, where about 20 new postdoctoral research associates and research software developers will be hired in the next year. The official job announcement can be seen here: http://rist.ro/en/details/news/postdoc-positions-in-machine- learning-optimization-deep-learning-and-information-geometry.html # Jobs Description # The three open positions will focus on different and overlapping aspects of the project: 1) Optimization Algorithms over Statistical Manifolds with Applications to Deep Learning The postdoctoral researcher will conduct research on the design and implementation of novel first- and second-order methods for the optimization of functions defined over statistical models, such as exponential families, the Gaussian distribution, and Markov Random Fields. In particular the research will focus on the optimization problem associated to the training of a Neural Network, which will be studied from the perspective of Optimization over Manifolds with non-Euclidean geometries. The postdoctoral candidate will develop optimization algorithms which explicitly take into account the Riemannian and dual-affine Hessian geometries of the search space, given by the Fisher information metric. Such algorithms should be efficient, scalable, largely parallelizable, and suitable for the large scale and big data settings. Keywords: stochastic gradient descent, Riemannian manifolds, dually-flat Hessian geometries, optimization over manifolds, second-order optimization methods, large scale optimization. 2) Theory of Neural Networks The postdoctoral researcher will contribute towards the definition of a probabilistic and geometric framework for the study of deep Neural Networks aimed at a better understanding of the working mechanisms behind the success of Deep Learning. The analysis is focused towards a better understanding of what enables Deep Learning systems to achieve remarkable successes, and of its limits, in classification and predictive analysis, with a particular focus on the learning task, in order to guide the development of novel algorithms. The research will include the study of the representational power of various Neural Networks topologies, by taking into consideration the impact of hierarchical architectures with respect to the expressiveness of the network; and the analysis of the number of local minima and of saddle points, which appear during the training and which strongly affect convergence of the optimization algorithms, depending on the nature of the network. Keywords: theory of neural networks, deep learning, learning representations, expressive power of neural networks. 3) Information Geometry of dually-flat Hessian Manifolds The postdoctoral researcher will focus on the characterization of first and second-order Riemannian and affine geometries of statistical models, or more in general Hessian manifolds, aimed at the study of optimization methods over statistical manifolds. Neural Networks can be modeled as statistical manifolds, or manifolds of Neural Networks, and the training of the network can be studied as an optimization problem over a non-linear manifold, where the weights of the network are the parameters of the model and thus the variables of the function to be optimized. The purpose of the analysis is to introduce alternative second-order approximations of a function over a statistical manifold, depending on the choice of the connection and thus how parallel transport is implemented, which are at the basis of the design of second-order optimization methods. Keywords: information geometry, geometry of statistical models, natural gradient, dually-flat manifolds, Hessian geometries. # Desired Qualifications # - PhD in machine learning, theoretical computer science, stochastic optimization, statistics, applied mathematics, including fields such as manifold optimization, differential geometry, statistical mechanics, and related fields - Strong publication record - Strong analytical skills, such as problem solving and logical thinking - Enthusiasm to work in a multidisciplinary and international research environment - Good written and oral communication skills in English Knowledge in machine learning is helpful, but not strictly mandatory. Doctoral students close to the competition of their thesis will also be considered. The positions are to start as early as December 2016 or at any agreed later date. Applications will be reviewed as they are received. RIST offers competitive salaries and top-level working conditions. The net salary for these positions will be around 2.000 euro per month, with a possible increase up to 2.200 euro, based on new tax incentives for research and development activities in Romania. Positions are endowed with travel resources. The cost of living in Cluj is significantly lower than in Western Europe or the USA (e.g., it is 1/3 of the cost of living in London, UK). # How to Apply # In order to apply to this position, the candidate should send an email to deepriemann.jobs at rist.ro, mentioning in the subject of the email "DeepRiemann Postdoc Application". The email should include among the attachments: - A cover letter - A complete CV with full list of publications - A short research statement (max 3 pages), which describes your research interests and explain why your skills, knowledge and experience makes you a suitable candidate for one or more of the open positions - The pdfs of 2 selected publications - Name and contact information of up to 3 referees, which will be contacted directly by the institute for a reference letter Informal inquiries can be sent to Dr. Luigi Malag? , Principal Investigator of the DeepRiemann project. # About the Institute # The Romanian Institute of Science and Technology is a non-governmental, not-for-profit, independent research institute, founded in 2009, with the purpose of offering scientists a place to conduct research in Romania with top working conditions, comparable to those you can find in Western Europe. RIST currently performs research on computational and experimental neuroscience, computational intelligence, machine learning, and dynamical systems. The institute is currently undergoing a phase of significant and sustained growth supported by European and Romanian structural funds, with plans for hiring around 20 new scientists and researchers in the next year. The institute has close contacts with the Babe?-Bolyai University, which is the largest university in Romania, and with the Technical University of Cluj-Napoca. The institute is located in Cluj-Napoca, in the heart of Transylvania, which has been named by Lonely Planet as the top region to visit in 2016. Cluj is a welcoming and innovative city, recently listed as one of the major tech hubs (with a 9% growth per year for IT industry). Cluj has 12 universities, over 70k students every year, and an extremely vibrant startup scene, which has recently named the Silicon Valley of Transylvania. Cluj is Europe's friendliest city for foreigners, according to a study by the UK Office of National Statistics, and Romania is no. 16 in the Internations best expat destinations of 2016. About 1100 French citizens, 800 Italian citizens and 500 German citizens live in Cluj (source). The city has an international airport, only 8km away from the city center, with flights to more than 30 European destinations. More information about Cluj: https://vimeo.com/171864331 https://vimeo.com/166021527 -------------- next part -------------- An HTML attachment was scrubbed... URL: From sheikh at tk.tu-darmstadt.de Thu Oct 27 04:07:30 2016 From: sheikh at tk.tu-darmstadt.de (Sheikh Mahbub Habib) Date: Thu, 27 Oct 2016 08:07:30 +0000 Subject: Connectionists: [CFP] 11th IFIP Trust Management Conference 2017, Gothenburg, Sweden Message-ID: <0EFBD807BC4DE04286BB540DC72ADDA8BC24523B@exchange01.tk.informatik.tu-darmstadt.de> IFIPTM 2017 - Call for Papers ------------------------------------------------------------------------------- The 11th IFIP International Conference on Trust Management Gothenburg, 12-16 June 2017 http://ifiptm2017.chalmers.se ------------------------------------------------------------------------------- Trust is an essential glue for any society, whether formed by human or artificial agents, whether in a real-life or an online setting. This trust needs to be established, reinforced or abolished to reflect changes in the society and its participants. The mechanisms for such trust management may be psychological or sociological in the case of humans, algorithmic or probabilistic, e.g., in the case of artificial agents. Services for brokering, certification, recommendation, legal enforcement, identity and reputation management may also help the agent in this management task, and they are all the more useful given the increasing scale and virtual nature of societies. Indeed, applications such as online social networks, collaborative systems or e-commerce need to contend with high transaction volume, anonymity, and malicious behavior. Solutions to these challenges need to be validated using realistic models and benchmarks. Now in its 11th edition, IFIPTM is a well-established conference in the field of trust, security and privacy, and invites contributions in all aspects of trust management, including but not limited to: Trust in Information Technology - formal aspects (specification, reasoning, and analysis) - trust-based and trust-aware IT policy management - trust in social networks and emerging contexts - trust in collaborative applications, crowd-sourcing and wiki systems - trust in human-computer interaction and usable systems - case studies and applications Socio-Technical, economic and sociological Trust - economic modeling of trust, risk and control; economics of trusted data quality - trust, control and reputation effects in social networking, e- and m-commerce - trust and socio materiality; socio-technical network structures; biological trust - ethical, sociological, psychological, legal aspects Trust and reputation management systems - architectures and models - benchmarks, metrics and computation Identity management and trust - anonymity, privacy and accountability - identity and personal information brokering - legal aspects Secure, trustworthy and privacy-aware systems - platforms and standards - software and services Trust building in Large scale systems - trust in Cloud environments - large Identity Management Systems like UID/SSN, Banks, Mobile user groups - trust management for large user groups including machine and human participation SPECIAL TRACK The special track "Trust on the road" aims to attract researchers and practitioners investigating issues of trustworthiness, security, privacy, and overall trust in automotive systems. Such systems range from the individual vehicle to vehicles communicating both with other vehicles (v2v) and with the physical infrastructure around them (v2i) as well as vehicles forming ad-hoc networks and using cloud-based networks for various services. The trustworthiness of exchanged information, the security of the connections, the privacy of the data, and the trust of the user in the provided services are crucial for the acceptance and proliferation of such safety-critical technology. In the context of the special track, we aim to explore the current state of the art and future research directions with perspectives from researchers as well as representatives of the automotive industry. In particular, we are interested in novel contributions with regard to the following topics focusing on trust within the automotive domain: - Trust, security, privacy, liability, and dependability in vehicular networks - Trust models and architectures for vehicular networks - Security engineering, formal methods, development and validation tools - In-vehicle communications (wireless or wired), in-vehicle architecture and system design - Vehicle-to-vehicle (V2V) communications and integration with on-board systems and networks - Vehicle-to-infrastructure (V2I) communications and protocols - Security of software downloads and remote diagnostics - In-vehicle communications and trust enhancing architectures (wireless or wired) - Security and privacy issues when using cloud services - Results from experimental systems, testbeds, and pilot studies - Awareness applications in vehicular networks - Applications and services to enhance safety, performance, and driver behavior - Standardization efforts w.r.t. security, privacy and safety PAPER SUBMISSION IFIPTM 2017 welcomes submissions of both full and short papers on any topic related to the IFIPTM themes of trust, security and privacy and the topics mentioned above. Submitted full papers must not exceed 16 pages in length, including bibliography and well-marked appendices; short papers must not exceed 8 pages in length. Interdisciplinary and multidisciplinary papers are encouraged and welcome. Submission will be through the EasyChair conference management system. Papers must be submitted as a single PDF file, formatted using the LNCS format. As previous editions, papers will be published by Springer under AICT series. Submit at https://easychair.org/conferences/?conf=ifiptm2017. Authors of selected papers will be invited to extend and improve their contributions for a special issue of the Web Intelligence journal (IOS Press). IMPORTANT DATES Paper submission: January 30, 2017 (firm deadline) Author notification: March 6, 2017 Camera-ready version: March 27, 2017 Conference dates: June 12-16, 2017 ORGANISING COMMITTEE General Chairs Simone Fischer-H?bner, Karlstad University, Sweden Stephen Marsh, University of Ontario Institute of Technology, Oshawa, Ontario, Canada Program Chairs Babak Esfandiari, Carleton University, Ottawa, Ontario, Canada Jan-Philipp Stegh?fer, Chalmers | University of Gothenburg, Sweden Special Track Chair Tomas Olovsson, Chalmers | University of Gothenburg, Sweden ******* Best regards ---- Dr. Sheikh M. Habib Area Head, Smart Security and Trust Telecooperation Division Department of Computer Science Technische Universit?t Darmstadt Germany Tel.:+4961511623199 Web: https://www.tk.informatik.tu-darmstadt.de/de/people/sheikh-mahbub-habib From julien.mayor at psykologi.uio.no Thu Oct 27 09:45:00 2016 From: julien.mayor at psykologi.uio.no (Julien Mayor) Date: Thu, 27 Oct 2016 13:45:00 +0000 Subject: Connectionists: Post-Doctoral Research Fellowship in Developmental Psychology Message-ID: <9585d4105bba41728dfacedbcad97771@mail-ex11.exprod.uio.no> ***Post-Doctoral Research Fellowship in Developmental Psychology*** Dear colleagues, A 3- to 4-year Post-Doctoral position is available at the Department of Psychology of the University of Oslo. The Post-Doctoral fellow will work on a project aiming at uncovering learning mechanisms underlying infant speech perception, word learning and phoneme acquisition, via the creation of computational models, as well as their validations using eye-tracking experiments. For more details about the project and how to apply, please consult: http://uio.easycruit.com/vacancy/1718497/65775?iso=no Further enquiries can be made directly to: julien.mayor at psykologi.uio.no. Please note the tight deadline, on November 30th, 2016. Kind regards, julien From doya at oist.jp Thu Oct 27 10:31:06 2016 From: doya at oist.jp (Kenji Doya) Date: Thu, 27 Oct 2016 23:31:06 +0900 Subject: Connectionists: ISSA Summer School 2017 on Consciousness and Intelligence: Call for Applications In-Reply-To: <20160918.113711.2810495729851306.piet@ias.edu> References: <20160918.113711.2810495729851306.piet@ias.edu> Message-ID: <9967BC99-44FC-4AA2-B3DF-BF6CC626041F@oist.jp> Call for Applications: ISSA Summer School 2017 https://groups.oist.jp/issa Date: May 22nd ? June 2nd, 2017 Venue: Center for Information and Neural Networks (CiNet), Osaka, Japan https://cinet.jp/english/contact/ The Initiative for a Synthesis in Studies of Awareness, ISSA for short, is a group of scientists advocating an integrative approach to the study of consciousness and intelligence. ISSA will organize a two-week Summer School, with lectures covering a variety of topics in experimental and computational neuroscience, cognitive science, philosophy, complex systems, robotics and artificial intelligence. Following the lectures in the morning, students will engage in group disucussions and hand-on exercises in psychophysics, MRI, MEG, and robotics in the afternoon. First week: Fundamental lecturers and group discussions ? Christof Koch (Allen Institute for Brain Science) ? Ryota Kanai (ARAYA Brain Imaging, YHouse) ? Larissa Albantakis (U Wisconsin-Madison) ? Dan Zahavi (U Copenhagen) ? Jun Tani (KAIST) Second week: Special topics and hands-on exercises ? Kaoru Amano (CiNet) ? Minoru Asada (Osaka U) ? Kenji Doya (OIST) ? Piet Hut (Institute for Advanced Study, ELSI, YHouse) ? Hiroshi Ishiguro (Osaka U, ATR) ? Shinji Nishimoto (CiNet) ? Mariko Osaka (CiNet) ? Nao Tsuchiya (Monash U) ? Noriko Yamagishi (CiNet) Application: We invite graduate students and postdoctoral researchers to participate in the summer school. Organizers will provide lodging for all accepted students and travel support for selected students. The applications will be open till December 25, 2016 from the web site (https://groups.oist.jp/issa). The result of selection, based on the research interest, educational background, and the balance of gender and geographic origins, will be notified by February 2017. Co-Sponsors ? Center for Information and Neural Networks (CiNet) ? CREST Artificial Consciousness Project (leader: Ryota Kanai) ? CREST Social Neuroscience Project (leader: Masahiko Haruno) ? Earth-Life Science Institute (ELSI), Tokyo Institute of Technology ? KAKENHI Mental Time Project (leader: Shigeru Kitazawa) ? KAKENHI Artificial Intelligence and Brain Science Project (leader: Kenji Doya) ? Okinawa Institute of Science and Technology (OIST) ? YHouse (leaders: Piet Hut and Ryota Kanai) Web site: https://groups.oist.jp/issa Contact: Neural Computation Unit, Okinawa Institute of Science and Technology ncus at oist.jp ---- Kenji Doya Neural Computation Unit, Okinawa Institute of Science and Technology 1919-1 Tancha, Onna, Okinawa 904-0495, Japan Phone: +81-98-966-8594; Fax: +81-98-966-2891 https://groups.oist.jp/ncu From dwang at cse.ohio-state.edu Thu Oct 27 13:27:58 2016 From: dwang at cse.ohio-state.edu (DeLiang Wang) Date: Thu, 27 Oct 2016 13:27:58 -0400 Subject: Connectionists: NEURAL NETWORKS, Nov. 2016 Message-ID: <080aeaf4-d1ba-4430-25be-180c32a8018e@cse.ohio-state.edu> Neural Networks - Volume 83, November 2016 http://www.journals.elsevier.com/neural-networks Rank-based pooling for deep convolutional neural networks Zenglin Shi, Yangdong Ye, Yunpeng Wu Approximate Bayesian MLP regularization for regression in the presence of noise Jung-Guk Park, Sungho Jo Implementation of Imitation Learning using Natural Learner Central Pattern Generator Neural Networks Hamed Shahbazi, Reyhaneh Parandeh, Kamal Jamshidi Relating observability and compressed sensing of time-varying signals in recurrent linear networks MohammadMehdi Kafashan, Anirban Nandi, ShiNung Ching Stability analysis for uncertain switched neural networks with time-varying delay Wenwen Shen, Zhigang Zeng, Leimin Wang Massively parallel WRNN reconstructors for spectrum recovery in astronomical photometrical surveys Christian Napoli, Emiliano Tramontana A theory of local learning, the learning channel, and the optimality of backpropagation Pierre Baldi, Peter Sadowski Synchronization of Markovian jumping inertial neural networks and its applications in image encryption M. Prakash, P. Balasubramaniam, S. Lakshmanan Computational analysis of memory capacity in echo state networks Igor Farkas, Radomir Bosak, Peter Gergel Simbrain 3.0: A flexible, visually-oriented neural network simulator Zachary Tosi, Jeffrey Yoshimi From dhallabhinav at gmail.com Thu Oct 27 13:35:25 2016 From: dhallabhinav at gmail.com (abhinav dhall) Date: Thu, 27 Oct 2016 13:35:25 -0400 Subject: Connectionists: Submission deadline approaching - IEEE ISBA 2017 - International Conference on Identity, Security and Behavior Analysis 2017 Message-ID: [Apologies for cross-postings] Submission deadline approaching - October 31 2016 ----------------------------------------------- IEEE International Conference on Identity, Security and Behavior Analysis (ISBA 2017) Location: New Delhi, India Dates: February 22-24 2017 http://ieee-biometrics.org/isba2017/ ----------------------------------------------- The third ISBA is a unique conference series initiated by the IEEE Biometrics and will be held in New Delhi, India. This conference is intended to meet the emerging need for a winter meeting, especially for the Asian participants where the introduction of large scale biometrics programs have attracted significant increase in research and development efforts. It will be a forum that brings together experts in biometrics, security, and human behavior to consider research issues and solutions that are robust, comprehensive, and broader than currently considered in each of these individual research areas. This conference serves to provide a new form for such broad areas defining human side of security and user behavior as well as social influence in the biometrics security. Topics of interest include, but are not limited to: ? Anti-Spoofing, Behavioral Biometrics, Biometric System Evaluation, Biometrics in Law Enforcement, Cybercrime ? De-identification, Detection and Tracking, Device Identification, Digital Forensics ? Human Behavior Analysis, Human Activity Understanding, Identity Management, Information Security, Person Re-identification ? Performance Evaluation, Privacy-preserving Computing, Predictive Analytics, Single and Multi-modal Biometrics ? Social Biometrics, Social and Criminal Network Inference, Surveillance Identification, Template Protection and Data Privacy ? Usability and Performance, User-centric Biometric Security Submitted papers may not be accepted or under review elsewhere. Submissions may be up to eight pages in conference format (double blind reviewing). Papers accepted and presented at ISBA2017 will be published in conference proceedings and made available in IEEE Xplore library. Important dates Submission deadline: October 31, 2016 Decision to authors: December 10, 2016 Camera ready submission: December 20, 2016 Conference: February 22-24, 2017 General Chair Rama Chellappa (University of Maryland, USA) General Co-chairs Ajay Kumar (PolyU, Hongkong) Richa Singh (IIIT-Delhi, India) Program Co-chairs M. Ehsan Hoque (University of Rochester, USA) Nitesh Saxena (University of Alabama at Birmingham, USA) Vishal M. Patel (Rutgers University, USA) Mayank Vatsa (IIIT-Delhi, India) Publication Chair Soma Biswas (Indian Institute of Science, India) Finance Chair Angshul Majumdar (IIIT-D, India) Publicity Chair Abhinav Dhall (University of Waterloo, Canada) Industry Liaison Sameer Shah (HCL, India) http://ieee-biometrics.org/isba2017/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From jdrugo at gmail.com Thu Oct 27 22:37:21 2016 From: jdrugo at gmail.com (Jan Drugowitsch) Date: Thu, 27 Oct 2016 22:37:21 -0400 Subject: Connectionists: Postdoc in computational neuroscience at Harvard Message-ID: Dear all, Jan Drugowitsch (Department of Neurobiology, Harvard) and Sam Gershman (Department of Psychology, Harvard) are seeking a postdoctoral fellow to work on a project combining computational modeling, psychophysics, and clinical studies. The project focuses on the neural basis of visual structure discovery, using motion perception as a model system. Our goal is to understand how neural circuits represent and reason about complex combinatorial structures, and how these neural circuits break down in autism. The Drugowitsch and Gershman labs are located in the Longwood medical area and Harvard?s Cambridge campus, respectively. Harvard, and the Boston area in general, has an excellent neuroscience community and programs in engineering, statistics, and related fields. Candidates must have a Ph.D. in a quantitative discipline and strong background in Bayesian modeling and computational neuroscience. Experience with visual psychophysics experiments is desirable but not essential. Applicants should send a CV and statement of research interests to Jan Drugowitsch (Jan_Drugowitsch at hms.harvard.edu). The initial appointment is for one year with the expectation of extension given satisfactory performance. Applications will be reviewed until the position is filled. Best regards, Jan Drugowitsch Assistant Professor in Neurobiology Harvard Medical School From tani1216jp at gmail.com Fri Oct 28 00:11:23 2016 From: tani1216jp at gmail.com (Jun Tani) Date: Fri, 28 Oct 2016 13:11:23 +0900 Subject: Connectionists: New book "Exploring Robotic Minds" from Oxford Univ. Press Message-ID: Dear colleagues, I?m happy to announce my new book just published from Oxford Univ. Press as follows. ?Exploring Robotic Minds: Actions, Symbols, and Consciousness as Self-Organizing Dynamic Phenomena? by Jun Tani https://global.oup.com/academic/product/exploring- robotic-minds-9780190281069?cc=kr&lang=en& https://www.amazon.com/Exploring-Robotic-Minds- Consciousness-Self-Organizing/dp/0190281065 Thank you for your attention!! Best wishes, Jun Jun Tani, Ph.D Professor, Department of Electrical Engineering, KAIST Building: N1, room: 516 http://neurorobot.kaist.ac.kr/tani.htm tani1216jp at gmail.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From evomusart at gmail.com Fri Oct 28 08:02:44 2016 From: evomusart at gmail.com (=?UTF-8?Q?Jo=C3=A3o_Correia?=) Date: Fri, 28 Oct 2016 13:02:44 +0100 Subject: Connectionists: Deadline Extension - EvoMusArt 2017 Message-ID: ------------------------------------------------ Call for papers for the 6th EVOMUSART conference ------------------------------------------------ ------------- NEWS: DEADLINE EXTENSION : 15th of November NEWS: For the 20th year anniversary of the evo* conferences a website was made available with all the information on the evoMUSART papers since 2003. Feel free to browse and bookmark: http://evomusart-index.dei.uc.pt/ ------------- The 6th International Conference on Computational Intelligence in Music, Sound, Art and Design (evoMUSART) will be held in Amsterdam in 19-21 April 2017, as part of the evo* event. The main goal of EvoMusArt is to bring together researchers who are using Computational Intelligence techniques for artistic tasks such as visual art, music, architecture, video, digital games, poetry, or design. The conference gives researchers in the field the opportunity to promote, present and discuss ongoing work in the area. Important dates: Submission: 15 November 2016 Notification to authors: 9 January 2017 Camera-ready deadline: 25 January 2017 Evo*: 19-21 April 2017 We welcome submissions which use Computational Intelligence techniques (e.g. Evolutionary Computation, Artificial Life, Machine Learning, Swarm Intelligence) in the generation, analysis and interpretation of art, music, design, architecture and other artistic fields. Submissions must be at most 16 pages long, in Springer LNCS format (instructions downloadable from http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0). Each submission must be anonymised for a double-blind review process and submitted to http://myreview.csregistry.org/evomusart17/ . The deadline for submission is 1 November 2016, and acceptance notification on 9 January 2017. Accepted papers will be presented orally or as posters at the event and included in the evoMUSART proceedings published by Springer Verlag in a dedicated volume of the Lecture Notes in Computer Science series. Indicative topics include but are not limited to: * Systems that create drawings, images, animations, sculptures, poetry, text, designs, webpages, buildings, etc.; * Systems that create musical pieces, sounds, instruments, voices, sound effects, sound analysis, etc...; * Systems that create artifacts such as game content, architecture, furniture, based on aesthetic and functional criteria; * Systems that resort to computational intelligence to perform the analysis of image, music, sound, sculpture, or some other types of artistic object; * Systems in which computational intelligence is used to promote the creativity of a human user; * Theories or models of computational aesthetics; * Computational models of emotional response, surprise, novelty; * Representation techniques for images, videos, music, etc; * Surveys of the current state-of-the-art in the area; * New ways of integrating the user in the process (e.g. improvisation, co-creation, participation). More information on the submission process and the topics of evoMUSART 2017 can be found at http://www.evostar.org/2017/cfp_evomusart.php We look forward to seeing you in Amsterdam in 2017! The evoMUSART 2017 organisers From rsun at rpi.edu Fri Oct 28 18:25:57 2016 From: rsun at rpi.edu (Professor Ron Sun) Date: Fri, 28 Oct 2016 18:25:57 -0400 Subject: Connectionists: New book: "Anatomy of the Mind", from Oxford Univ. Press In-Reply-To: References: Message-ID: New book published by Oxford University Press, 2016: "Anatomy of the Mind: Exploring Psychological Mechanisms and Processes with the Clarion Cognitive Architecture" by Ron Sun (part of Oxford Series on Cognitive Models and Architectures) For details, see: https://global.oup.com/academic/product/anatomy-of-the-mind-9780199794553?cc=us&lang=en& or https://www.amazon.com/Anatomy-Mind-Psychological-Architecture-Architectures/dp/0199794553 Thanks. ======================================================== Professor Ron Sun Cognitive Sciences Department Rensselaer Polytechnic Institute 110 Eighth Street, Carnegie 302A Troy, NY 12180, USA phone: 518-276-3409 fax: 518-276-8268 email: dr.ron.sun [AT] gmail.com web: http://sites.google.com/site/drronsun https://scholar.google.com/citations?user=MD8-GMcAAAAJ&hl=en ======================================================= From ahu at cs.stir.ac.uk Fri Oct 28 13:26:00 2016 From: ahu at cs.stir.ac.uk (Dr Amir Hussain) Date: Fri, 28 Oct 2016 18:26:00 +0100 Subject: Connectionists: Call for Papers: IEEE Transactions on Affective Computing Special Issue: "Affective Reasoning for Big Social Data Analysis" Message-ID: IEEE Transactions on Affective Computing ( http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5165369 - ISI-SCI Impact Factor: 1.87) invites papers for a new Special Issue on: "Affective Reasoning for Big Social Data Analysis" Full Call for Papers available below, and also online: https://www.computer.org/cms/Computer.org/transactions/cfps/cfp_tacsi_arbsda.pdf Guest Editors Erik Cambria, Nanyang Technological University, Singapore ( cambria at ntu.edu.sg) Amir Hussain, University of Stirling, United Kingdom (ahu at cs.stir.ac.uk) Alessandro Vinciarelli, University of Glasgow, United Kingdom ( vincia at dcs.gla.ac.uk) Important Dates: Submission Deadline: December 1st, 2016 Notification of Acceptance: Feburary 1st, 2017 Revised submission Deadline: April 1st, 2017 Final Manuscripts Due: June 1st, 2017 Background and Motivation: As the Web rapidly evolves, Web users are evolving with it. In an era of social connectedness, people are becoming increasingly enthusiastic about interacting, sharing, and collaborating through social networks, online communities, blogs, Wikis, and other online collaborative media. In recent years, this collective intelligence has spread to many different areas, with particular focus on fields related to everyday life such as commerce, tourism, education, and health, causing the size of the Web to expand exponentially. The distillation of knowledge from such a big amount of unstructured information, however, is an extremely difficult task, as the contents of today?s Web are perfectly suitable for human consumption, but remain hardly accessible to machines. The opportunity to capture the opinions of the general public about social events, political movements, company strategies, marketing campaigns, and product preferences has raised growing interest both within the scientific community, leading to many exciting open challenges, as well as in the business world, due to the remarkable benefits to be had from marketing and financial market prediction. Existing approaches to big social data analysis mainly rely on parts of text in which sentiment is explicitly expressed, e.g., through polarity terms or affect words (and their co-occurrence frequencies). However, opinions and sentiments are often conveyed implicitly through latent semantics, which make purely syntactical approaches ineffective. In this light, this Special Issue focuses on the introduction, presentation, and discussion of novel techniques that further develop and apply affective reasoning tools and techniques for big social data analysis. A key motivation for this Special Issue, in particular, is to explore the adoption of novel affective reasoning frameworks and cognitive learning systems to go beyond a mere word-level analysis of natural language text and provide novel concept-level tools and techniques that allow a more efficient passage from (unstructured) natural language to (structured) machine-processable affective data, in potentially any domain. Articles are thus invited in areas such as machine learning, weakly supervised learning, active learning, transfer learning, deep neural networks, novel neural and cognitive models, data mining, pattern recognition, knowledge-based systems, information retrieval, natural language processing, common-sense reasoning, and big data computing. Topics include, but are not limited to: ? Machine learning for big social data analysis ? Affective common-sense reasoning ? Social network modeling and analysis ? Social media representation and retrieval ? Multi-modal sentiment analysis ? Affective human-agent, -computer, and -robot interaction ? User profiling and personalization ? Aided affective knowledge acquisition ? Multi-lingual sentiment analysis ? Time-evolving sentiment tracking The Special Issue also welcomes papers on specific application domains of big social data analysis, e.g., influence networks, customer experience management, intelligent user interfaces, multimedia management, computer-mediated human-human communication, enterprise feedback management, surveillance, art. The authors will be required to follow the Author?s Guide for manuscript submission to IEEE ToAC. -- The University achieved an overall 5 stars in the QS World University Rankings 2015 The University of Stirling is a charity registered in Scotland, number SC 011159. -------------- next part -------------- An HTML attachment was scrubbed... URL: From boracchi at elet.polimi.it Fri Oct 28 19:00:02 2016 From: boracchi at elet.polimi.it (Giacomo Boracchi) Date: Sat, 29 Oct 2016 01:00:02 +0200 Subject: Connectionists: CFP "Concept Drift, Domain Adaptation & Learning in Dynamic Environments", SS @ IJCNN 2017 Message-ID: CALL FOR PAPERS Special Session on "Concept Drift, Domain Adaptation & Learning in Dynamic Environments" will be held within the INNS-IEEE IJCNN 2017, Anchorage Alaska in May, 14-19 2017. http://home.deib.polimi.it/boracchi/events/ijcnn2017_SS/index.html http://www.ijcnn.org/ ********************************************************** IMPORTANT DATES Paper submission: November 15th, 2016 Paper Decision notification: January 20th, 2017 Camera-ready submission: February 20th, 2017 Conference Dates: May 14 - 19th, 2017 *********************************************************** One of the fundamental goals in computational intelligence is to achieve brain-like intelligence, a remarkable property of which is the ability to incrementally learn from noisy and incomplete data, and ability to adapt to changing environments. The special session aims at presenting novel approaches to incremental learning and adaptation to dynamic environments both from the more traditional and theoretical perspective of computational intelligence and from the more practical and application-oriented one. This Special Session aspires at building a bridge between academic and industrial research, providing a forum for researchers in this area to exchange new ideas with each other, as well as with the rest of the neural network & computational intelligence community. *Topics* Papers must present original work or review the state-of-the-art in the following non-exhaustive list of topics: . Methodologies/algorithms/techniques for learning in dynamic/non-stationary environments . Incremental learning, lifelong learning, cumulative learning . Domain adaptation and covariate-shift adaptation . Semi-supervised learning methods for nonstationary environments . Ensemble methods for learning in nonstationary environments . Learning under concept drift and class imbalance . Learning recurrent concepts . Change-detection and anomaly-detection algorithms . Information-mining algorithms in nonstationary datastreams . Cognitive-inspired approaches for adaptation and learning . Applications that call for learning in dynamic/non-stationary environments, or change/anomaly detection, such as o adaptive classifiers for concept drift o adaptive/Intelligent systems o fraud detection o fault detection and diagnosis o network-intrusion detection and security o intelligent sensor networks o time series analysis . Benchmarks/standards for evaluating algorithms learning in non-stationary/dynamic environments *Keywords* Concept drift, nonstationary environment, change/anomaly detection, domain adaptation, incremental learning, data streams. *Paper Submission* THE DEADLINE FOR THE PAPER SUBMISSION TO THE SPECIAL SESSION IS THE SAME OF IJCNN 2017, November 15th 2017. All the submissions will be peer-reviewed with the same criteria used for other contributed papers. Perspective authors will submit their papers through the IJCNN 2017 conference submission system at http://www.ijcnn.org/ Please make sure to select the Special Session nr 9 "Concept Drift, Domain Adaptation & Learning in Dynamic Environments" from the "S. SPECIAL SESSION TOPICS" name in the "Main Research topic" dropdown list; Templates and instruction for authors will be provided on the IJCNN webpage http://www.ijcnn.org/ All papers submitted to the special sessions will be subject to the same peer-review procedure as regular papers, accepted papers will be published in the IEEE Conference Proceedings . Further information about IJCNN 2017 can be found at http://www.ijcnn.org/ For any question you may have about the Special Session or paper submission, feel free to contact Giacomo Boracchi *********************************************************** Special Session on "Concept Drift, Domain Adaptation & Learning in Dynamic Environments" @ IEEE IJCNN 2017 *Organizes* . Giacomo Boracchi (Politecnico di Milano, Dipartimento di Elettronica, Informazione e Bioingegneria, Italy) . Robi Polikar (Rowan University, Glassboro, NJ, USA) . Manuel Roveri (Politecnico di Milano, Dipartimento di Elettronica, Informazione e Bioingegneria, Italy) . Gregory Ditzler, (University of Arizona, AZ, USA) *TPC* . Alfred Bifet, University of Waikato, New Zealand . Gianluca Bontempi, Universit? Libre de Bruxelles, Belgium . Giovanni Da San Martino, Qatar Computing Research Institute . Barbara Hammer, Bielefeld University, Germany . Georg Krempl, University Magdeburg, Germany . Ludmilla Kuncheva, University of Bangor, Wales, UK . Vincent Lemaire, Orange Labs, France . Leandro L. Minku, University of Leicester, England, UK . Russel Pears, Auckland University of Technology, New Zealan . Leszek Rutkowski, Czestochowa University of Technology, Poland . Shiliang Sun, East China Normal University, China . Marley Vellasco, Pontif?cia Universidade Cat?lica do Rio de Janeiro, Brasil ********************************************************** -- Giacomo Boracchi, PhD DEIB - Dipartimento di Elettronica, Informazione e Bioingegneria Politecnico di Milano Via Ponzio, 34/5 20133 Milano, Italy. Tel. +39 02 2399 3467 http://home.dei.polimi.it/boracchi/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From ajyu at ucsd.edu Fri Oct 28 12:41:00 2016 From: ajyu at ucsd.edu (Angela Yu) Date: Fri, 28 Oct 2016 09:41:00 -0700 Subject: Connectionists: Postdoc position in computational modeling Message-ID: Applications are invited from highly motivated researchers for a postdoctoral position immediately available in the Computational & Cognitive Neuroscience Lab, led by Angela Yu, at University of California, San Diego. Candidates must have a strong background in mathematics and/or machine learning, and be committed to applying rigorous mathematical tools to modeling cognitive and neural processes. Experience or interest in carrying out human behavioral experiments (either in person or on Amazon M-Turk) and/or collaborating with other human/animal neuroscience laboratories is also desirable. Current research in the lab ranges across cognitive control, decision-making, visual search, active learning, social cognition, and machine learning. Accepted candidate would have great latitude in determining own research projects. Dr. Yu's lab is situated within the Cognitive Science department of UCSD, and affiliated with the Computer Science Department, Electrical Engineering Department, Neurosciences Graduate Program, and the Institute of Neural Computation. There are ample opportunities for collaborations with related groups across the UCSD main campus, the medical school, and the Salk Institute. Interested candidates should send a research statement, along with a CV including publications, to Dr. Angela Yu (ajyu at ucsd.edu ). Candidates are invited to explain in detail how their own research interests dovetail that of Dr. Yu's lab. Two or more letters of references should be sent directly to Dr. Yu. Dr. Yu will be interviewing candidates at the Society for Neuroscience Annual Meeting in San Diego, November 12-16, 2016. ------------------------------------- Angela J. Yu Associate Professor UCSD Cognitive Science www.cogsci.ucsd.edu/~ajyu ------------------------------------- -------------- next part -------------- An HTML attachment was scrubbed... URL: From ahu at cs.stir.ac.uk Fri Oct 28 13:53:15 2016 From: ahu at cs.stir.ac.uk (Dr Amir Hussain) Date: Fri, 28 Oct 2016 18:53:15 +0100 Subject: Connectionists: Increased Impact Factor (2015/16) and Table of Contents Alert: Cognitive Computation journal (Springer Nature): Vol.8, No.5 / Oct 2016 Issue Message-ID: Dear Colleagues: (with advance apologies for any cross-postings) We are delighted to announce the publication of Volume 8, No.5 / Oct 2016 Issue, of (Springer Nature's) Cognitive Computation journal - www.springer.com/12559 ================================================================= Important News: Increased Impact Factor & Six bi-monthly Journal Issues since 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) in 2011 The ISI IF for 2015/16 has increased to 1.933 (from 1.44 in 2014/15) - Thomson Reuters Journal Citation Reports? 2015 Many congratulations to the editors, reviewers and authors! 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, since 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, since Feb 2015! ================================= The October 2016 Issue comprises a Special Issue on: Advances in Brain-Inspired Cognitive Systems (BICS), including a selection of 18 papers. The Guest Editorial (by Bin Luo, Amir Hussain, Mufti Mahmud and Jin Tang) is available for FREE download from: http://link.springer.com/article/10.1007/s12559-016-9431-7 The full listing of published articles (Table of Contents) for this October 2016 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/12559/8/5/ A list of the journal's Open Access articles can be found here: http://link.springer.com/search?query=&search-within=Journal&facet-journal-id=12559&package=openaccessarticles 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 over 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 weeks of receipt. We also welcome relevant high quality multi-disciplinary proposals for Special Issues - three are already planned for 2016/17! (including an exciting forthcoming one, titled: "Advances in Biologically Inspired Reservoir Computing" : http://static.springer.com/sgw/documents/1570471/application/pdf/Advances+in+Biologically+Inspired+Reservoir+Computing.pdf - submissions are now closed!) 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 NEW: Open Access Springer Nature/BioMed Central (BMC) journal: Big Data Analytics (http://www.bdataanalytics.com/) - Now accepting submissions! NEW: Springer Series on Socio-Affective Computing: http://www.springer.com/series/13199 Also consider your work for a related forthcoming Book Series: Cognitive Computation Trends (emails us for details!) =========================================================== Table of Contents Alert -- Cognitive Computation Vol 8 No 5, October 2016 =========================================================== Advances in Brain-Inspired Cognitive Systems Bin Luo, Amir Hussain, Mufti Mahmud, Jin Tang http://link.springer.com/article/10.1007/s12559-016-9431-7/ Action-Based Pedestrian Identification via Hierarchical Matching Pursuit and Order Preserving Sparse Coding Si-Bao Chen, Yi Xin, Bin Luo http://link.springer.com/article/10.1007/s12559-016-9393-9/ A Generative Learning Approach to Sensor Fusion and Change Detection Alexander R. T. Gepperth, Thomas Hecht, Mandar Gogate http://link.springer.com/article/10.1007/s12559-016-9390-z/ A Human Visual Experience-Inspired Similarity Metric for Face Recognition Under Occlusion Jian-Xun Mi, Chao Li, Cong Li, Tao Liu, Ying Liu http://link.springer.com/article/10.1007/s12559-016-9420-x/ A Sensor Self-aware Distributed Consensus Filter for Simultaneous Localization and Tracking Xiangyuan Jiang, Peng Ren, Chunbo Luo http://link.springer.com/article/10.1007/s12559-016-9423-7/ Common Visual Patterns Discovery with an Elastic Matching Model Meili Zhao, Bo Jiang, Bin Luo, Jin Tang http://link.springer.com/article/10.1007/s12559-016-9401-0/ Discriminative Lasso Zhihong Zhang, Jianbing Xiahou, Zheng-Jian Bai, Edwin R. Hancock? http://link.springer.com/article/10.1007/s12559-016-9402-z/ Fast Robot Localization Approach Based on Manifold Regularization with Sparse Area Features Hua Wu, Yan-Xiong Wu, Chang-An Liu, Guo-Tian Yang, Shi-Yin Qin http://link.springer.com/article/10.1007/s12559-016-9427-3/ Hierarchical Visual Perception and Two-Dimensional Compressive Sensing for Effective Content-Based Color Image Retrieval Yan Zhou, Fan-Zhi Zeng, Hui-min Zhao, Paul Murray, Jinchang Ren http://link.springer.com/article/10.1007/s12559-016-9424-6/ Improved Reversible Image Authentication Scheme Zhaoxia Yin, Xuejing Niu, Zhili Zhou, Jin Tang, Bin Luo http://link.springer.com/article/10.1007/s12559-016-9408-6/ Multi-manifolds Discriminative Canonical Correlation Analysis for Image Set-Based Face Recognition Haifeng Hu, Jianquan Gu http://link.springer.com/article/10.1007/s12559-016-9403-y/ Target Tracking Based on Biological-Like Vision Identity via Improved Sparse Representation and Particle Filtering Gun Li, Zhong-yuan Liu, Hou-biao Li, Peng Ren http://link.springer.com/article/10.1007/s12559-016-9410-z/ A Bio-Inspired Incremental Learning Architecture for Applied Perceptual Problems Alexander Gepperth, Cem Karaoguz http://link.springer.com/article/10.1007/s12559-016-9389-5/ An Automated Method for Characterization of Evoked Single-Trial Local Field Potentials Recorded from Rat Barrel Cortex Under Mechanical Whisker Stimulation Mufti Mahmud, Claudia Cecchetto, Stefano Vassanelli http://link.springer.com/article/10.1007/s12559-016-9399-3/ A Neuro-Fuzzy Control System Based on Feature Extraction of Surface Electromyogram Signal for Solar-Powered Wheelchair M. Shamim Kaiser, Zamshed Iqbal Chowdhury, Shamim Al Mamun http://link.springer.com/article/10.1007/s12559-016-9398-4/ Biologically Inspired Progressive Enhancement Target Detection from Heavy Cluttered SAR Images Fei Gao, Fei Ma, Yaotian Zhang, Jun Wang, Jinping Sun, Erfu Yang http://link.springer.com/article/10.1007/s12559-016-9405-9/ Parallel Brain Simulator: A Multi-scale and Parallel Brain-Inspired Neural Network Modeling and Simulation Platform Xin Liu, Yi Zeng, Tielin Zhang, Bo Xu http://link.springer.com/article/10.1007/s12559-016-9411-y/ Sequentially Supervised Long Short-Term Memory for Gesture Recognition Peisong Wang, Qiang Song, Hua Han, Jian Cheng http://link.springer.com/article/10.1007/s12559-016-9388-6/ Towards a Biologically Inspired Soft Switching Approach for Cloud Resource Provisioning Amjad Ullah, Jingpeng Li, Amir Hussain, Erfu Yang http://link.springer.com/article/10.1007/s12559-016-9391-y/ ----------------------------------------------- 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/journ al/12559/6/4/page/1 The full listing of Vol. 7, No.1 / Feb 2015 can be viewed here: http://link.springer.com/journal/12559/7/1/ (with the first six papers part of 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 full listing of Vol. 7, No. 2 / April 2015, can be viewed here: http://link.springer.com/journal/12559/7/2/ This comprises a Special Issue on "Sentic Computing", Guest Edited by: E. Cambria and A. Hussain. The Guest Editorial titled: "Sentic Computing" is available (for free download) here: http://link.springer.com/article/10.1007/s12559-015-9325-0 The full listing of Vol. 7, No. 3 / June 2015, can be viewed here: http://link.springer.com/journal/12559/7/3/ The full listing of Vol. 7, No. 4 / August 2015, can be viewed here: http://link.springer.com/journal/12559/7/4/ This comprises an invited paper by A. Vinciarelli and A. Esposito, et al. titled: Open Challenges in Modelling, Analysis and Synthesis of Human Behaviour in Human?Human and Human?Machine Interactions, which is followed by six regular papers. The full listing of Vol. 7, No. 5 / October 2015, can be viewed here: http://link.springer.com/journal/12559/7/5/ The full listing of Vol. 7, No.6 / December 2015, can be viewed here: http://link.springer.com/journal/12559/7/6/ This comprises a Special Issue titled: "Dealing with Big Data-Lessons from Cognitive Computing" (the Guest Editorial is available for free download here: http://link.springer.com/article/10.1007/s12559-015-9364-6). This is followed by seven regular papers, including an invited paper by Hojjat Adeli et al. titled: "Nature Inspired Computing: An Overview and Some Future Directions" (free download available here: http://link.springer.com/article/10.1007/s12559-015-9370-8) The full listing of Vol. 8, No.1 / February 2016, can be viewed here: http://link.springer.com/journal/12559/8/1/ This comprises an invited paper by Ron Sun et al. titled: "Emotion: A Unified Mechanistic Interpretation from a Cognitive Architecture" (this is available for free download here: http://link.springer.com/content/pdf/10.1007%2Fs12559-015- 9374-4.pdf). This is followed by eight regular papers. The full listing of Vol. 8, No. 2 / April 2016, can be viewed here: http://link.springer.com/journal/12559/8/2/ This comprises two invited papers, the first by Yew-Soon Ong et al. (titled: Evolutionary Multitasking: A Computer Science View of Cognitive Multitasking) and the second by Zidong Wang et al. (titled: A Novel Switching Delayed PSO Algorithm for Estimating Unknown Parameters of Lateral Flow Immunoassay). These are followed by 10 regular papers, and finally a Special Issue titled: "Cognitively-Inspired Computing for Gerontechnology" (comprising five manuscripts, with the Guest Editorial available for free download here: http://link.springer.com/content/pdf/10.1007%2Fs12559-016-9392-x.pdf). The full listing of Vol. 8, No.3 / June 2016, can be viewed here: http://link.springer.com/journal/12559/8/3/ This Issue comprises two Open Access invited papers, the first by Hussein Abbass et al. (titled: "Trusted Autonomy and Cognitive Cyber Symbiosis: Open Challenges", available for free download from: http://link.springer.com/article/10.1007/s12559- 015-9365-5), and the second by Kevin Warwick et al. (titled: "Passing the Turing Test Does Not Mean the End of Humanity", available for free download from: http://link.springer.com/article/10.1007/s12559-015-9372-6). These are followed by 10 regular papers. The full listing of Vol. 8 No.4 / Aug 2016 can be viewed here: http://link.springer.com/journal/12559/8/4/ This Issue comprises an OPEN ACCESS invited paper, by Yiyu Yao (titled: Three-Way Decisions and Cognitive Computing, available for free download from: http://link.springer.com/article/10.1007/s12559-016-9397-5?view=classic ). This is followed by 16 regular papers. -- The University achieved an overall 5 stars in the QS World University Rankings 2015 The University of Stirling is a charity registered in Scotland, number SC 011159. -------------- next part -------------- An HTML attachment was scrubbed... URL: From tomas.hromadka at gmail.com Fri Oct 28 17:54:24 2016 From: tomas.hromadka at gmail.com (Tomas Hromadka) Date: Fri, 28 Oct 2016 23:54:24 +0200 Subject: Connectionists: COSYNE 2017: Abstract submission closes soon Message-ID: <790ad39c-9a4d-1348-2321-8146180f16cd@gmail.com> ==================================================== Computational and Systems Neuroscience 2017 (Cosyne) MAIN MEETING 23 - 26 February 2017 Salt Lake City, Utah WORKSHOPS 27 - 28 February 2017 Snowbird, Utah www.cosyne.org ==================================================== *IMPORTANT DATE* Abstract submission deadline is 10 November 2016 (11.59pm PST) COSYNE The annual Cosyne meeting provides an inclusive forum for the exchange of empirical and theoretical approaches to problems in systems neuroscience, in order to understand how neural systems function. The MAIN MEETING is single-track. A set of invited talks are selected by the Executive Committee, and additional talks and posters are selected by the Program Committee, based on submitted abstracts. The WORKSHOPS feature in-depth discussion of current topics of interest, in a small group setting. For details on workshop proposals please visit Cosyne.org -> Workshops. Cosyne topics include but are not limited to: neural coding, natural scene statistics, dendritic computation, neural basis of persistent activity, nonlinear receptive field mapping, representations of time and sequence, reward systems, decision-making, synaptic plasticity, map formation and plasticity, population coding, attention, and computation with spiking networks. We would like to foster increased participation from experimental groups as well as computational ones. Please circulate widely and encourage your students and postdocs to apply. When preparing an abstract, authors should be aware that not all abstracts can be accepted for the meeting, due to space constraints. Abstracts will be selected based on the clarity with which they convey the substance, significance, and originality of the work to be presented. For more information and details on submitting abstracts please visit www.cosyne.org, section Abstracts. CONFIRMED SPEAKERS Yoshua Bengio (Montreal) Brent Doiron (Pittsburgh) Catherine Du Lac (Harvard) Greg Gage (Backyard Brains) Surya Ganguli (Stanford) Maria Geffen (Penn) Ann Graybiel (MIT) Gero Miesenbock (Oxford) Liz Phelps (NYU) Jonathan Pillow (Princeton) Vanessa Ruta (Rockefeller) Daphna Shahomy (Columbia) Kay Tye (MIT) Nao Uchida (Harvard) ORGANIZING COMMITTEE: General Chairs: Megan Carey (Champalimaud) and Emilio Salinas (Wake Forest) Program Chairs: Ilana Witten (Princeton) and Eric Shea-Brown (U Washington) Workshop Chairs: Laura Busse (LMU, Munich) and Alfonso Renart (Champalimaud) Undergraduate Travel Chairs: Jill O'Reilly (Oxford) and Robert Wilson (U Arizona) Publicity Chair: Il Memming Park (Stony Brook) EXECUTIVE COMMITTEE: Anne Churchland (CSHL) Zachary Mainen (Champalimaud) Alexandre Pouget (U Geneva) Anthony Zador (CSHL) CONTACT cosyne.meeting [at] gmail.com COSYNE MAILING LISTS Please consider adding yourself to Cosyne mailing lists (groups) to receive email updates with various Cosyne-related information and join in helpful discussions. See Cosyne.org -> Mailing lists for details. From terry at salk.edu Fri Oct 28 18:49:52 2016 From: terry at salk.edu (Terry Sejnowski) Date: Fri, 28 Oct 2016 15:49:52 -0700 Subject: Connectionists: NEURAL COMPUTATION - November 1, 2016 In-Reply-To: Message-ID: Neural Computation - Volume 28, Number 11 - November 1, 2016 Available online for download now: http://www.mitpressjournals.org/toc/neco/28/11 ----- Article Neural Quadratic Discriminant Analysis: Nonlinear Decoding With V1-like Computation Marino Pagan, Eero Simoncelli, and Nicole Rust Letters Identification of Stable Spike-Timing-Dependent Plasticity >From Spiking Activity With Generalized Multilinear Modeling Brian S. Robinson, Theodore W Berger, and Dong Song Variations on the Theme of Synaptic Filtering: A Comparison of Integrate-and-Express Models of Synaptic Plasticity for Memory Lifetimes Terry Elliott On the Analytical Solution of Firing Time for SpikeProp Simon de Montigny, Benooit R. Masse Continuous Online Sequence Learning With an Unsupervised Neural Network Model Yuwei Cui, Subutai Ahmad, and Jeff Hawkins Chaotic Resonance in Coupled Inferior Olive Neurons With the Llinas Approach Neuron Model Sou Nobukawa, Haruhiko Nishimura The Lamellar Structure of the Brain Fiber Pathways Vitaly L Galinsky, Lawrence R Frank An Online Structural Plasticity Rule for Generating Better Reservoirs Subhrajit Roy, Arindam Basu ------------ ON-LINE -- http://www.mitpressjournals.org/neuralcomp SUBSCRIPTIONS - 2016 - VOLUME 28 - 12 ISSUES Student/Retired $78 Individual $138 Institution $1,108 MIT Press Journals, One Rogers Street, Cambridge, MA 02142-1209 Tel: (617) 253-2889 FAX: (617) 577-1545 journals-cs at mit.edu ------------ From luca.oneto at unige.it Sat Oct 29 04:55:44 2016 From: luca.oneto at unige.it (Luca Oneto) Date: Sat, 29 Oct 2016 10:55:44 +0200 Subject: Connectionists: =?utf-8?q?JCNN_2017_SPECIAL_SESSION_on_=22Large_D?= =?utf-8?q?atasets_and_Big_Data_Analytics=22_2=C2=B0_CFP?= Message-ID: [Apologies if you receive multiple copies of this CFP] Call for papers: special session on "Large Datasets and Big Data Analytics: Theory, Methods, and Applications" at IJCNN 2017 International Joint Conference on Neural Networks (IJCNN 2017). 14-19 May 2017, Anchorage, Alaska, USA - http://www.ijcnn.org/ DESCRIPTION: The information age brings along an exponentially growing quantity of heterogeneous data from multiple sources in every aspect of our lives: data coming from social networks, internet of things, experiments in biology research and data from transportation systems are only a few examples. Recent trends in the area suggest that in the coming years the exponential data growth will continue, and that there is a strong need to find efficient solutions to deal with aspects such as data wrangling, real-time processing, information extraction and abstract model generation. Large datasets and big data analytics is the area of research focused on collecting, examining and processing large multi-structure, multi-modal, and multi-source datasets in order to discover patterns, correlations and extract information from data. In order to be able to perform such an analysis, conventional technologies and machine learning theory and algorithms are not directly applicable because they are not able to deal efficiently and effectively with such amount of data. Thus, specific techniques have to be developed. The purpose of this special session is to highlight recent advances in the field of large datasets and big data analytics. In particular, this session welcomes contributions toward both the development of new machine learning methods and the improvement of already available tools suited for big data analysis. We also encourage the submission of new theoretical results in the Statistical Learning Theory framework and innovative solutions to real world problems. In particular, topics of interest include, but are not limited to: - Statistical Learning Theory for Large Datasets; - Big Data Technologies; - Learning on data Streams; - Deep Learning for Large Datasets; - Scalable Machine Learning for Structured Data; - Scalable Kernel Methods for Large Datasets; - Recommender Systems for Large Datasets; - Big Data for Smart Cities and Transportation; - Big Social Data Analysis; - Big Data for Cybersecurity; - Big Data in Bioinformatics and Healthcare; - Big Data in the Internet of Things. SUBMISSION: Prospective authors must submit their paper through the IJCNN portal following the instructions provided inhttp://www.ijcnn.org/paper-submission. Each paper will undergo a peer reviewing process for its acceptance. IMPORTANT DATES: Paper submission deadline : 15 November 2016 Notification of acceptance : 20 January 2017 Camera-ready submission: 20 February 2017 The IJCNN 2017 conference : 14-19 May 2017 SPECIAL SESSION ORGANISERS Luca Oneto University of Genoa (Italy) Nicol? Navarin University of Padua (Italy) Michele Donini Istituto Italiano di Tecnologia (Italy) Fabio Aiolli University of Padua (Italy) Davide Anguita University of Genoa (Italy) ------------------------------------------------------------ ----------------------- Luca Oneto, PhD University of Genoa web: www.lucaoneto.com DIBRIS Department e-mail: Luca.Oneto at unige.it SmartLab Laboratory e-mail: Luca.Oneto at gmail.com Via Opera Pia 11a Fax: +39-010-3532897 16145 Genoa ITALY Phone: +39-010-3532192 www.smartlab.ws ------------------------------------------------------------ ----------------------- -------------- next part -------------- An HTML attachment was scrubbed... URL: From emj at uci.edu Sat Oct 29 19:25:14 2016 From: emj at uci.edu (Eric Mjolsness) Date: Sat, 29 Oct 2016 16:25:14 -0700 Subject: Connectionists: Faculty Positions at UC Irvine: AI, vision, machine learning, NLP Message-ID: MidCareer Faculty Positions at UC Irvine Application deadline: Dec 9th 2016 (Applications received by November 9, 2016 will receive fullest consideration.) Apply online at: https://recruit.ap.uci.edu/apply/JPF03719 The University of California, Irvine (UCI) is engaged in a multi-year campuswide strategic expansion and seeks to hire midcareer faculty (advanced assistant, tenured associate, to early full professors) in the area of information and computer sciences who have distinguished publication records and upward trajectories in their research profiles. Qualified applicants with interests in artificial intelligence, computer vision, machine learning, natural language processing, bioinformatics and related topics are encouraged to apply for these positions. UCI has a very active group of faculty in these areas including Anima Anandkumar, Pierre Baldi, Rina Dechter, Charless Fowlkes, Alex Ihler, Rick Lathrop, Eric Mjolsness, Sameer Singh, Padhraic Smyth, Erik Sudderth, and Xiaohui Xie - primarily in the computer science department, with strong interdisciplinary connections to departments such as cognitive science, informatics, and statistics. Recently celebrating its 50th anniversary, UCI is part of the premier public university system in the world. It was recently named by U.S. News & World Report as a top ten public university and by the New York Times as No. 1 among U.S. universities that do the most for low-income students. UCI is located in one of the world?s safest and most economically vibrant communities and is Orange County?s second-largest employer, contributing $4.8 billion annually to the local economy. The University of California, Irvine is an Equal Opportunity/Affirmative Action Employer advancing inclusive excellence. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories covered by the UC nondiscrimination policy. Eric -- Eric Mjolsness Professor, Departments of Computer Science and Mathematics University of California, Irvine emj at uci.edu http://emj.ics.uci.edu -------------- next part -------------- An HTML attachment was scrubbed... URL: From terry at salk.edu Sat Oct 29 22:24:51 2016 From: terry at salk.edu (Terry Sejnowski) Date: Sat, 29 Oct 2016 19:24:51 -0700 Subject: Connectionists: Computational Neuroscience Graduate Program at UCSD In-Reply-To: Message-ID: UCSD GRADUATE PROGRAM IN COMPUTATIONAL NEUROSCIENCE https://healthsciences.ucsd.edu/education/neurograd/computational/Pages/default.aspx Application deadline: Thursday, December 1, 2016: http://neurograd.ucsd.edu/2page.php?id=gradadm ***** The goal of the Computational Neuroscience Specialization in the Neurosciences Graduate Program at UCSD is to train researchers who are equally at home measuring large-scale brain activity, analyzing the data with advanced computational techniques, and developing new theories for brain function and behavior. Candidates from a wide range of backgrounds are invited to apply, including Biology, Psychology, Computer Science, Engineering, Physics and Mathematics. The three major themes in the training program are: 1. Neurobiology of Neural Systems: Anatomy, physiology and behavior of systems of neurons. Using modern neuroanatomical, behavioral, neuropharmacological and electrophysiological techniques. Lectures, wet laboratories and computer simulations, as well as research rotations. Major new imaging and recording techniques also will be taught, including optogenetics, two-photon laser scanning microscopy, diffusion tensor imaging and and functional magnetic resonance imaging (fMRI). 2. Algorithms and Realizations for the Analysis of Neuronal Data: New algorithms and techniques for analyzing data obtained from physiological recording, with an emphasis on recordings from large populations of neurons with imaging and multielectrode recording techniques. New methods for the study of co-ordinated activity, such as differential covariance and delay-differential analysis. 3. Dynamics and Control of Neurons and Neural Circuits: Theoretical aspects of single cell function and emergent properties as many neurons interact among themselves and react to sensory inputs. A synthesis of approaches from mathematics and physical sciences as well as biology are used to explore the collective properties and nonlinear dynamics of neuronal systems, as well as issues in sensory coding and motor control. ***** Participating Faculty include: * Henry Abarbanel (Physics): Nonlinear and oscillatory dynamics; modeling central pattern generators in the lobster stomatogastric ganglion. * Thomas Albright (Salk Institute): Motion processing in primate visual cortex; linking single neurons to perception; fMRI in awake, behaving monkeys. * Kenta Asahina (Salk Institute): Neural circuits for aggression and escape behavior in flies * Eimen Azim (Salk Institute): Neural circuits underlying motor planning, execution and learning. * Sharona Ben-Haim (Neurosurgery): Mechanisms for seizures propagation in humans and monkeys. * Ed Callaway (Salk Institute): Neural circuits, visual perception, visual cortex, and genetic tools for tracing neural pathways. * Gert Cauwenberghs (Bioengineering): Neuromorphic Engineering; analog VLSI chips; wireless recording and nanoscale instrumentation for neural systems; large-scale cortical modeling. * Sreekanth Chalasani (Salk Institute): C. elegans: genes, networks and behavior Optical recording of olfactory processing. * Andrea Chiba (Cognitive Science): Spatial attention, associative learning, cholinergic neuromodulation of behavior, amygdala recordings * Todd Coleman (Bioengineering): Brain-Machine Interfaces (BMI) * Garrison Cottrell (Computer Science and Engineering): Dynamical neural network models and learning algorithms * Virginia De Sa (Cognitive Science): Computational basis of perception and learning; multi-sensory integration and contextual influences * Mark Ellisman (Neurosciences, School of Medicine): High resolution electron and light microscopy; anatomical reconstructions. * Fred Gage (Salk Institute): Neurogenesis and models of the hippocampus; neuronal diversity, neural stem cells. * Timothy Gentner (Psychology): Birdsong learning. Neuroethology of vocal communication and audition * Ralph Greenspan (Neurobiology): Molecular and neurobiological studies of innate and learned behaviors in the fruit fly * Xin Jin (Salk Institute): How the brains learn and generate actions. * Harvey Karten (Neurosciences, School of Medicine): Anatomical, physiological and computational studies of the retina and optic tectum of birds and squirrels * David Kleinfeld (Physics): Active sensation in rats; properties of neuronal assemblies; optical imaging of large-scale activity. * Scott Makeig (Institute for Neural Computation): Analysis of cognitive event-related brain dynamics and fMRI using time-frequency and Independent Component Analysis * Mikhael Rabinovich (Institute for Nonlinear Science): Dynamical systems analysis of the stomatogastric ganglion of the lobster and the antenna lobe of insects * Pamela Reinagel (Biology): Sensory and neural coding; natural scene statistics; recordings from the visual system of cats and rodents. * John Reynolds (Salk): Visual attention, cortex, psychophysics, neurophysiology, neural modeling * Massimo Scanziani (Biology): Neural circuits in the somotosensory cortex; physiology of synaptic transmission; inhibitory mechanisms. * Terrence Sejnowski (Salk Institute/Neurobiology): Computational models and physiological studies of synaptic, neuronal and network function. * Tanya Sharpee (Salk): Statistical physics and information theory approaches to sensory processing in natural auditory and visual environments. * Gabe Silva (Bioengineering): Cellular neural engineering * Nicholas Spitzer (Neurobiology): Regulation of ionic channels and neurotransmitters in developing neurons and neural function. * Charles Stevens (Salk Institute): Synaptic physiology; theoretical neuroscience; neuroanatomical scaling. * Massimo Vergassola (Physics): Modeling, dynamics, orientation, sensory systems, biological physics * Jing Wang (Biology): Representation of olfactory information in the nervous system of Drosophila * Ruth Williams (Mathematics): Probabilistic analysis of stochastic systems and continuous learning algorithms * Angela Yu (Cognitive Science): Sensory processing, attentional selection, perceptual decision-making, sensorimotor integration, learning, and adaptation. ***** On-line applications: http://neurograd.ucsd.edu/2page.php?id=gradadm The deadline for completed application materials, including letters of recommendation, is Thursday, December 1, 2016. ***** From emj at uci.edu Sat Oct 29 19:25:22 2016 From: emj at uci.edu (Eric Mjolsness) Date: Sat, 29 Oct 2016 16:25:22 -0700 Subject: Connectionists: Faculty Positions at UC Irvine: Bioinformatics & Computational Biology Message-ID: <7cee32e5-8a63-297a-d81f-c17f6f80f73c@uci.edu> MidCareer Faculty Positions at UC Irvine Application deadline: Dec 9th 2016 (Applications received by November 9, 2016 will receive fullest consideration.) Apply online at: https://recruit.ap.uci.edu/apply/JPF03719. The University of California, Irvine (UCI) is engaged in a multi-year campus-wide strategic expansion and seeks to hire mid-career faculty (advanced assistant, tenured associate, to early full professors) with distinguished publication records and upward trajectories in their research profiles. Qualified applicants with interests in bioinformatics, biomedical informatics, computational biology and related topics in the intersection of computation and biology are encouraged to apply for these positions. UCI has a very active group of faculty in these areas including Pierre Baldi, Charless Fowlkes, Rick Lathrop, Eric Mjolsness, Babak Shababa, and Xiaohui Xie - mainly in the Computer Science department, with strong interdisciplinary connections to departments such as Statistics, Biomedical Engineering, the School of Biological Sciences, and the School of Medicine. Recently celebrating its 50th anniversary, UCI is part of the premier public university system in the world. It was recently named by U.S. News & World Report as a top ten public university and by the New York Times as No. 1 among U.S. universities that do the most for low-income students. UCI is Orange County?s second-largest employer, contributing $4.8 billion annually to the local economy. Irvine one of the world?s safest and most economically vibrant communities. It is highly ranked as a place to live, has extensive bike lanes and open spaces, and is just a few miles away from Pacific Ocean beaches. The University of California, Irvine is an Equal Opportunity/Affirmative Action Employer advancing inclusive excellence. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories covered by the UC nondiscrimination policy. Eric -- Eric Mjolsness Professor, Departments of Computer Science and Mathematics University of California, Irvine emj at uci.edu http://emj.ics.uci.edu -------------- next part -------------- An HTML attachment was scrubbed... URL: From nteneva at uchicago.edu Sat Oct 29 19:36:39 2016 From: nteneva at uchicago.edu (Nedelina Teneva) Date: Sat, 29 Oct 2016 18:36:39 -0500 Subject: Connectionists: CfP: 1st Workshop on Data Management for End-to-End Machine Learning Message-ID: DEEM'17 The 1st Workshop on Data Management for End-to-End Machine Learning, May 14, 2017. http://deem-workshop.org https://twitter.com/deem_workshop Held in conjunction with ACM SIGMOD 2017 Raleigh, NC, USA, May 14-19, 2017 http://sigmod2017.org/ ---------- WORKSHOP ---------- Applying Machine Learning (ML) in real-world scenarios is a challenging task. In recent years, the main focus of the database community has been on creating systems and abstractions for the efficient training of ML models on large datasets. However, model training is only one of many steps in an end-to-end ML application, and a number of orthogonal data management problems arise from the large-scale use of ML, which require the attention of the data management community. Therefore, DEEM aims to bring together researchers and practitioners at the intersection of applied machine learning, data management, and systems research, with the goal to discuss the arising data management issues in ML application scenarios. The workshop solicits *regular research papers describing preliminary and ongoing research results*. In addition, the workshop encourages the submission of *industrial experience reports of end-to-end ML deployments*. Submissions can either be *short papers (4 pages)* or *long papers (up to 10 pages)* following the ACM proceedings format, as described in https://www.acm.org/publicatio ns/proceedings-template. Examples of data management problems in ML are as follows: - Simultaneously executing relational and linear algebraic operations in data preprocessing and feature extraction - Choosing among popular classes of ML models (linear models, decision trees, and deep neural networks) - Executing costly offline evaluation processes for choosing features and hyperparameters - Deployment of models and integration into existing business workflows - Fast and Efficient Online Predictions from trained ML Models Areas of particular interest for the workshop include (but are not limited to): - Data Management in Machine Learning Applications - Definition, Execution, and Optimization of Complex ML Pipelines - Systems for Managing the Lifecycle of Machine Learning Models - Systems for Efficient Hyperparameter Search and Feature Selection - Machine Learning Services in the Cloud - Modeling, Storage, and Lineage of ML experimentation data - Integration of Machine Learning and Dataflow Systems - Integration of Machine Learning and ETL Processing - Benchmarking of Machine Learning Applications - Definition and Execution of Complex Ensemble Predictors - Architectures for Streaming Machine Learning ---------------- IMPORTANT DATES ---------------- Papers submission deadline: February 1, 2017 Authors notification: March 1, 2017 Deadline for camera-ready copy: March 20, 2017 Workshop: Sunday May 14th, 2017 ---------------------- SUBMISSION GUIDELINES ---------------------- The workshop will have two tracks for regular research papers (including research in progress) and industrial papers (e.g., industrial experience reports of end-to-end ML deployments). Submissions can either be *short papers (4 pages)* or *long papers (up to 10 pages)* following the ACM proceedings format, as described in https://www.acm.org/publicatio ns/proceedings-template. ---------------- PUBLICATION ---------------- The workshop proceedings will be published in ACM DL and the organizers will prepare a SIGMOD Record report. --------------------------- ORGANIZERS --------------------------- - Sebastian Schelter (Amazon) - Reza Zadeh (Stanford & Matroid) - Markus Weimer (Microsoft) - Rajeev Rastogi (Amazon) - Volker Markl (TU Berlin) --------------------------- PROGRAM COMMITTEE --------------------------- - Sunita Sarawagi (IIT Bombay) - Sudip Roy (Google) - Rainer Gemulla (University of Mannheim) - Matthias Boehm (IBM Research) - Matthias Seeger (Amazon) - Evan Sparks (UC Berkeley) - Chris R?? (Stanford) - Ted Dunning (MapR Technologies) - Dionysios Logothetis (Facebook) - Nedelina Teneva (University of Chicago) - Vasia Kalavri (KTH Stockholm) - Venu Satuluri (Twitter) - Shannon Quinn (University of Georgia) - Dmitriy Lyubimov (Apache Mahout) - Tilmann Rabl (TU Berlin) - Max Heimel (Snowflake) - Felix Biessmann (Amazon) - Arun Kumar (UC San Diego) -- Nedelina Teneva -------------- next part -------------- An HTML attachment was scrubbed... URL: From horacio at njit.edu Sun Oct 30 09:47:16 2016 From: horacio at njit.edu (Horacio G. Rotstein) Date: Sun, 30 Oct 2016 09:47:16 -0400 Subject: Connectionists: Mathematical Neuroscience Subgroup - Society for Mathematical Biology (SMB) Message-ID: Dear colleagues, The Society for Mathematical Biology (SMB) has made an open call to establish thematic subgroups. We'd like to invite you to join us in the creation of the SMB Subgroup on Mathematical Neuroscience by signing the petition below. If you are an SMB member please indicate so in the form. The primary goal of the MathNeuro Subgroup is to contribute to the advancement of interdisciplinary research and dissemination of knowledge in mathematical, computational and theoretical neuroscience. Specific activities include the organization of workshops and/or minisymposia on mathematical neuroscience and related topics and the support of existing initiatives that further the subgroup's interests. Additional goals include promoting the interaction between theoretical and experimental neuroscientists, education and outreach. https://docs.google.com/forms/d/e/1FAIpQLSfhvsOb7UUzdsUJFz8R osd1Gu0rOQCDWWexvyTJLLowLeezTg/viewform First tentative chair and alternate chair: Horacio G. Rotstein and Stephen Coombes? -- Horacio, NY/NJ area. "Az di bobe volt gehat beytsim volt zi geven mayn zeide" (Yiddish expression) Horacio G. Rotstein Professor Department of Mathematical Sciences New Jersey Institute of Technology Newark, NJ, 07102, USA. Graduate Faculty Behavioral Neuroscience Program Rutgers University (NWK) and Federated Department of Biological Sciences Rutgers / NJIT tel: (1-973) 596-5306 e-mail: horacio at njit.edu horacior at andromeda.rutgers.edu http://web.njit.edu/~horacio -------------- next part -------------- An HTML attachment was scrubbed... URL: From oleary at usc.edu Sun Oct 30 15:22:58 2016 From: oleary at usc.edu (Daniel Edmund O'Leary) Date: Sun, 30 Oct 2016 19:22:58 +0000 Subject: Connectionists: Pre - ICIS Workshop - Call for Papers Message-ID: Pre - ICIS Workshop - Call for Papers - Saturday December 10 (10:00 to 4:30) http://icis2016.aisnet.org/artificial-intelligence-applications/ Artificial Intelligence and Applications - ICIS 2016 icis2016.aisnet.org This workshop will address issues related to artificial intelligence and its applications, particularly with applications to business settings and problems. This workshop will address issues related to artificial intelligence and its applications, particularly with applications to business settings and problems. All aspects of artificial intelligence and artificial narrow intelligence are of interest, including emerging concerns with * cognitive computing, * natural language, * Internet of Things, * ontologies for AI, * machine learning, * knowledge from data, text, audio and video * question answering, * smart advisor applications, * autonomous applications, * autonomic systems, * neural networks, * knowledge representation and management, * multiple agent models, * real world applications, * impact of AI systems in organizations, etc. Researchers should submit their research for consideration for the workshop to Daniel E. O'Leary, oleary at usc.edu. In order to be considered for presentation, papers should be submitted by November 20. Presenters and attendees will be required to register for the workshop. "Artificial and Cognitive Intelligence for Autonomic Applications" -------------- next part -------------- An HTML attachment was scrubbed... URL: From cruz at informatik.uni-hamburg.de Mon Oct 31 11:30:50 2016 From: cruz at informatik.uni-hamburg.de (Francisco Cruz) Date: Mon, 31 Oct 2016 16:30:50 +0100 Subject: Connectionists: [journals] Call for papers: Special Issue on Bio-inspired Social Robot Learning in Home Scenarios Message-ID: <72d2c2e9-15a5-d7f4-1575-b62dc59d54d5@informatik.uni-hamburg.de> IEEE Transactions on Cognitive and Developmental Systems Special Issue on Bio-inspired Social Robot Learning in Home Scenarios http://www.informatik.uni-hamburg.de/wtm/SocialRobotsWorkshop2016/CFP_TCDS_SI_SocialRobots.pdf *Call for papers* There has been considerable progress in robotics in the last years allowing robots to successfully contribute to our society. We can find them from industrial environments, where they are nowadays established, to domestic places, where their presence is steadily rising. The proposed special issue intends to explore the following question: ?How well prepared are learning robots to be social actors in daily-life home environments in the near future?. The special issue is therefore not only an opportunity to address this focuses on the latest scientific contributions on bio-inspired learning and social robotics, but also links them with a clear focus to push the presence of robots in people?s daily-life environment. Thus, one main goal of the special issue is offering a common foundation for roboticists from different fields of expertise to contribute beyond the current state-of-the-art of learning methods in robotics especially applied to home scenarios and recent developments in assistive robots. The subjects of the special issue include, but are not limited to: - Interactive reinforcement learning. - Policy and reward shaping. - Neural learning of object affordances and contextual affordances. - Predictive learning from sensorimotor information. - Learning understanding of environment ambiguity. - Learning with hierarchical and deep neural architectures. - Bootstrapping complex action learning in robots. - Learning supported by external trainers, by demonstration and imitation. - Parental scaffolding as a bootstrapping method for learning. *Submissions* The special issue is open for all submissions which will be independently peer-reviewed in accordance with IEEE policy. Manuscripts should be prepared according to the ?Information for Authors? of the journal, found at http://cis.ieee.org/publications.html, and submitted through the IEEE TCDS Manuscript center under the category: "SI: Social Robots": https://mc.manuscriptcentral.com/tcds-ieee. Papers submitted must not have been published previously, though they may represent significant extensions of prior work. *Important dates* 31 January 2017 - Deadline for manuscript submission. 15 April 2017 - Notification of authors. 15 May 2017 - Deadline for revised manuscripts. 15 June 2017 - Final decisions. For further information, please contact one of the following guest editors in this order: Francisco Cruz Knowledge Technology Institute, University of Hamburg, Germany cruz at informatik.uni-hamburg.de Jimmy Baraglia Emergent Robotics Laboratory, Osaka University, Japan jimmy.baraglia at ams.eng.osaka-u.ac.jp Yukie Nagai Emergent Robotics Laboratory, Osaka University, Japan yukie at ams.eng.osaka-u.ac.jp Stefan Wermter Knowledge Technology Institute, University of Hamburg, Germany wermter at informatik.uni-hamburg.de Francisco Cruz Research Associate Knowledge Technology Group Department of Informatics University of Hamburg Vogt-K?lln-Str. 30 22527 Hamburg, Germany Office F-217 Phone: +49 40 42883 2524 http://www.knowledge-technology.info From geri at robot-learning.de Mon Oct 31 09:13:09 2016 From: geri at robot-learning.de (Gerhard Neumann) Date: Mon, 31 Oct 2016 13:13:09 +0000 Subject: Connectionists: [jobs] Closing soon: LECTURER/SENIOR LECTURER in Machine Learning and Robotics, University of Lincoln, UK Message-ID: *LECTURER/SENIOR LECTURER in Machine Learning and Robotics (Learning for Autonomous Systems)* *Location: University of Lincoln, UK* College of Science - School of Computer Science *Position: *Lecturer or Senior Lecturer *Salary: * From ?32,004 per annum *Please note that these are fully tenured (permanent) faculty positions. The post of Lecturer in UK is equivalent to Assistant Professor in US. We are hoping to recruit up to TWO persons at either lecturer or senior lecturer level.* *Closing Date: * Thursday 03 November 2016 *Interview Date: * Friday 18 November 2016 *Reference: *COS277 We seek to appoint two permanent Lecturers or Senior Lecturers with established research expertise in Learning for Autonomous Systems or a related field. You should hold a PhD or be near to completion, and should be able to demonstrate a good track record in these research fields. Once in post, you are expected to develop your own research portfolio, acquire external funding, publish in the highest quality journals and conferences, contribute to real-world applications with positive impacts on the wider society and economy, and to conduct, direct and supervise research in line with the targets set by the School. You will be a key part of the Lincoln Centre for Autonomous Systems (L-CAS), which specialises in the integration of perception, learning, decision-making, control and interaction capabilities in autonomous systems and the application of this research in fields such as personal robotics, agri-food, healthcare, security, and intelligent transportation. The L-CAS is one of the fastest growing robotics groups in the UK. We provide a highly-dynamic inter-disciplinary research environment with a broad range of collaboration opportunities and a large variety of robots to work with. We are looking to recruit new people ? from early careers researchers to senior professionals - who share our ambition to become one of the world?s leading robotics labs. Your research interests will form an integral part of a new research focus on Learning for Autonomous Systems, working together with the newly appointed Professor of Computational Learning for Autonomous Systems. As a successful candidate, your research areas should be focused on applying machine learning techniques, such as (but not limited to)reinforcement learning, learning from demonstration, deep learning or Bayesian methods, to robotics and autonomous systems with applications such as (but not limited to) dexterous manipulation, humanoid robots, human-robot collaboration, swarm robotics or autonomous driving. You will be expected to take an active part in the activities of the School of Computer Science, to contribute to its teaching activity at undergraduate and postgraduate levels, and to demonstrate a commitment to maintaining the University?s high standards in teaching and learning. The School of Computer Science at the University of Lincoln has scored highly in the recent independent performance measures of UK university computing departments; in the top 20% for student satisfaction (NSS 2015), the top 50 for research excellence in its publications (REF 2014) and approximately 10% above the sector average for graduate employability (DLHE 2014). In the most recently published subject league tables (Sunday Times 2015; Complete University Guide 2016) the School is the highest ranked ?new? (post 1992) computer science department in the country. The University of Lincoln is a forward-thinking, ambitious institution and you will be working in the heart of a thriving, beautiful, safe and friendly city. The School provides a stimulating environment for academic research, and is located on the picturesque waterfront campus in the historic and vibrant city of Lincoln. The University has just announced a ?130M investment programme, a significant part of which is being invested in new, purpose-built facilities for the School of Computer Science. If you would like to know more about this opportunity, please contact either Prof Gerhard Neumann (Professor of Computational Learning for Autonomous Systems, geri at robot-learning.de), Prof Tom Duckett (Director of L-CAS, tduckett at lincoln.ac.uk) or Dr Kevin Jacques (Acting Head of School, kjacques at lincoln.ac.uk). As a member of the Athena SWAN Charter we are committed to advancing gender equality in STEM, therefore female applicants are strongly encouraged to apply. To apply online, please visit our website at https://jobs.lincoln.ac.uk/ vacancy.aspx?ref=COS277 If you have any queries please email jobs at lincoln.ac.uk or telephone 01522 886 775. Please quote the job reference number and title in all correspondence. -- --------------------------------------------- Gerhard Neumann Chair of Computational Learning for Autonomous Systems (starting Nov. 2016) University of Lincoln -------------- next part -------------- An HTML attachment was scrubbed... URL: From erdi.peter at wigner.mta.hu Mon Oct 31 19:23:52 2016 From: erdi.peter at wigner.mta.hu (=?ISO-8859-2?Q?=C9rdi_P=E9ter?=) Date: Tue, 1 Nov 2016 00:23:52 +0100 (CET) Subject: Connectionists: study abroad programs in Budapest Message-ID: BSCS-US announces two study abroad programs in Budapest for 2017. 1. Our historical program: BSCS - BUDAPEST SEMESTER IN COGNITIVE SCIENCE PHILOSOPHY TO NEUROSCIENCE will be held in the Fall of 2017, see http://www.bscs-us.org/ [www.bscs-us.org] . 2. We also have a program now in its third year: ***************************************** Systems Neuroscience: a study abroad summer program Program start/end dates: June 12 - Aug 4 2017 The BSCS Systems Neuroscience Program takes place at and academically supervised by the Department of Anatomy, Histology and Embryology, Semmelweis University Medical School, Budapest **************************************** For details, see: http://sysneuro-semester.org/ [sysneuro-semester.org] Inquiry: Program directors: Peter Erdi perdi at kzoo.edu Laszlo Negyessy Office: bscs at bscs-us.org From ajyu at ucsd.edu Mon Oct 31 14:06:07 2016 From: ajyu at ucsd.edu (Angela Yu) Date: Mon, 31 Oct 2016 11:06:07 -0700 Subject: Connectionists: PhD position in cognitive modeling Message-ID: <29C40CD9-356C-482D-90A7-CE9AB84DE02A@ucsd.edu> Applications are invited from highly motivated students to conduct PhD research in the Computational & Cognitive Neuroscience Lab, led by Angela Yu, at University of California, San Diego. Candidates must have a strong background in mathematics and/or machine learning, and be committed to applying rigorous mathematical tools to modeling cognitive and neural processes. Experience or interest in carrying out human behavioral experiments (either in person or on Amazon M-Turk) and/or collaborating with other human/animal neuroscience laboratories is also desirable. Current research in the lab ranges across cognitive control, decision-making, visual search, active learning, social cognition, and machine learning. Dr. Yu's group is situated within the Cognitive Science department of UCSD, but Dr. Yu advises students not only from the Cognitive Science, but also from Computer Science & Engineering, Electrical & Computer Engineering, and Neurosciences PhD programs. Interested students should apply directly to one or more of the PhD programs, and indicate Dr. Yu as a potential research advisor in the research statement. They are also encouraged to email Dr. Yu directly to explain why they think their interests/background are a good fit for working with Dr. Yu. ------------------------------------- Angela J. Yu Associate Professor UCSD Cognitive Science www.cogsci.ucsd.edu/~ajyu ------------------------------------- -------------- next part -------------- An HTML attachment was scrubbed... URL: