From jorgecbalmeida at gmail.com Mon Oct 1 06:41:18 2018 From: jorgecbalmeida at gmail.com (Jorge Almeida) Date: Mon, 1 Oct 2018 11:41:18 +0100 Subject: Connectionists: DEADLINE APPROACHING - OCTOBER 5. One fMRI Post-Doc (very competitive salary) 5 year position available under an ERC Starting Grant on the organization of object knowledge Message-ID: The Proaction Laboratory (Perception and Recognition of Objects and Actions; http://gaius.fpce.uc.pt/pessoais/jorgealmeida/proaction_home.html; Jorge Almeida?s Lab) at the University of Coimbra (www.uc.pt), Portugal is looking for a motivated and bright Post-doctoral researcher to work on an ERC Starting Grant project (ContentMAP) on the neural organization of object knowledge. In this project we will explore how complex information is topographically organized in the brain using fMRI and state of the art analytical techniques, as well as computational approaches, and neuromodulation. Excellent understanding of and experience with fMRI and data analysis is required. Strong programming skills (matlab, python, etc.) are also a requirement. Experience with data analysis techniques using Representational Similarity Analysis, MVPA, and Machine Learning, as well as computational approaches to cognitive neuroscience (e.g., SOM) are a plus. Very good English (oral and written) communicative skills are necessary. The position is for a maximum of 5 years, and will start in February 2019. The position involves no formal teaching (unless the candidate wants to). It does involve, however, lab mentoring. The salary is extremely competitive ? between 2200 and 2400 euros per month (dependent on experience), tax free (annual 26400-28800 euros tax free). This value is on par with the average salaries at top American institutions, as well as London, Paris, etc. However, the cost of living in Portugal (and particularly in Coimbra) is much lower. According to Numbeo, 2400 euros would be equivalent to 4850 pounds in London/4800 euros in Paris/6615 USD in Boston/6210 USD in Los Angeles/ 8330 USD in New York). The researcher will work directly with Jorge Almeida in Coimbra, but the laboratory has extensive collaborations with researchers throughout the world. In fact, there may be the option of spending some time in another lab as part of the position. The researcher will also be encouraged to develop her/his own projects and look for additional funding so that the stay can be extended. We have access to a 3T MRI scanner with a 32-channel coil (with EEG inside the scanner), to tDCS with neuronavigation, and to a fully set psychophysics lab. We have EEG and eyetracking on site. We also have access, through other collaborations, to a 7T scanner. Finally, the University of Coimbra is a 700 year old University and has been selected as a UNESCO world Heritage site. Coimbra is one of the most lively university cities in the world, and it is a beautiful city with easy access to the beach and mountain. The deadline for the application is OCTOBER 5, but you should apply as soon as you can, as we may fill in the positions sooner than the deadline if there are candidates with a superb fit with the requirements and project. The interested candidates should email Jorge Almeida for questions and applications. Please send an email with the subject ?Post-doc position under ERC - ContentMAP? with your *curriculum vitae, list of publications, 2 reference letters, and a short description of your experience in the field and how you fulfill the requirements (fit with the position)* to: jorgealmeida at fpce.uc.pt. -------------- next part -------------- An HTML attachment was scrubbed... URL: From jorgecbalmeida at gmail.com Mon Oct 1 06:41:54 2018 From: jorgecbalmeida at gmail.com (Jorge Almeida) Date: Mon, 1 Oct 2018 11:41:54 +0100 Subject: Connectionists: Many Doctoral and Pre-Doctoral 5 year positions available under an ERC Starting Grant on the organization of object knowledge Message-ID: Apologies for cross-posting. The Proaction Laboratory (Perception and Recognition of Objects and Actions; *http://gaius.fpce.uc.pt/pessoais/jorgealmeida/proaction_home.html *; Jorge Almeida?s Lab) at the University of Coimbra (*www.uc.pt *), Portugal is looking for motivated and bright doctoral and pre-doctoral researchers to work on a prestigious ERC Starting Grant project (ContentMAP) on the neural organization of object knowledge. In this project we will explore how complex information is topographically organized in the brain using fMRI and state of the art analytical techniques, as well as computational approaches, and neuromodulation. Experience with fMRI and data analysis is required. Strong programming skills (matlab, python, etc.) are also a requirement. Experience with data analysis techniques used in vision and object recognition (e.g., Representational Similarity Analysis, MVPA, Machine Learning, population Receptive Fields/phase lag analysis), as well as computational approaches to cognitive neuroscience (e.g., SOM) is a plus. Very good English (oral and written) communicative skills are necessary. The positions are for a maximum of 5 years, and will start in February 2019. The salary is competitive especially considering the cost of living in Portugal (and particularly in Coimbra). The researchers will work directly with Jorge Almeida in Coimbra, but the laboratory has extensive collaborations with researchers throughout the world. In fact, there may be the option of spending some time in another lab as part of the position. We have access to a 3T MRI scanner with a 32-channel coil (with EEG inside the scanner), to tDCS with neuronavigation, and to a fully set psychophysics lab. We have EEG and eyetracking on site. We also have access, through other collaborations, to a 7T scanner. Finally, the University of Coimbra is a 700 year old University and has been selected as a UNESCO world Heritage site. Coimbra is one of the most lively university cities in the world, and it is a beautiful city with easy access to the beach and mountain. The deadline for the application is October 10, but you should apply as soon as you can, as we may fill in the positions sooner than the deadline if there are candidates with a superb fit with the requirements and project. The interested candidates should email Jorge Almeida for questions and applications. Please send an email with the subject ?Positions under ERC - ContentMAP? with your *curriculum vitae, list of publications, 2 reference letters, and a short description of your experience in the field and how you fulfill the requirements (fit with the position)* to: *jorgealmeida at fpce.uc.pt *. -------------- next part -------------- An HTML attachment was scrubbed... URL: From icpram at insticc.info Mon Oct 1 07:45:47 2018 From: icpram at insticc.info (icpram at insticc.info) Date: 1 Oct 2018 12:45:47 +0100 Subject: Connectionists: CFP ICPRAM 2019 - 8th Int.l Conf. on Pattern Recognition Applications and Methods (Prague/Czech Republic) Message-ID: <20181001114545.1.88DC048A6BE93EB4@insticc.info> SUBMISSION DEADLINE 8th International Conference on Pattern Recognition Applications and Methods Submission Deadline: October 22, 2018 http://www.icpram.org/ February 19 - 21, 2019 Prague, Czech Republic. ICPRAM is organized in 2 major tracks: - Theory and Methods - Applications In Cooperation with: ACM SIGCHI, ACM SIGGRAPH, EUROGRAPHICS and AFIG.
Proceedings will be submitted for indexation by: DBLP, DBLP, Thomson Reuters, EI, SCOPUS and Semantic Scholar.
With the presence of internationally distinguished keynote speakers: Linda Shapiro, University of Washington, United States Bram van Ginneken, Radboud University Medical Center, Netherlands Michal Irani, Weizmann Institute of Science, Israel Davide Maltoni, University of Bologna, Italy A short list of presented papers will be selected so that revised and extended versions of these papers will be published by Springer. All papers presented at the congress venue will also be available at the SCITEPRESS Digital Library (http://www.scitepress.org/DigitalLibrary/). Should you have any question please don't hesitate contacting me. Kind regards, ICPRAM Secretariat Address: Av. D. Manuel I, 27A, 2? esq. 2910-595 Setubal, Portugal Tel: +351 265 520 185 Fax: +351 265 520 186 Web: http://www.icpram.org/ e-mail: icpram.secretariat at insticc.org From biostec at insticc.info Mon Oct 1 07:45:38 2018 From: biostec at insticc.info (biostec at insticc.info) Date: 1 Oct 2018 12:45:38 +0100 Subject: Connectionists: CFP BIOSTEC 2019 - 12th Int.l Joint Conf. on Biomedical Engineering Systems and Technologies (Prague/Czech Republic) Message-ID: <20181001114536.1.A7ECF6CED1CE48F0@insticc.info> SUBMISSION DEADLINE 12th International Joint Conference on Biomedical Engineering Systems and Technologies Submission Deadline: October 22, 2018 http://www.biostec.org/ February 22 - 24, 2019 Prague, Czech Republic. In Cooperation with: ACM SIGCHI, ACM SIGGRAPH, EUROGRAPHICS and AFIG.
Proceedings will be submitted for indexation by: DBLP, DBLP, Thomson Reuters, EI, SCOPUS and Semantic Scholar.
With the presence of internationally distinguished keynote speakers: Hossam Haick, Israel Institute of Technology, Israel Andres Diaz Lantada, Universidad Politecnica de Madrid, Spain Henrique Martins, Universidade da Beira Interior, Portugal A short list of presented papers will be selected so that revised and extended versions of these papers will be published by Springer. All papers presented at the congress venue will also be available at the SCITEPRESS Digital Library (http://www.scitepress.org/DigitalLibrary/). Should you have any question please don't hesitate contacting me. Kind regards, BIOSTEC Secretariat Address: Av. D. Manuel I, 27A, 2? esq. 2910-595 Setubal, Portugal Tel: +351 265 520 185 Fax: +351 265 520 186 Web: http://www.biostec.org/ e-mail: biostec.secretariat at insticc.org From icaart at insticc.info Mon Oct 1 07:45:28 2018 From: icaart at insticc.info (icaart at insticc.info) Date: 1 Oct 2018 12:45:28 +0100 Subject: Connectionists: CFP ICAART 2019 - 11th Int.l Conf. on Agents and Artificial Intelligence (Prague/Czech Republic) Message-ID: <20181001114526.1.6B48A195119BBF4E@insticc.info> SUBMISSION DEADLINE 11th International Conference on Agents and Artificial Intelligence Submission Deadline: October 22, 2018 http://www.icaart.org/ February 19 - 21, 2019 Prague, Czech Republic. ICAART is organized in 2 major tracks: - Agents - Artificial Intelligence In Cooperation with: ACM SIGCHI, ACM SIGGRAPH, EUROGRAPHICS and AFIG.
Proceedings will be submitted for indexation by: DBLP, DBLP, Thomson Reuters, EI, SCOPUS and Semantic Scholar.
With the presence of internationally distinguished keynote speakers: Penousal Machado, University of Coimbra, Portugal Carla Gomes, Cornell University, United States Michal Pechoucek, Czech Technical University in Prague, Czech Republic Lambert Schomaker, University of Groningen, Netherlands A short list of presented papers will be selected so that revised and extended versions of these papers will be published by Springer. All papers presented at the congress venue will also be available at the SCITEPRESS Digital Library (http://www.scitepress.org/DigitalLibrary/). Should you have any question please don't hesitate contacting me. Kind regards, ICAART Secretariat Address: Av. D. Manuel I, 27A, 2? esq. 2910-595 Setubal, Portugal Tel: +351 265 520 185 Fax: +351 265 520 186 Web: http://www.icaart.org/ e-mail: icaart.secretariat at insticc.org From cah369 at nyu.edu Mon Oct 1 21:03:47 2018 From: cah369 at nyu.edu (Catherine Hartley) Date: Mon, 1 Oct 2018 21:03:47 -0400 Subject: Connectionists: Save the dates - Reinforcement Learning and Decision Making 2019 - July 7-10 Message-ID: <40B55013-60E9-4AEA-A446-AF0F11B51994@nyu.edu> ====================================================== The 4th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM2019) www.rldm.org July 7-10 2019 at McGill University, Montr?al, Qu?bec, Canada ====================================================== Over the last few decades, reinforcement learning and decision making have been the focus of an incredible wealth of research spanning a wide variety of fields including psychology, artificial intelligence, machine learning, operations research, control theory, animal and human neuroscience, economics and ethology. Key to many developments in the field has been interdisciplinary sharing of ideas and findings. The goal of RLDM is to provide a platform for communication among all researchers interested in "learning and decision making over time to achieve a goal". The meeting is characterized by the multidisciplinarity of the presenters and attendees, with cross-disciplinary conversations and teaching and learning being central objectives along with the dissemination of novel theoretical and experimental results. The main meeting will be single-track, consisting of a mixture of invited and contributed talks, tutorials, and poster sessions. For the first time, RLDM 2019 will conclude with a half-day of thematically-focused contributed Workshops, which will be run in parallel. TENTATIVE DATES Submissions open: December 15, 2018 Submissions close: February 15, 2019 We look forward to seeing you in Montr?al! Best, RLDM2019 ORGANIZERS PROGRAM CHAIRS Catherine Hartley Michael Littman GENERAL CHAIR Satinder Singh LOCAL CHAIRS Joelle Pineau Doina Precup Ross Otto EXECUTIVE COMMITTEE: Yael Niv Peter Dayan Satinder Singh Rich Sutton Emma Brunskill Nathaniel Daw From royf at berkeley.edu Tue Oct 2 03:28:05 2018 From: royf at berkeley.edu (Roy Fox) Date: Tue, 2 Oct 2018 00:28:05 -0700 Subject: Connectionists: **Deadline Extended** -- NIPS 2018 Workshop -- Infer2Control Message-ID: ** Submission deadline is extended to Friday, October 12, 2018 (Anywhere on Earth) ** **************************************************************************************************** > Infer to Control: Probabilistic Reinforcement Learning and Structured Control > NIPS 2018 Workshop > Saturday, December 8 > Montr?al, Canada > Website: https://sites.google.com/view/infer2control-nips2018 > Please address questions to: infer2control.nips2018 at gmail.com **************************************************************************************************** Reinforcement learning and imitation learning are effective paradigms for learning controllers of dynamical systems from experience. These fields have been empowered by recent success in deep learning of differentiable parametric models, allowing end-to-end training of highly nonlinear controllers that encompass perception, memory, prediction, and decision making. The aptitude of these models to represent latent dynamics, high-level goals, and long-term outcomes is unfortunately curbed by the poor sample complexity of many current algorithms for learning these models from experience. Probabilistic reinforcement learning and inference of control structure are emerging as promising approaches for avoiding prohibitive amounts of controller?system interactions. These methods leverage informative priors on useful behavior, as well as controller structure, such as hierarchy and modularity, as useful inductive biases that reduce the effective size of policy search space and shape the optimization landscape. Intrinsic and self-supervised signals can further guide the training process of distinct internal components?such as perceptual embeddings, predictive models, exploration policies, and inter-agent communication?to break down the hard holistic problem of control into more efficiently learnable parts. Effective inference methods are crucial for probabilistic approaches to reinforcement learning and structured control. Approximate control and model-free reinforcement learning exploit latent system structure and priors on policy structure, that are not directly evident in the controller?system interactions, and must be inferred by the learning algorithm. The growing interest of the reinforcement learning and optimal control community in the application of inference methods is synchronized well with the development by the probabilistic learning community of powerful inference techniques, such as probabilistic programming, variational inference, Gaussian processes, and nonparametric regression. This workshop is a venue for the inference and reinforcement learning communities to come together in discussing recent advances, developing insights, and future potential in inference methods and their application to probabilistic reinforcement learning and structured control. The goal of this workshop is to catalyze tighter collaboration within and between the communities, that will be leveraged in upcoming years to rise to the challenges of real-world control problems. #### IMPORTANT DATES: #### - Submission deadline (extended): Friday, October 12, 2018 (Anywhere on Earth) - Author notification: Monday, October 22, 2018 - Final version deadline: Friday, November 30, 2018 - Workshop: Saturday, December 8, 2018 #### SUBMISSION DETAILS: #### - Research papers are solicited on inference for reinforcement learning and control, its theory and applications, and related fields. - Contributed papers may include novel research, preliminary results, or surveys of recent results. - Papers are limited to 4 pages, excluding references and appendices of any length, in the NIPS style: https://nips.cc/Conferences/2018/PaperInformation/StyleFiles. - Submissions must be anonymized for double-blind review. - All accepted papers will be presented as spotlights and posters, and made publicly available as a non-archival report, allowing future submissions to archival conferences or journals. - Authors of top accepted papers will be invited to give short contributed talks. - Submission link: https://cmt3.research.microsoft.com/INFER2CONTROL2018 - Please check the workshop website for the latest updates: https://sites.google.com/view/infer2control-nips2018 #### ORGANIZERS: #### - Leslie Kaelbling - Martin Riedmiller - Marc Toussaint - Igor Mordatch - Roy Fox - Tuomas Haarnoja -------------- next part -------------- An HTML attachment was scrubbed... URL: From s.purcell at exeter.ac.uk Tue Oct 2 05:00:51 2018 From: s.purcell at exeter.ac.uk (Purcell, Sarah) Date: Tue, 2 Oct 2018 09:00:51 +0000 Subject: Connectionists: PhD opportunities at the Universities of Bath and Exeter In-Reply-To: References: Message-ID: Dear all, The Universities of Bath and Exeter are seeking applications for PhD candidates for two biology/medicine modelling projects. Both projects will use a combination of mathematical modelling and data analysis (possibly with some data collection for interested applicants). The studentship will cover 3.5 years, with a start date of September 2019. However, this is open for EU students only. The first project will involve multi-scale modelling of skeletal muscle bioenergetics, with applications to deficits in cystic fibrosis. The student would primarily be based at the University of Exeter (with Dr. Kyle Wedgwood & Prof. Craig Williams) with secondments at the University of Bath (with Dr. James Betts). For more information, see here: http://www.exeter.ac.uk/studying/funding/award/?id=3236 The second project will investigate ion channel mutations associated with dementia. The student would primarily be based at the University of Bath (with Prof. Alain Nogaret) with secondments at the University of Exeter (with Prof. Andy Randall, Dr. Kyle Wedgwood). For full details of the project, please visit http://www.gw4biomed.ac.uk/available-projects-2/neuroscience-and-mental-health-projects/ and select the project entitled "In-depth understanding of dementia-associated changes to neuronal signalling" Best wishes, Dr. Kyle Wedgwood MRC Research Fellow Centre for Biomedical Modelling & Analysis College of Engineering, Mathematics and Physical Sciences University of Exeter Living Systems Institute Stocker Road EX4 4QD ________________________________________________________________ -------------- next part -------------- An HTML attachment was scrubbed... URL: From vcutsuridis at gmail.com Tue Oct 2 14:28:15 2018 From: vcutsuridis at gmail.com (Vassilis Cutsuridis) Date: Tue, 2 Oct 2018 20:28:15 +0200 Subject: Connectionists: Frontiers Research Topic on Neuroscience of response inhibition In-Reply-To: References: Message-ID: Announcement of the Frontiers Research Topic --------------------------------------------------------------------------------------------------------------------------------------------------------- Neuroscience of response inhibition: bridging scales with experiments and computational modelling ---------------------------------------------------------------------------------------------------------------------------------------------------------- Response inhibition is the ability to override a planned or an already initiated response. It is the hallmark of executive control, because it allows people to flexibly adjust their behaviour according to their goals. In everyday life, there are many examples of response inhibition, such as stopping yourself when you are about to cross a street where a speeding car is approaching. Response inhibition deficits favour impulsive behaviours which may be detrimental to an individual?s life and it has been linked to disorders such as attention-deficit/hyperactivity disorder, obsessive-compulsive disorder, schizophrenia, and substance abuse disorders. In this Research Topic, we welcome papers critically evaluating the existing methods of response inhibition, introducing new experimental and theoretical approaches that probe particular parts of brain circuitry and unravel neuronal mechanisms as candidates of impulse control. We welcome scientists from different fields: from neuroscience of microcircuits to systems neuroscience of large-scale networks and behavioural neuroscience. The work can be experimental or computational. Commentaries and reviews on innovative key issues of response inhibition are also welcome. We invite you to submit a manuscript until November 30, 2018. Contributions will be published as soon as they are accepted and synchronously gathered in the Research Topic volume. For more information, do not hesitate to contact us (email of Vassilis Cutsuridis: vcutsuridis at gmail.com ). The organisers Vassilis Cutsuridis (University of Lincoln) Ganesan Venkatasubramanian (National Institute of Mental Health and Neurosciences, Bangalore, India) -------------- next part -------------- An HTML attachment was scrubbed... URL: From hbilen at ed.ac.uk Tue Oct 2 10:12:50 2018 From: hbilen at ed.ac.uk (Hakan Bilen) Date: Tue, 2 Oct 2018 15:12:50 +0100 Subject: Connectionists: Funded PhD position at ETS Montreal in machine learning Message-ID: *Efficient Deep Learning for Training and Inference* Applications are invited for a funded PhD position in computer vision and machine learning at ETS Montreal, Canada. The candidate will work under the supervision of Prof. Marco Pedersoli at ETS Montreal and Prof. Hakan Bilen at University of Edinburgh. The position is available immediately after the candidate passes ETS application requirements. Financial support is available for the project?s duration (maximum of 3-4 years). We are looking for highly motivated doctoral students, who are interested in performing cutting-edge research in computationally efficient deep learning models, with a particular focus on problems regarding networks training and optimization, compression and fast inference. Prospective applicants should have: ? Strong academic record with an excellent M.Sc. degree in computer science, applied mathematics, or electrical engineering, preferably with expertise in one or more of the following areas: machine learning, deep learning, computer vision; ? A good mathematical background; ? Very good programming skills in languages such as Python, C, C++ and deep learning libraries such as TensorFlow or Pytorch A prior publication in one of the major conferences or journals in computer vision/machine learning is not necessary but would be a very desirable. Application process: For consideration, please send by *October 15th* a resume, names and contact details of two references, transcripts for undergraduate and graduate studies, and a link to a Master thesis (as well as relevant publications if any) with a title *[Prospective PhD student]* to Marco Pedersoli (Marco.Pedersoli at etsmtl.ca) and Hakan Bilen (hbilen at ed.ac.uk) -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- An embedded and charset-unspecified text was scrubbed... Name: not available URL: From visigrapp at insticc.info Tue Oct 2 21:39:57 2018 From: visigrapp at insticc.info (visigrapp at insticc.info) Date: 3 Oct 2018 02:39:57 +0100 Subject: Connectionists: CFP VISAPP 2019 - 14th Int.l Conf. on Computer Vision Theory and Applications (Prague/Czech Republic) Message-ID: <20181003013953.1.A1E926B42C982806@insticc.info> SUBMISSION DEADLINE 14th International Conference on Computer Vision Theory and Applications Submission Deadline: October 22, 2018 http://www.visapp.visigrapp.org/ February 25 - 27, 2019 Prague, Czech Republic. VISAPP is organized in 5 major tracks: - Image Formation and Preprocessing - Image and Video Analysis - Image and Video Understanding - Applications and Services - Motion, Tracking and Stereo Vision In Cooperation with: AAAI and APRP.
Proceedings will be submitted for indexation by: DBLP, Thomson Reuters, EI, SCOPUS and Semantic Scholar.
With the presence of internationally distinguished keynote speakers: Daniel McDuff, Microsoft, United States Diego Gutierrez, Universidad de Zaragoza, Spain Jiri Matas, Czech Technical University in Prague, Faculty of Electrical Engineering, Czech Republic Dima Damen, University of Bristol, United Kingdom Stefano Baldassi, Meta Company, United States A short list of presented papers will be selected so that revised and extended versions of these papers will be published by Springer. All papers presented at the congress venue will also be available at the SCITEPRESS Digital Library (http://www.scitepress.org/DigitalLibrary/). Should you have any question please don't hesitate contacting me. Kind regards, VISAPP Secretariat Address: Av. D. Manuel I, 27A, 2? esq. 2910-595 Setubal, Portugal Tel: +351 265 100 033 Fax: +351 265 520 186 Web: http://www.visapp.visigrapp.org/ e-mail: visapp.secretariat at insticc.org From caspar.schwiedrzik at googlemail.com Wed Oct 3 03:29:13 2018 From: caspar.schwiedrzik at googlemail.com (Caspar M. Schwiedrzik) Date: Wed, 3 Oct 2018 09:29:13 +0200 Subject: Connectionists: =?utf-8?q?Deadline_approaching=3A_PhD_in_visual_p?= =?utf-8?q?erceptual_learning_at_the_Neural_Circuits_and_Cognition_?= =?utf-8?q?lab_=40_ENI_=26_German_Primate_Center_G=C3=B6ttingen?= Message-ID: The European Neuroscience Institute in G?ttingen (ENI-G) Germany, a partnership between the University Medical Center G?ttingen and the Max-Planck-Society, is seeking a *Ph.D. student * About us: The Neural Circuits and Cognition lab of Caspar Schwiedrzik at the European Neuroscience Institute (ENI-G) and the German Primate Center (DPZ) in G?ttingen, Germany is looking for an outstanding PhD student interested in studying the neural basis of perceptual learning in vision. The project investigates neural mechanisms of learning and perception at the level of circuits and single cells, utilizing functional magnetic resonance imaging (fMRI) in combination with electrophysiology and behavioral testing in humans and non-human primates. It is funded by an ERC Starting Grant (Acronym VarPL; ?Specificity or generalization? Neural mechanisms for perceptual learning with variability?). The PhD student?s project will focus on developing new perceptual learning paradigms and investigating the neural basis of perceptual learning in humans using fMRI. In addition, the PhD student will cooperate with other lab members on parallel electrophysiological and fMRI experiments as well as comparative research exploring the same questions in non-human primates. The lab seeks to understand the cortical basis and computational principles of perception and experience-dependent plasticity in the macaque and human brain (see http://www.eni-g.de/groups/neural-circuits-and-cognition). To this end, we use a multimodal approach including fMRI-guided electrophysiological recordings in non-human primates and fMRI and ECoG in humans. The PhD student will play a key role in our research efforts in this area. The lab is located at the ENI (http://www.eni-g.de) and the DPZ ( http://www.dpz.eu), which are interdisciplinary research centers with international faculty and students pursuing cutting-edge research in neuroscience. The PhD student will have access to a new imaging center with a dedicated 3T research scanner, electrophysiology, and behavioral setups. ENI-G is engaged in experimental molecular and cellular research on the central and peripheral nervous systems as well as cognitive and systems neurosciences research. ENI is part of the University Medical Center G?ttingen and associated with the Max Planck Society. The University Medical Center G?ttingen is a tertiary care center. Its 7,400 employees work in over 65 departments and facilities to provide top-quality patient care, excellent research and modern teaching facilities. G?ttingen provides a vibrant and stimulating neuroscience community with a strong background in computational as well as experimental neurosciences. The PhD student will have the opportunity to join one of the fourteen programs of the G?ttingen Graduate School for Neurosciences, Biophysics, and Molecular Biosciences (http://www.ggnb.uni-goettingen.de). Your profile: The position will be available starting in November 2018 with an initial appointment for 3 years and a salary according to 50% TVL-13. Candidates should have a degree (master, diploma or equivalent) in a relevant field (e.g., neuroscience, psychology, biology), and ideally prior experience in fMRI, strong quantitative, programming, and experimental skills, and share a passion for understanding the neural basis of visual perception and its plasticity. Interested candidates should send their curriculum vitae, a description of their scientific interest and the names and contact information of up to two references who are able to comment on your academic background and who agreed to be contacted to c.schwiedrzik at eni-g.de, preferably before *October 10th, 2018*, but later expressions of interest will be considered until the position is filled. A good command of English is a requirement, but fluency in German is not essential. Please apply by 10.10.2018 to: Universit?tsmedizin G?ttingen European Neuroscience Institute G?ttingen Neural Circuits and Cognition Lab Dr. Caspar Schwiedrzik Grisebachstr. 5 37077 G?ttingen Germany Tel.: +49-(0)551-39-61371 E-Mail: c.schwiedrzik at eni-g.de -------------- next part -------------- An HTML attachment was scrubbed... URL: From A.Soltoggio at lboro.ac.uk Wed Oct 3 04:26:20 2018 From: A.Soltoggio at lboro.ac.uk (Andrea Soltoggio) Date: Wed, 3 Oct 2018 09:26:20 +0100 Subject: Connectionists: One funded Ph.D. studentship in Machine Learning Message-ID: Dear All, One funded Ph.D. studentship is available at the Computer Science Department, Loughborough University, to work on evolutionary and learning systems for neural control networks. *Working environment.* The student will be based at the Computer Science Department and will work under the supervision of Dr. Andrea Soltoggio http://www.lboro.ac.uk/departments/compsci/staff/academic-teaching/andrea-soltoggio/ and in collaboration with other laboratories on campus and international partners. The research group has access to a number of robotic platforms such as mobile and flying robots, advanced manufacturing robots, High-Performance Computing clusters, and GPU computing. The Computer Science Department and robotics laboratories have ongoing collaborations with large industries and programs to promote start-ups. Loughborough University is ranked 7th in the UK in the 2019 League Table Ranking http://www.thecompleteuniversityguide.co.uk/loughborough/performance ), and is located in Loughborough, a town well connected to London by a 1h20m journey by train. *Requirements.* The ideal candidate holds (or is about to obtain) a first-class honour undergraduate/postgraduate degree (or equivalent) in Computer Science, Mathematics, Statistics, Electrical or Electronic Engineering, or has authored publications in recognised conferences/journals. Independent working skills are valued as well as the capability of working in a team. Collegiality and interpersonal skills are essential. Excellent English language skills are also essential (see requirements here http://www.lboro.ac.uk/international/englang/index.htm) Start: as soon as possible. Studentship: ?14,777 per annum plus tuition fees at the UK/EU rate for 3 years, plus budget for personal computers and international travel. Enquiries and applications. Interested candidates are invited to send preliminary enquiries to a.soltoggio at lboro.ac.uk including a CV, a university transcript of marks, a list of references, and a statement of about 300 words motivating their interest in this area of research. For the full application, please follow the link: http://www.lboro.ac.uk/study/postgraduate/apply/ Best regards, Andrea Soltoggio -- Dr. Andrea Soltoggio Lecturer in Artificial Intelligence Department of Computer Science, Centre for Information Management Haslegrave Building, N.2.03 Loughborough University LE11 3TU, UK Phone: +44 (0) 1509 635748 Email: a.soltoggio at lboro.ac.uk Twitter: @asoltoggio Web: http://www.lboro.ac.uk/departments/compsci/staff/dr-andrea-soltoggio.html -------------- next part -------------- An HTML attachment was scrubbed... URL: From emmanuel.vincent at inria.fr Wed Oct 3 11:41:27 2018 From: emmanuel.vincent at inria.fr (Emmanuel Vincent) Date: Wed, 3 Oct 2018 17:41:27 +0200 Subject: Connectionists: Audio Source Separation and Speech Enhancement book Message-ID: Dear list, We are glad to announce the release of a new book on Audio Source Separation and Speech Enhancement: https://www.wiley.com/en-us/Audio+Source+Separation+and+Speech+Enhancement-p-9781119279891 This 500-page book provides a unifying view of source separation and enhancement, including but not limited to array processing, matrix factorization, and deep learning based methods, and speech and music applications, with consistent notation and terminology across all chapters. Emmanuel, Tuomas, and Sharon -- Emmanuel Vincent Multispeech Project-Team Inria Nancy - Grand Est 615 rue du Jardin Botanique, 54600 Villers-l?s-Nancy, France Phone: +33 3 8359 3083 - Fax: +33 3 8327 8319 Web: http://members.loria.fr/evincent/ From memming.park at stonybrook.edu Wed Oct 3 13:42:35 2018 From: memming.park at stonybrook.edu (Il Memming Park) Date: Wed, 3 Oct 2018 13:42:35 -0400 Subject: Connectionists: Multiple open-rank tenure-track positions open at the AI Institute of Stony Brook University Message-ID: The department of computer science and department of biomedical informatics at the Stony Brook University are recruiting tenure track faculties. The senior-level position come with the title of Empire Innovation Professor, and enhanced salary and research support. Exceptionally qualified senior and junior candidates in *all areas of Artificial Intelligence* are invited to apply, particularly in the following areas: *Machine learning, computer vision, natural language processing or data science*. See the following links for details: https://www.cs.stonybrook.edu/about-us/career/Multiple-Positions-all-levels-Empire-Innovation-Professor-AI-Institute-Stony-Brook-University Official Job Title: Assistant, Associate or Full Professor REF#: F-9924-18-08 *The position will be open until filled.* Sincerely, Memming Park -- Assistant Professor Department of Neurobiology and Behavior Department of Applied Mathematics and Statistics Institute for Advanced Computing Science Institute for AI-Driven Discovery and Innovation Stony Brook University http://catniplab.github.io -------------- next part -------------- An HTML attachment was scrubbed... URL: From kyunghyun.cho at nyu.edu Wed Oct 3 11:03:18 2018 From: kyunghyun.cho at nyu.edu (Kyunghyun Cho) Date: Wed, 3 Oct 2018 11:03:18 -0400 Subject: Connectionists: Professor of Data Science and Mathematics at NYU Message-ID: Professor of Data Science and Mathematics Open rank (tenured/tenure-track) The Center for Data Science (CDS) and the Courant Institute of Mathematical Sciences seeks candidates for an open rank joint faculty position, anticipated to begin in in September 2019. Appointments may be made at either a junior or senior level. Background CDS is the focal point for NYU?s university-wide initiative in data science and statistics, established 5 years ago, and one of the country?s leading data science research and training facilities. CDS is a vibrant space with about 15 jointly appointed faculty (growing to over 20 in the next two years) and about 10 associated faculty across computer science, mathematics, engineering, neuroscience, linguistics, politics, psychology, physics, biology and business; a list of affiliate faculty spanning a wide range of NYU?s schools and departments, a highly successful Masters program and one of the first Data Science PhD programs. CDS?s research focuses on tools and methods at the intersection between applied mathematics, data science, high-dimensional statistics, machine learning, optimization, and several data-driven application areas. The Courant Institute houses one of the top applied mathematics departments in the world. CDS and the Math department both host vibrant interdisciplinary Ph.D. programs and several faculty at NYU are already jointly appointed at both the Center for Data Science and Courant. We seek a strong candidate who will leverage existing strengths of the Courant Institute in applied mathematics to carry out data science research. We are particularly focused on expanding in the area of Applied and Theoretical Statistics as well as interdisciplinary areas where the innovative and principled use of statistics is of vital importance. Exceptional candidates from other data-science relevant areas, such as optimization and the mathematical foundations of inference and data-representation will be considered as well. Requirements Please include a CV, a short statement of your research and teaching interests, and a list of at least three references capable of providing a letter on your behalf. A Ph.D. in Statistics, Computer Science, Mathematics, or a related quantitative field is required. How to Apply Applications must be submitted through the NYU Careers portal. Applications and supporting documents received by December 15th, 2018 will receive full consideration. *Please note, the official job posting should be live within the next few days, applicants can submit their applications at that time. Please be sure to check the careers page, and this page frequently for updates. We will provide a link to the official job posting as soon as it?s live. Equal Opportunity The Courant Institute/New York University is an Equal Opportunity/Affirmative Action Employer. Applications from women and underrepresented groups are particularly encouraged. New York University is situated in Greenwich Village, one of the most vibrant and family friendly neighborhoods in the City of New York. -------------- next part -------------- An HTML attachment was scrubbed... URL: From dwang at cse.ohio-state.edu Wed Oct 3 21:39:03 2018 From: dwang at cse.ohio-state.edu (DeLiang Wang) Date: Wed, 3 Oct 2018 21:39:03 -0400 Subject: Connectionists: Neural Networks Best Paper Award Message-ID: <710518e7-f33f-4cef-5a5b-2bef0b8355e8@cse.ohio-state.edu> We are pleased to announce the recipient of the 2016 Best Paper Award: "Evolving Spatio-temporal Data Machines Based on the NeuCube Neuromorphic Framework: Design Methodology and Selected Applications" by Nikola Kasabova, Nathan M. Scott, ..., and Jie Yang, published in Neural Networks, volume 78, pp. 1-14, June 2016. More details are given below: https://www.journals.elsevier.com/neural-networks/news/neural-networks-best-paper-award-winner-announced This paper has open access: https://doi.org/10.1016/j.neunet.2015.09.011 Kenji Doya and DeLiang Wang Co-Editors-in-Chief Neural Networks From recruitment at bioinf.jku.at Thu Oct 4 01:08:25 2018 From: recruitment at bioinf.jku.at (Recruitment) Date: Thu, 4 Oct 2018 07:08:25 +0200 Subject: Connectionists: Research Fellow in Machine Learning / Deep Learning, Hochreiter Group, Linz, Austria Message-ID: <75376bdd-4660-14a3-1f5d-dbb1c12af0f8@bioinf.jku.at> Research Fellow in Machine Learning / Deep Learning, Hochreiter Group, Linz, Austria Johannes Kepler University Linz (JKU), Austria, is looking for two post-doctoral research fellows to advance machine learning and deep learning research with Sepp Hochreiter. These six year positions are affiliated both with the newly established LIT AI Lab and the Institute for Machine Learning. Job description: ???? conduct independent research in the field, ?? ? collaborate in machine learning and deep learning projects, ???? publish in renowned international journals and conferences, ???? supervise students; prepare and hold lectures; support study programs. Requirements: ???? PhD degree, ???? track record in machine learning (e.g. deep learning, reinforcement learning, kernel methods, probabilistic modeling, meta-learning, attention models), ???? knowledge in one or more of the following application domains is a plus: signal processing, vision, speech, natural language processing, physics, bio-/chemoinformatics, computational medicine, autonomous driving, ???? willingness and ability to work in a team and to support students and junior researchers. About the group: Within the last years, Sepp Hochreiter (who is best known for the invention of LSTM, for the Vanishing Gradient problem, ?Flat Minima?, and ?Learning to Learn?) has built up a dynamic team of more than 20 researchers. The group has recently achieved widely acclaimed contributions and successes, such as, winning the NIH?s Tox21 toxicity prediction challenge with deep learning, the invention of the ELU activation function, Self-Normalizing Networks, and providing a convergence proof for GAN learning. The group has many international collaborations and receives funding from national and international research programs as well as from companies, such as, Johnson&Johnson, Merck, Bayer, Zalando and from joined labs like the Audi.JKU Deep Learning Center. About the location: The area offers an excellent quality of living in the heart of Europe ? close to the alps between Vienna, Salzburg, Prague and Munich. Linz provides a superb cultural environment, most famous for the Ars Electronica Festival, the Brucknerfest, and the nearby Salzburg Festival. The picturesque and versatile landscape provides countless options for recreation and sports in nature (skiing, hiking, climbing, cycling, and many more). If you have questions, please contact: Prof. Dr. Sepp Hochreiter, +43 732 2468 4520, recruitment at bioinf.jku.at. Prospective applicants interested in this position are requested to electronically send an application via the online portal http://jku.at/application. Please include ?Job Reference Number 3578? (deadline: Dec 12, 2018). From stolu at elektro.dtu.dk Thu Oct 4 08:43:33 2018 From: stolu at elektro.dtu.dk (Silvia Tolu) Date: Thu, 4 Oct 2018 12:43:33 +0000 Subject: Connectionists: Research Assistant position at Technical University of Denmark In-Reply-To: References: , Message-ID: Dear all, the Technical University of Denmark offers a three-months research assistantship in the research field of neuro-robotics. The candidate will be part of a team that is already involved in the framework of the EU Flagship Project ?Human Brain Project? (HBP). The position addresses research in neural computation for robotics systems. Please find enclosed the pdf with all the necessary information and contact. Kind regards/ Med venlig hilsen, Silvia Tolu Postdoctoral Researcher, Marie Curie Fellow Technical University of Denmark Department of Electrical Engineering ------------------------------------ Richard Petersens Plads Building 326 2800 Kgs. Lyngby Direct +45 45253928 -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: Research_Assistant_in_Neuromorphic.pdf Type: application/pdf Size: 69262 bytes Desc: Research_Assistant_in_Neuromorphic.pdf URL: From boris.gutkin at ens.fr Thu Oct 4 14:24:04 2018 From: boris.gutkin at ens.fr (boris gutkin) Date: Thu, 4 Oct 2018 20:24:04 +0200 Subject: Connectionists: =?utf-8?q?Tenure_Track_Position_in_Computational_?= =?utf-8?q?Neuroscience_Ecole_Normale_Sup=C3=A9rieure_Paris_France?= Message-ID: Junior Professor in Computational Neuroscience at Ecole Normale Superieure, Paris France Department of Cognitive Studies at the Ecole Normale Superieure (Paris France) seeks candidates for a tenure-track junior professor in computational neuroscience. Candidates in cognitive computational neuroscience, machine learning approaches to neuroscience and statistical neuroscience are particularly encouraged to apply. Successful candidate will join the computational neuroscience core at the Laboratory for Cognitive and Computational Neuroscience (LNC2, https://lnc2.dec.ens.fr/fr). Candidates should show a strong track record of research in computational neuroscience as well as potential for scientific independence and achievement. Candidate will be expected to develop an independent research program during their pre-tenure period In addition to research candidates will spear-head the computational neuroscience track in the Master of Cognitive Sciences at ENS (Cogmaster,www.cogmaster.net/ ), provide teaching in computational neuroscience at the masters and upper undergraduate level as well as supervise masters and doctoral students. The position offers a 5-year tenure-track contract with an evaluation at the end of the 3rd year. Upon successful evaluaton, the candidate will proceed directly to a competition for a full professorship at ENS Paris. Support for national and international grant competitions will be provided. The candidate will join a lively cognitive neuroscience and computational neuroscience community. Notably the computational neuroscience core of the LNC includes research groups of Boris Gutkin, Srdjan Ostojic and Sophie Deneve and counts over 20 members in total. Computational approaches to human cognitive neuroscience and neuroeconomics are also represented by groups of Etienne Koechlin, Valentin Wyart and Stefano Palminteri. Ample interactions with experimental and computational groups in the Paris area are available and encouraged. LNC2-DEC-ENS is located in the heart of Paris in the Quartier Latin. Candidates should send an application package by e-mail to the application email address below. The subject line should include the words COMPUTATIONAL NEUROSCIENCE ENS POSITION followed by the name of the applicant. APPLICATION ADDRESS: recruitment.jp-compneuro at ens.fr The application package should include: - a CV, including a list of publications; - contacts of 3 referees from whom recommendations letters can be requested; - ?a statement outlining both teaching and research goals/experience (up to 3 pages); - a research sample consisting of 3 papers. Deadline for the applications is Nov 15 2018. Candidate is expected to start in September 2019. Informal enquiries and Questions can be sent to boris.gutkin at ens.fr <> -------------- next part -------------- An HTML attachment was scrubbed... URL: From ohad.kammar at gmail.com Thu Oct 4 23:15:08 2018 From: ohad.kammar at gmail.com (Ohad Kammar) Date: Thu, 4 Oct 2018 23:15:08 -0400 Subject: Connectionists: LAFI 2019: Languages for Inference --- First Call-for-Proposals Message-ID: LAFI 2019: Languages for Inference (formerly PPS) ================================================ Tuesday, 15 January 2019, Cascais/Lisbon, Portugal A workshop affiliated with POPL 2019 https://popl19.sigplan.org/track/lafi-2019 Important dates (anywhere on earth) ------------------------------------------------- LAFI submission deadline Thu 1 Nov 2018 Notification Mon 3 Dec 2018 Early Registration Deadline TBD Workshop Tue 15 Jan 2019 ------------------------------------------------- Submission: https://lafi19.hotcrp.com/ Registration: TBD Context ======= Inference concerns re-calibrating program parameters based on observed data, and has gained wide traction in machine learning and data science. Inference can be driven by probabilistic analysis and simulation, and through back-propagation and differentiation. Languages for inference offer built-in support for expressing probabilistic models and inference methods as programs, to ease reasoning, use, and reuse. The recent rise of practical implementations as well as research activity in inference-based programming has renewed the need for semantics to help us share insights and innovations. This workshop aims to bring programming-language and machine-learning researchers together to advance all aspects of languages for inference. Topics include but are not limited to: + design of programming languages for inference and/or differentiable programming; + inference algorithms for probabilistic programming languages, including ones that incorporate automatic differentiation; + automatic differentiation algorithms for differentiable programming languages; + probabilistic generative modelling and inference; + variational and differential modelling and inference; + semantics (axiomatic, operational, denotational, games, etc) and types for inference and/or differentiable programming; + efficient and correct implementation; + and last but not least, applications of inference and/or differentiable programming. For a sense of the talks, posters, and blogs in past years, see + PPS-2018: http://conf.researchr.org/track/POPL-2018/pps-2018 blog: http://pps2018.soic.indiana.edu/ + PPS-2017: http://conf.researchr.org/track/POPL-2017/pps-2017 blog: http://pps2017.soic.indiana.edu/) + PPS-2016: http://conf.researchr.org/track/POPL-2016/pps-2016 blog: http://pps2016.soic.indiana.edu/) This year we are explicitly expanding the focus of the workshop from statistical probabilistic programming to encompass differentiable programming for statistical machine learning. We expect this workshop to be informal, and our goal is to foster collaboration and establish common ground. Thus, the proceedings will not be a formal or archival publication, and we expect to spend only a portion of the workshop day on traditional research talks. Nevertheless, as a concrete basis for fruitful discussions, we call for extended abstracts describing specific and ideally ongoing work on probabilistic programming languages, semantics, and systems. Submission guidelines ===================== Extended abstracts are up to 2 pages in PDF format, excluding references. Please submit them by November 1 (AoE) using HotCRP at: https://lafi19.hotcrp.com/ In line with the SIGPLAN Republication Policy: http://www.sigplan.org/Resources/Policies/Republication/ inclusion of extended abstracts in the programme is not intended to preclude later formal publication. Programme committee co-chairs: Jeffrey Siskind, School of Electrical and Computer Engineering, Purdue University Ohad Kammar, University of Oxford -------------- next part -------------- An HTML attachment was scrubbed... URL: From v.steuber at herts.ac.uk Fri Oct 5 07:03:17 2018 From: v.steuber at herts.ac.uk (Steuber, Volker) Date: Fri, 5 Oct 2018 11:03:17 +0000 Subject: Connectionists: PhD studentship: Rapid Bacteria Colony Counting Algorithm Development In-Reply-To: <1529080128822.22268@herts.ac.uk> References: <1496229607391.68206@herts.ac.uk>, <1527249156023.61617@herts.ac.uk>, <1529080128822.22268@herts.ac.uk> Message-ID: <1538737392575.21384@herts.ac.uk> PhD Studentship: Rapid Bacteria Colony Counting Algorithm Development ?Biocomputation Research Group , University of Hertfordshire and Synoptics Limited, Cambridge Programme Description The University invites applications for a PhD student to join our Hertfordshire Knowledge Exchange Partnership (HKEP) scheme. This four-year project requires a PhD student to undertake a collaborative research project with support from University academic supervisor(s) and company scientists. The project begins with a Knowledge Exchange year in which you are based in the company. Successful completion of the first year will require the submission of a scientific report, research proposal and an oral examination. The successful candidate will then begin a three-year PhD research project in an area of interest to the company. Start date: January 2019 Duration: Four years Company: Synoptics Limited, Cambridge Stipend: Starts at ?15,220 per annum plus approved expenses. All students will also receive a maximum contribution towards their individual tuition fees that is equivalent to the Home/EU student fee in each year of registration. Project Overview: Bacterial colony counting is widely used in both industry and research laboratories in a wide range of applications; these include quality control, environmental monitoring, immunological studies and medical testing. The number of colonies on an agar plate can be used to estimate the number of viable bacteria (total viable count) present in a test sample. This can then be used as an indicator of the cleanliness of a surface, the sterility of a product or the presence of a bacterial infection. Traditionally, colony counting was performed manually or using a light box which was time-consuming and prone to human error. The advent of automated colony counters, which use sophisticated algorithms to detect and count colonies based on shape or colour, has overcome these drawbacks. The popular technologies exploited for bacteria colony counting are edge detection techniques for image processing. However, a number of challenges remain in automated colony counting: identifying and splitting touching colonies, background noise, colony density variance etc. Hence, more advanced and sophisticated techniques need to be developed to cope with these issues while taking efficiency into account. The aim of this project is to propose and implement new algorithms which are robust to noise for rapid bacterial colony detection and counting. Supervisor Information Dr Na Helian Dr Yi Sun Dr Peter Lane Mr Richard Hopwood Application Process For further information and to apply for this role please email hsp at herts.ac.uk. The deadline for applications is 31st October 2018. Informal enquires should be addressed to Dr. Na Helian (n.helian at herts.ac.uk). Please note that applications sent directly to these address will not be accepted.? https://www.jobs.ac.uk/job/BNE643/phd-studentship-rapid-bacteria-colony-counting-algorithm-development? -------------- next part -------------- An HTML attachment was scrubbed... URL: From rrosenb1 at nd.edu Fri Oct 5 14:56:26 2018 From: rrosenb1 at nd.edu (Robert Rosenbaum) Date: Fri, 5 Oct 2018 14:56:26 -0400 Subject: Connectionists: Two Faculty Positions in Applied Mathematics and Statistics - Univ. of Notre Dame, USA Message-ID: Dear colleagues, The Department of Applied and Computational Mathematics and Statistics (ACMS) in the University of Notre Dame is accepting applications for two faculty positions: 1) Tenure-track Robert and Sara Lumpkins Assistant Professor in Applied Mathematics (in rare cases, consideration could be given to appointment at the associate professor level for an outstanding candidate) to be filled this year in the broad area of applied and computational mathematics. 2) Associate or Full Professor in Statistics (in rare cases, consideration could be given to appointment at the endowed, full professor level for an exceptional candidate) to be filled this year. Preference will be given to applicants whose research includes multi-disciplinary collaborations including research in computational neuroscience and related fields. Applicants must submit a cover letter, curriculum vitae, research and teaching statements, and should also arrange for at least three letters of recommendation to be submitted through the Interfolio system (https://apply.interfolio.com/53861 for the Applied Math position and https://apply.interfolio.com/53860 for Statistics). These letters should address the applicant's research accomplishments and supply evidence that the applicant has the ability to communicate articulately and teach effectively. The successful applied mathematics applicants must have a doctorate in mathematics, applied mathematics, computational sciences, or a closely related field, and a record of success in both research and teaching. The successful statistics applicants must have a doctorate in statistics, biostatistics, or a closely related field, and a record of success in both research and teaching. ACMS includes research groups in applied mathematics, statistics and computational science. ACMS offers a Bachelor of Science, a doctoral degree, a research master?s degree, and a professional master?s degree. ACMS is a department in the College of Science. The teaching load in ACMS is three courses per year, and the position begins in August 2019. We will begin reviewing completed applications October 1, and continue accepting applications through December 1. If the application is for a tenure-level position teaching evaluations from the past three years are also required. Applicants are invited to contact the Department Chair, Bei Hu, at b1hu at nd.edu, at any time. ? Robert Rosenbaum Assistant Professor Department of Applied and Computational Mathematics and Statistics University of Notre Dame From torcini at gmail.com Sun Oct 7 11:34:31 2018 From: torcini at gmail.com (A. Torcini) Date: Sun, 7 Oct 2018 17:34:31 +0200 Subject: Connectionists: Professor Position in Theoretical Physics - Cergy-Pontoise (France) Message-ID: Dear all, We expect the opening of a Full Professor position at the Theoretical Physics and Modelisation Laboratory (LPTM), Physics Department, University Cergy Pontoise, France. Position to start in September 2019. This position will be endowed by Labex MME-DII (see https://labex-mme-dii.u-cergy.fr/) with a "Chaire d'Excellence" or special funding involving: A 4-year 10,000 Euros/year personal research grant A 4-year, up to 13,000 Euros/year, salary bonus A 4-year partial two-third teaching dispensation, leading to a 64 hrs annual service instead of the statutory 192 hrs. Teaching at Physics Department, Universit? Cergy Pontoise, is done at undergraduate/graduate/postgraduate level; note that teaching curriculum includes a fully-English taught Master degree in Theoretical Physics , see https://www.u-cergy.fr/fr/formations/programms-taught-in-english/msc-master-of-science.html LPTM is a jointly supervised CNRS-Universit? Cergy Pontoise research entity within the Physics Department, Faculty of Science and Techniques, UCP. Research domains include: Condensed Matter Physics, 2D physics , Fundaments of quantum theory, Cold Atoms, with strong numerical aspects and connections with experimental groups; Classical and Quantum Integrable systems; Stochastic processes and theoretical statistical mechanics; Soft matter theory, Complex systems, Non-linear dynamics and computational neuroscience . Research collaborations involve more than 80 laboratories or departments of Physics, Mathematical Sciences and Computer Sciences throughout the world. We are looking for outstanding candidates with a high level expertise in one or several domains pertaining to this research spectrum, without any predefined priority. Note that application to a French Professor position is subject to getting the "Qualification" assessment from French academic institution, the next call for the "Qualification aux fonctions de Professeur des Universit?s" DEADLINE 24 october 2018. It is recommended to obtain it at national level by applying through the portal: https://www.galaxie.enseignementsup-recherche.gouv.fr/ensup/cand_qualification_droit_commun.htm Confirmation of opening is to occur around October 2018. Application schedule and procedures will be found on the above-mentioned portal. during March 2019. The expected start of the position is September 2019. Please feel free to diffuse this information as broadly as you think it useful. For more information you may contact: Jean Avan, Chairman LPTM: jean.avan at u-cergy.fr Andreas Honecker, Deputy Chairman; andreas.honecker at u-cergy.fr Flora Koukiou, Head of Department: flora.koukiou at u-cergy.fr Best regards Jean Avan From pgrover at andrew.cmu.edu Sun Oct 7 22:03:02 2018 From: pgrover at andrew.cmu.edu (Pulkit Grover) Date: Sun, 7 Oct 2018 22:03:02 -0400 Subject: Connectionists: Slice electrophysiology postdoc and technician positions at Carnegie Mellon's Neurosciences Institute In-Reply-To: References: Message-ID: Dear Colleagues, As a part of a newly funded project, Grover, Chamanzar, Kainerstorfer, Barth, and Gittis labs at Carnegie Mellon University (Pittsburgh, PA, USA) are actively looking for joint postdocs and technicians for slice electrophysiology experiments. Our team's goal is to develop novel methods for neural stimulation and recording in somatosensory and motor cortex for closed-loop experiments in rodents and in future in non-human primates. We aim to establish advanced theoretical techniques, closely with experimental validation, for invasive and noninvasive high-throughput neurostimulation, and recording with high spatiotemporal resolution for advancing diagnosis treatment of disorders such as epilepsy, Parkinson's, and brain injuries, as well as fundamental understanding of the brain. This is an ideal opportunity for a neuroscientist or a biomedical engineer who wants to be involved in developing next generation neural interfacing techniques and use these advanced methods for fundamental and applied neuroscience studies. The role of the technician is to perform surgeries and prepare brain slices and help with the experiments. The technician is expected to directly work with students and postdocs to design and conduct experiments. The postdoc will be affiliated with the Carnegie Mellon Neuroscience Institute, and will get the opportunity to work with a team of accomplished researchers from various disciplines ranging from Biological Sciences, ECE, BME at CMU as well as clinicians at University of Pittsburgh. This is an opportunity to work on a challenging scientific problem in a highly interdisciplinary and vibrant environment. *Requirements*: Prior experience with rodent surgeries, particularly mice. Interest in or experience with brain slice preparation and experiments. Experience with patch clamp recording and electrophysiology or voltage imaging in neurons is essential. The labs are committed to the professional development of the members, making this position a valuable preparation for those interested in academic, industrial or entrepreneurial careers. The position has no mandatory teaching or administrative duties. The ideal start date is as soon as possible (11/2018 or shortly thereafter), but application review will continue until the positions are filled. The position is initially for at least 12 months with the possibility of renewal. Compensation will be competitive, and commensurate with relevant experience. CMU has competitive benefits (including comprehensive medical insurance) and is an equal opportunity employer. Candidates should send a CV, a statement of research experience and interests, expected date of availability, and the contact information for three references to pulkit at cmu.edu, mchamanz at andrew.cmu.edu, and jkainers at andrew.cmu.edu with the subject line "Brain Slice Positions?. Please find the ads attached. Thanks Pulkit on behalf of CMU faculty: Pulkit Grover Maysam Chamanzar Jana Kainerstorfer Alison Barth Aryn Gittis -- Pulkit Grover Associate Professor Electrical & Computer Engineering Biomedical Engineering (by courtesy) Center for Neural Basis of Cognition (by courtesy) Carnegie Mellon University, Pittsburgh, PA -15213. -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: CMUBrainSliceTechnicianPosition.pdf Type: application/pdf Size: 124055 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: CMUBrainSlicePostdocPosition.pdf Type: application/pdf Size: 113823 bytes Desc: not available URL: From mark.humphries at manchester.ac.uk Mon Oct 8 07:34:51 2018 From: mark.humphries at manchester.ac.uk (Mark Humphries) Date: Mon, 8 Oct 2018 11:34:51 +0000 Subject: Connectionists: Postdoctoral position in circuit modelling at Nottingham, deadline 7th November Message-ID: <7E954275ED82B9468C2C731FB72522F5013E110AF2@MBXP09.ds.man.ac.uk> A postdoctoral position is available in the lab of Prof Mark Humphries at the University of Nottingham. We seek a postdoctoral researcher to tackle the deep question of how dopamine controls the dynamics of the striatum. As the main target of dopamine in the brain, the striatum bears the brunt of dopamine loss in Parkinson?s disease. Yet how dopamine controls the output of the striatum, and how the loss of dopamine disrupts that output, is unknown. The successful candidate will be responsible for constructing and simulating models of the striatum to investigate how dopamine controls the striatum?s dynamics, and the implications this will have for Parkinson?s disease. The project will build upon the detailed models of the striatum from the Humphries group (e.g. Humphries et al 2009 Neural Networks; 2010, PLoS Computational Biology). This is also a chance to join the newly-created computational neuroscience centre at Nottingham, which includes Profs Mark van Rossum and Stephen Coombes. Find out more about the lab and its interests here: https://www.humphries-lab.org/ The post will be available for 18 months in the first instance. More details, eligibility, and application instructions here: https://www.nottingham.ac.uk/jobs/currentvacancies/ref/SCI353818 Deadline: 7th November 2018 To discuss this or other projects, please contact Mark (mark.humphries at nottingham.ac.uk). Professor Mark Humphries | MRC Senior non-Clinical Fellow | Chair in Computational Neuroscience humphries-lab.org [0da17e2a-9ed5-496a-b161-9fd4491ce5c7]@markdhumphries Public blog: https://medium.com/the-spike -------------- next part -------------- An HTML attachment was scrubbed... URL: From bhuang at vt.edu Mon Oct 8 16:53:38 2018 From: bhuang at vt.edu (Bert Huang) Date: Mon, 8 Oct 2018 16:53:38 -0400 Subject: Connectionists: Job opening: TT Assistant Professor in AI/ML at Virginia Tech Message-ID: <1B79A773-AAE3-4A35-B92A-0877EB42FB6F@vt.edu> Folks, Virginia Tech?s Department of Computer Science is looking for faculty in AI and ML. See the ad pasted below. Feel free to reach out to me with questions, as I?m on the search committee. I?ll also be at NIPS, if you want to discuss there. Bert --------------------- ASSISTANT PROFESSOR IN AI/ML The Department of Computer Science at Virginia Tech (cs.vt.edu) seeks applicants for a tenure-track assistant professor position in artificial intelligence and/or machine learning. Exceptional candidates at higher ranks may also be considered. Candidates with core research interests in AI/ML are especially encouraged to apply. Some example areas include deep learning, reinforcement learning, natural language processing, probabilistic models, optimization, and learning theory, computing, and intelligent systems. CANDIDATES The successful candidate will join an active group of CS faculty in the AI/ML area, many of whom are members of the Discovery Analytics Center (dac.cs.vt.edu), which leads data science research on campus. CS faculty also collaborate in other interdisciplinary research groups, including the Center for Human Computer Interaction (hci.vt.edu) and the Center for Business Intelligence and Analytics (cbia.pamplin.vt.edu). Faculty participate in data analytics education initiatives (analytics.cs.vt.edu), including the Computational Modeling and Data Analytics (ais.science.vt.edu/programs/cmda.html) undergraduate program. Computer Science also collaborates closely with many departments, including Electrical and Computer Engineering (ece.vt.edu) and Statistics (stat.vt.edu), and more broadly across the university, including with the Hume Center for National Security and Technology (hume.vt.edu) and the Biocomplexity Institute (bi.vt.edu). Successful candidates will have the opportunity to engage in transdisciplinary research, curriculum, and outreach initiatives with other university faculty working in the Data & Decisions Destination Area, one of several university-wide initiatives (provost.vt.edu/destination-areas). Candidates must have a Ph.D. in computer science or related field at the time of appointment, and a rank-appropriate record of scholarship and collaboration in computing research. They are expected to develop a nationally recognized research group. The successful candidate will be expected to teach graduate and undergraduate courses, mentor graduate students, and should support diversity in the campus community. Virginia Tech is committed to building a culturally diverse faculty and strongly encourages applications from traditionally underrepresented communities. The position requires occasional travel to professional meetings. The selected candidate must pass a criminal background check prior to employment. COMPUTER SCIENCE AT VIRGINIA TECH The department has 53 teaching faculty, including 47 tenured or tenure-track faculty, over 950 undergraduate majors, and over 250 graduate students. Departmental annual research expenditures over the last four years average $12 million. The department is in the College of Engineering (eng.vt.edu), whose undergraduate program ranks 13th and graduate program ranks 30th among all U.S. engineering schools (USN&WR). This position is located at the main campus in Blacksburg, VA (blacksburg.gov), in a region that is consistently ranked among the country's best places to live. HOW TO APPLY Applications must be submitted online to jobs.vt.edu for posting #TR0180129. Applicant screening will begin on December 10, 2018 and continue until the position is filled. Inquiries should be directed to Dr. Edward Fox, Search Committee Chair, fox at vt.edu. Virginia Tech does not discriminate against employees, students, or applicants on the basis of age, color, disability, gender, gender identity, gender expression, national origin, political affiliation, race, religion, sexual orientation, genetic information, or veteran status; or otherwise discriminate against employees or applicants who inquire about, discuss, or disclose their compensation or the compensation of other employees, or applicants; or any other basis protected by law. From sergio.escalera.guerrero at gmail.com Tue Oct 9 05:19:47 2018 From: sergio.escalera.guerrero at gmail.com (Sergio Escalera) Date: Tue, 9 Oct 2018 11:19:47 +0200 Subject: Connectionists: Springer book: Inpainting and Denoising, call for book chapters Message-ID: *Springer book: Inpainting and Denoising, call for book chapters* *Deadline: 30/10/2018* Contact: sergio.escalera.guerrero at gmail.com ************************************************************************ *Aims and scope**: * The problem of dealing with missing data or incomplete data in machine learning arises in many applications. Recent strategies make use of generative models to impute missing or corrupted data. Advances in computer vision using deep generative models have found applications in image/video processing, such as denoising [1], restoration [2], super-resolution [3], or inpainting [4,5]. We focus on image and video inpainting tasks, that might benefit from novel methods such as Generative Adversarial Networks (GANs) [6,7] or Residual connections [8,9]. Solutions to the inpainting problem may be useful in a wide variety of computer vision tasks. *Book chapter contribution**: *The scope comprises all aspects of image and video inpainting and denoising. Including but not limited to the following topics: - 2D/3D human pose recovery under occlusion, - human inpainting, - human retexturing, - video decaptioning, - temporal occlusion recovery, - object recognition under occlusion, - fingerprint recognition, - fingerprint denoising, - future frame video prediction, - unsupervised learning for missing data recovery and/or denoising, - new data and applications of inpainting and/or denoising. Book chapter submission instructions: http://chalearnlap.cvc.uab.es/workshop/29/schedule/ There is no page limit. Authors have to use this template . Contributions will be published within a volume in this series: http://www.springer.com/series/15602. *References:* [1] V. Jain and S. Seung, ?Natural image denoising with convolutional networks,? in Advances in Neural Information Processing Systems, 2009, pp. 769?776. [2] L. Xu, J. S. Ren, C. Liu, and J. Jia, ?Deep convolutional neural network for image deconvolution,? in Advances in Neural Information Processing Systems 27, Z. Ghahramani, M. Welling, C. Cortes, N. D. Lawrence, and K. Q. Weinberger, Eds. Curran Associates, Inc., 2014, pp. 1790?1798. [3] C. Dong, C. C. Loy, K. He, and X. Tang, ?Image super-resolution using deep convolutional networks,? IEEE transactions on pattern analysis and machine intelligence, vol. 38, no. 2, pp. 295?307, 2016. [4] J. Xie, L. Xu, and E. Chen, ?Image denoising and inpainting with deep neural networks,? in Advances in Neural Information Processing Systems, 2012, pp. 341?349. [5] A. Newson, A. Almansa, M. Fradet, Y. Gousseau, and P. P?erez, ?Video inpainting of complex scenes,? SIAM Journal on Imaging Sciences, vol. 7, no. 4, pp. 1993?2019, 2014. [6] I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio, ?Generative adversarial nets,? in Advances in neural information processing systems, 2014, pp. 2672?2680. [7] D. Pathak, P. Kr?ahenb?uhl, J. Donahue, T. Darrell, and A. Efros, ?Context encoders: Feature learning by inpainting,? in Computer Vision and Pattern Recognition (CVPR), 2016. [8] K. He, X. Zhang, S. Ren, and J. Sun, ?Deep residual learning for image recognition,? in The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2016. [9] X.-J. Mao, C. Shen, and Y.-B. Yang, ?Image Restoration Using Convolutional Auto-encoders with Symmetric Skip Connections,? ArXiv e-prints, Jun. 2016. -- *Dr. Sergio Escalera Guerrero*Head of Human Pose Recovery and Behavior Analysis Lab Project Manager at the Computer Vision Center Director of ChaLearn Challenges in Machine Learning Associate professor at University of Barcelona / Universitat Oberta de Catalunya / Aalborg Univ. / Dalhousie University Phone:+34934020853 Email: sergio.escalera.guerrero at gmail.com / Webpage: http://www.sergioescalera.com/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From dst at cs.cmu.edu Wed Oct 10 04:47:16 2018 From: dst at cs.cmu.edu (Dave Touretzky) Date: Wed, 10 Oct 2018 04:47:16 -0400 Subject: Connectionists: job: Assistant Professor in Systems Neuroscience with computational interests Message-ID: <31449.1539161236@ammon2.boltz.cs.cmu.edu> To apply: https://apply.interfolio.com/53283 The Department of Biological Sciences and the Center for the Neural Basis of Cognition (CNBC) at Carnegie Mellon University seek a tenure-track faculty candidate in systems neuroscience at the assistant professor level. Carnegie Mellon is strongly committed to expanding brain research and investing in new faculty that span the disciplines of computational and systems neuroscience. As part of this effort, Carnegie Mellon is establishing a new, cross-disciplinary neuroscience institute (seehttps://www.cmu.edu/news/stories/archives/2018/february/neuroscience-institute.html) that will bring together various neuroscience initiatives and programs at the institution, including the CNBC at Carnegie Mellon. Brain science faculty have access to facilities that include a state-of-the-art animal facility, high-performance computing clusters, and neuroimaging centers (see http://www.cmu.edu/bio and http://www.cnbc.cmu.edu). The candidate will join a growing and highly interactive neuroscience community at Carnegie Mellon and will be a member of the CNBC, an interdisciplinary and collaborative group of neuroscientists from Carnegie Mellon and the University of Pittsburgh. Applications are encouraged from individuals using advanced, cutting-edge techniques to examine the dynamic properties of neuronal ensembles in vivo, especially in awake or freely-moving animals. The candidate will join a faculty with strength in big data analytics, machine learning, signal processing, and bioengineering. Preference will be given to a candidate who will leverage these tools for data acquisition and analysis, especially those whose own research helps drive innovation in these areas. Questions can be addressed to Prof. Aryn Gittis (agittis at cmu.edu). To apply: https://apply.interfolio.com/53283 From maneesh+connectionists at gatsby.ucl.ac.uk Wed Oct 10 07:38:55 2018 From: maneesh+connectionists at gatsby.ucl.ac.uk (Maneesh Sahani) Date: Wed, 10 Oct 2018 12:38:55 +0100 Subject: Connectionists: Gatsby Unit PhD programme (Theoretical Neuroscience and Machine Learning) Message-ID: Application for 2019 entry to the Gatsby Unit PhD programme is open. The deadline is 15th November 2018. The Gatsby Computational Neuroscience Unit at UCL is a leading research centre focused on theoretical neuroscience and machine learning. We study unsupervised, supervised and reinforcement learning in brains and machines; inference, coding and neural dynamics; Bayesian and kernel methods, and deep learning; with applications to the analysis of perceptual processing and cognition, neural data, signal and image processing, machine vision and nonparametric hypothesis testing. The Unit 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 we share 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 and Francis Crick Institutes. Students at the Gatsby Unit complete a four-year 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 and intensive introduction to both fields. Students are encouraged to work and interact closely with peers and faculty in the SWC and/or CSML throughout their PhD, providing a uniquely multidisciplinary research environment. Applicants should have a strong analytical and quantitative background, a keen interest in neuroscience, machine learning or both, and a relevant first degree, for example in Computer Science, Engineering, Mathematics, Neuroscience, Physics, Psychology or Statistics. Full funding is available regardless of nationality and current residence. The Unit also welcomes applicants who have secured or are seeking funding from other sources. Applications should be submitted via an online portal, accessible from http://www.gatsby.ucl.ac.uk/teaching/phd. Only applications complete by the deadline are guaranteed full consideration; late applications will be entertained only if places remain unfilled. Further details of research interests are available from http://www.gatsby.ucl.ac.uk/research.html and the individual faculty webpages at http://www.gatsby.ucl.ac.uk/members.html. Questions should be directed to admissions at gatsby.ucl.ac.uk. -- Maneesh Sahani, Ph.D. Professor of Theoretical Neuroscience and Machine Learning, Director, Gatsby Computational Neuroscience Unit UCL, 25 Howland Street, London W1T 4JG From pierre-yves.oudeyer at inria.fr Wed Oct 10 08:23:49 2018 From: pierre-yves.oudeyer at inria.fr (Pierre-Yves Oudeyer) Date: Wed, 10 Oct 2018 14:23:49 +0200 Subject: Connectionists: [publication and call for dialog] IEEE CIS Newsletter on Cognitive and Developmental Systems Message-ID: <467B0365-F2F9-4AAD-AC1F-2D83380226E5@inria.fr> Dear colleagues, we are happy to announce the release of the latest issue of the IEEE CIS Newsletter on Cognitive and Developmental Systems (open access). This is a biannual newsletter addressing the sciences of developmental and cognitive processes in natural and artificial organisms, from humans to robots, at the crossroads of cognitive science, developmental psychology, artificial intelligence, machine learning and neuroscience. It is available at: https://goo.gl/NAwBfD Featuring dialog: === "Curiosity as Driver of Extreme Specialization in Humans" == Dialog initiated by Celeste Kidd with responses from: Elizabeth Bonawitz, Maya Zhe Wang, Brian Sweis, Benjamin Hayden, Susan Engel, Abigail Hsiung, Shabnam Hakimi, Alison Adcock, Moritz Daum, Arjun Shankar, Tobias Hauser, Goren Gordon and Perry Zurn == Topic: Curiosity-driven learning is probably one of the most fundamental mechanisms in human learning, and yet it is also probably one of the least understood. Broadly construed as spontaneous exploration and engagement with activities or material without any extrinsic goal (as opposed to searching for information useful for an extrinsic goal), many mysteries remain to be uncovered. What are the causal links between curiosity and learning? How does prior knowledge about a topic or an activity relates to curiosity about this topic? What is the role of curiosity in life-span development? Can human curiosity explain the apparently unique tendency of humans for extreme specialization? Reversely, how do different forms of curiosity (diversive or specific) evolve as children grow up and become adults? While early computational models of curiosity propose theoretical approaches to understand their cognitive mechanisms, how can we understand the affective/ emotional dimensions of curiosity? And how has the linguistic concept of ?curiosity? evolved in occidental culture? Call for new dialog: === ? Leveraging Adaptive Games to Learn How to Help Children Learn Effectively" == Dialog initiated by George Kachergis == Topic: How can one achieve efficiently ?translational educational sciences? and get these principles used in real-world large-scale educational technologies? In this dialog, Georges Kachergis highlights challenges related to collaborations between cognitive scientists and game developers, how to deploy real world experiments, and how to enable scientific understanding when many variables cannot easily be controlled? Those of you interested in reacting to this dialog initiation are welcome to submit a response by December 15th, 2018. The length of each response must be between 600 and 800 words including references (contact pierre-yves. oudeyer at inria.fr). Let us remind you that all issues of the newsletter are all open-access and available at: https://goo.gl/ZjjZNz I wish you a stimulating reading! Best regards, Pierre-Yves Oudeyer, Editor of the IEEE CIS Newsletter on Cognitive and Developmental Systems Research director, Inria Head of Flowers project-team Inria and Ensta ParisTech, France http://www.pyoudeyer.com Twitter: https://twitter.com/pyoudeyer and Fabien Benureau, Editorial Assistant Cognitive NeuroRobotics Unit, Okinawa Institute of Science and Technology 1919-1 Tancha, Onna, Okinawa Japan Email: fabien.benureau [at] oist [dot] jp -------------- next part -------------- An HTML attachment was scrubbed... URL: From tomas.hromadka at gmail.com Wed Oct 10 11:30:08 2018 From: tomas.hromadka at gmail.com (Tomas Hromadka) Date: Wed, 10 Oct 2018 17:30:08 +0200 Subject: Connectionists: COSYNE 2019: Abstract submission is now open; Call for workshop proposals; Cosyne Mentoring Forum Message-ID: ==================================================== Computational and Systems Neuroscience 2019 (Cosyne) MAIN MEETING 28 February - 03 March 2019 Lisbon, Portugal WORKSHOPS 04 March - 05 March 2019 Cascais, Portugal www.cosyne.org ==================================================== IMPORTANT DATES Abstract submission is now open Workshop proposal deadline: 31 October 2018 Cosyne registration opens: 11 November 2018 Abstract submission deadline: 15 November 2018 ---------------------------------------------------- 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 is 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 see below or 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. This year 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 Cosyne.org -> Abstracts. COSYNE SPEAKERS Bruno Averbeck (NIMH) Gwyneth Card (Janelia) Kathleen Cullen (John Hopkins) Kenji Doya (OIST) Ken Harris (UCL) Sonja Hofer (Sainsbury Wellcome Centre) Yann LeCun (NYU) Edvard Moser (NTNU) Yiota Poirazi (IMBB-FORTH) Maneesh Sahani (Gatsby-UCL) Eric Shea-Brown (U Washington) Sara Solla (Northwestern) Karel Svoboda (Janelia) Ilana Witten (Princeton) ORGANIZING COMMITTEE General Chairs: Linda Wilbrecht (Berkeley) and Brent Doiron (U Pittsburgh) Program Chairs: Eugenia Chiappe (Champalimaud) and Christian Machens (Champalimaud) Workshop Chairs: Catherine Hartley (NYU) and Ralf Haefner (U Rochester) Undergraduate Travel Chairs: Angela Langdon (Princeton) and Robert Wilson (U Arizona) Publicity Chair: Il Memming Park (Stony Brook) Development Chair: Michael Long (NYU) EXECUTIVE COMMITTEE Stephanie Palmer (U Chicago) Zachary Mainen (Champalimaud) Alexandre Pouget (U Geneva) Anthony Zador (CSHL) CONTACT meeting [at] cosyne.org ---------------------------------------------------- CALL FOR WORKSHOP PROPOSALS ---------------------------------------------------- A series of workshops will be held after the main Cosyne meeting. The goal is to provide an informal forum for the discussion of important research questions and challenges. Controversial issues, open problems, comparisons of competing approaches, and alternative viewpoints are encouraged. The overarching goal of all workshops should be the integration of empirical and theoretical approaches, in an environment that fosters collegial discussion and debate. Preference will be given to proposals that differ substantially in content, scope, and/or approach from workshops of recent years (examples available at Cosyne.org -> Workshops). Relevant topics include, but are not limited to: sensory processing; motor planning and control; functional neural circuits; motivation, reward and decision making; learning and memory; adaptation and plasticity; neural coding; neural circuitry and network models; and methods in computational or systems neuroscience. In order to foster discussion within Workshops and reduce overlap between workshops, organizers should inform invited speakers that a single person should not speak in more than one of the Workshops taking place on the same day. WORKSHOP DETAILS - There will be 4-8 workshops/day, running in parallel. - Each workshop is expected to draw between 15 and 80 people. - The workshops will be split into morning (08.00-11.00a) and afternoon (04.30-07.30p) sessions. - Workshops will be held at Cascais, a coastal village ~34 km west of Lisbon. Buses from the main conference will be provided. SUBMISSION INSTRUCTIONS Submission instructions for workshop proposals are available at Cosyne.org -> Workshops. Proposals should include: - Name(s) and email address(es) of the organizers (no more than 2 organizers per session, please). The first author on the list becomes the contact author for the proposal. - A title. - A brief description of 1) what the workshop will address and accomplish, 2) why the topic is of interest, 3) who is the targeted group of participants. - Names, affiliations, and expected topics of talks of potential invitees, and a list of confirmed speakers. Preference will be given to workshops with the most confirmed speakers. - A brief summary of relevant prior experiences and publications of the organizers (about half a page total). - Proposed workshop length (1 or 2 days). Most workshops will be limited to a single day. If you think your workshop needs two days, please explain why. Workshop organizer responsibilities include coordinating workshop participation and content, scheduling all speakers and submitting a final schedule for the workshop program, and moderating the discussion. Organizers can be speakers but need not speak depending on scheduling constraints. SUGGESTIONS Experience has shown that the best discussions during a workshop are those that arise spontaneously. A good way to foster these is to have short talks and long question periods (e.g. 30+15 minutes), and have plenty of breaks. We recommend fewer than 10 talks. When preparing workshop proposals, the organizers are encouraged to: - address timeliness of workshop in the proposal: what new insights have been generated (new papers, data, techniques, whatever) over the past few years that make now the right time for discussing them and for presenting them to the wider community? - directly describe how speakers address the central topic, e.g. which are the big question(s), which speakers represent different viewpoints on the same question, which experimentalist addresses the theories addressed by which theoretician (and vice versa); - address controversies and bring together speakers from different ?camps? in the same field, or from different fields that---according to the organizers---should talk more to each other for whatever reason; WORKSHOP COSTS Detailed registration costs, etc., will be available at www.cosyne.org. Please note: Cosyne does NOT provide travel funding for workshop speakers. All workshop speakers are expected to pay for workshop registration fees. Participants are encouraged to register early, in order to qualify for discounted registration rates. One complimentary (free) organizer registration is provided per workshop. For workshops with 2 organizers, the free registration can be given to one of the organizers or split evenly between them. COSYNE 2019 WORKSHOP CHAIRS Catherine Hartley (NYU) and Ralf Haefner (University of Rochester) email: workshops [at] cosyne.org ---------------------------------------------------- COSYNE MENTORING FORUM ---------------------------------------------------- Cosyne Mentoring Forum provides a platform for discussions among Cosyne participants, particularly for help with composing abstracts for the meeting and getting feedback before submission. The forum is intended to be a place to connect with other computational and systems neuroscientists. Forum members are encouraged to share advice on everything from writing a great Cosyne abstract to navigating a job search. See Cosyne.org -> Mailing lists for details on how to subscribe and post to the forum. ---------------------------------------------------- OTHER 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 p.andras at keele.ac.uk Wed Oct 10 14:01:14 2018 From: p.andras at keele.ac.uk (Peter Andras) Date: Wed, 10 Oct 2018 19:01:14 +0100 Subject: Connectionists: Assistant Professor positions at Keele University In-Reply-To: References: Message-ID: <324601d460c3$3c637ff0$b52a7fd0$@keele.ac.uk> Two Assistant Professor (UK Lecturer) positions in Computer Science Keele University - Faculty of Natural Sciences - School of Computing and Mathematics Closing date for applications: 21st October 2018 Keele University is renowned for its exciting approach to higher education, innovative research, beautiful campus, strong community spirit and excellent student experience. With a turnover in excess of ?150 million, over 10,000 students and a total staff of approximately 2000, the University provides high quality teaching across a wide range of academic and vocational subjects and promotes world-class research. The University hosts the largest UK Smart Energy Network Demonstrator (SEND) with an associated Centre for Doctoral Training based in the School of Computing and Mathematics. Applications are welcome from dynamic and enthusiastic individuals committed to high quality teaching and research in any relevant field of Computer Science (e.g. software engineering, evolutionary systems, security, human-computer interaction, biological computation, machine learning, formal methods, distributed systems, smart energy, high-performance computing, artificial intelligence applications ? but not restricted to these particular fields). Applicants will have interests that complement our existing research strengths while broadening the scope of our teaching expertise. The Assistant Professor (UK Lecturer) posts are part of continued growth and expansion of Computer Science at Keele, which presents many new opportunities for the development of synergies in both teaching and research. Candidates will be expected to develop an active research programme that both complements and extends our existing research profile in Computer Science. Candidates are also expected to develop research collaborations with colleagues at Keele and elsewhere in strategic research areas of the University, such as smart energy, AI, big data or digital health. Details of the research carried out in Computer Science at Keele can be found at: http://www.keele.ac.uk/scm/research/compsci/ The successful candidates will have a PhD in an appropriate area of Computer Science (or be very close to completion of his/her PhD) and will have a strong commitment to delivering high quality undergraduate teaching, including supervision of undergraduate and postgraduate research projects and the development and delivery of new modules. The post-holders will have the skills, enthusiasm and flexibility for teaching across a wide range of computer science topics and will also contribute to recruitment activities and administrative duties within our Computer Science programmes. Informal enquires can be made to Professor Peter Andras on 01782 733412 or p.andras at keele.ac.uk Keele University is committed to the principles of the Athena SWAN charter, and values equality and diversity across our workforce. We strive to ensure that our workforce is representative of broader society, and therefore, we would actively welcome applications from women for this role. Keele University values equality and diversity across our workforce and to ensuring our staff community is reflective of the diversity of our student population. In support of these commitments the University welcomes applications from individuals of Black, Asian and ethnic minority backgrounds for all roles. For full post details please visit: www.keele.ac.uk/vacancies Keele University employees wishing to apply should login to Employee Self Service and click on the 'View current vacancies' link. Closing date for applications: 21st October 2018 Interviews will be held on: 16th November 2018 Post reference: KU00000898 -------------- next part -------------- An HTML attachment was scrubbed... URL: From p.andras at keele.ac.uk Wed Oct 10 14:00:13 2018 From: p.andras at keele.ac.uk (Peter Andras) Date: Wed, 10 Oct 2018 19:00:13 +0100 Subject: Connectionists: Advanced Research Fellowships - Artificial Intelligence In-Reply-To: <321501d460c1$17842d80$468c8880$@keele.ac.uk> References: <31f501d460c0$3eccbf20$bc663d60$@keele.ac.uk> <320701d460c0$b1ce1f50$156a5df0$@keele.ac.uk> <321501d460c1$17842d80$468c8880$@keele.ac.uk> Message-ID: <323f01d460c3$181f9840$485ec8c0$@keele.ac.uk> Industrial Strategy Advanced Research Fellowships Special area of interest: Artificial Intelligence and industrial / medical applications. Keele University Closes: 30th October 2018 Job Ref: KU00000892 Salary: Grade 8 ?42,036-?50,132/Grade 9 ?51,630-?59,828 We?re Keele and we?re different. Founded over 60 years ago to meet the challenges of a rapidly changing world, our mission today is as relevant as it was then. A key part of our mission is the delivery of research with the highest impact. The University and its Science & Innovation Park play a critical economic anchor role across and beyond the Midlands area of the UK. In the last 2 years we have invested over ?40 million in building our capacity to work collaboratively with business, industry and a wider set of partners. As part of our future plans for continued investment, we are now seeking to recruit two Industrial Strategy Advanced Research Fellows to the University. Applications are welcomed from individuals with a track record in any discipline, which aligns with the aims and objectives of the UK Government?s Industrial Strategy and the UKRI Funding Councils delivering the strategy (e.g. artificial intelligence). We particularly welcome applications which will further build the University?s reputation for internationally-excellent, world-leading and high impact research in one or more grand challenge areas within the Industrial Strategy. The fellowships are principally research focused positions until July 2021, after which role-holders will transition into substantive academic roles which will include both teaching and research responsibilities. Appointments will be considered at grade 8 (Lecturer scale) or grade 9 (Senior Lecturer scale). The level will be determined by the experience and track-record of individual candidates. Candidates will be expected to demonstrate an established or emerging track record of high quality collaborative research with business, industry and other non-academic partners across the UK, aligned to areas of existing research endeavour at Keele University. An ability to demonstrate a track-record and future desire to collaborate with a wide range of commercial partners, large and small, will be welcomed. Initial applications are invited with a deadline of 30 October 2018, with interviews taking place 3-7 December 2018. Applications will be selected against the person specification for the role, which will include consideration of how the proposed candidate will complement established and emerging areas of research in regard to our interdisciplinary research themes of: sustainable futures, social inclusion and global health. Applicants interested in applying for these jobs in the area of Artificial Intelligence and its industrial / medical applications may contact Professor Peter Andras (p.andras at keele.ac.uk ) for further information about these jobs. Keele University values equality and diversity across our workforce and to ensuring our staff community is reflective of the diversity of our student population. In support of these commitments the University welcomes applications from individuals of Black, Asian and ethnic minority backgrounds for all roles. For full post details please visit: www.keele.ac.uk/vacancies Keele University employees wishing to apply should login to Employee Self Service and click on the 'View current vacancies' link. Closing date for applications: 30th October 2018 Promoting Equality, Valuing Diversity. --- Professor Peter Andras Head of School School of Computing and Mathematics Keele University Keele, Staffordshire ST5 5BG UK Tel. +44-1782-733412 Fax. +44-1782-734268 E-mail: p.andras at keele.ac.uk Web: www.scm.keele.ac.uk/staff/p_andras/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From uwe.aickelin at unimelb.edu.au Thu Oct 11 01:56:02 2018 From: uwe.aickelin at unimelb.edu.au (Uwe Aickelin) Date: Thu, 11 Oct 2018 05:56:02 +0000 Subject: Connectionists: Academic Vacancies at the University of Melbourne Message-ID: Are you looking for an exciting academic career building on a sense of history? Did you know that the School of Computing and Information Systems at The University of Melbourne played the world?s first music on a computer (https://theconversation.com/how-australia-played-the-worlds-first-music-on-a-computer-60381)? Or that we commissioned Australia?s first computer and managed Australia?s first internet connections? But we don?t just have a great history, we are also currently ranked number 1 in Australia and 14th in the world in the latest 2018 QS World University Rankings. And we have ambitious plans for the future ? we are supported by a 10-year strategic $1 Billion investment in people and infrastructure by the University of Melbourne. Do you want to join us? We are hiring academics across a range of areas in Computer Science and Information Systems, including Natural Language Processing, Security and Digital Health. We are also looking for female applicant in any area of Computing and Information Systems. More details are here: http://www.eng.unimelb.edu.au/about/departments/school-of-computing-and-information-systems We review applications on a rolling basis as they come in. Final application deadline is 11 November 2018. Uwe Aickelin -------------------------------------------------------------------------------------------------------------- Professor Uwe Aickelin ? Head of School School of Computing and Information Systems Melbourne School of Engineering University of Melbourne, Victoria 3010, Australia T. +613 8344 3635 E: uwe.aickelin at unimelb.edu.au W: http://aickelin.com [signature_237791722] -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image001.png Type: image/png Size: 2509989 bytes Desc: image001.png URL: From mark.humphries at manchester.ac.uk Thu Oct 11 06:41:26 2018 From: mark.humphries at manchester.ac.uk (Mark Humphries) Date: Thu, 11 Oct 2018 10:41:26 +0000 Subject: Connectionists: Fully-funded PhD in computational neuroscience at Nottingham, deadline 31st October Message-ID: <11479_1539254490_w9BAfS1v012609_7E954275ED82B9468C2C731FB72522F5013E111612@MBXP09.ds.man.ac.uk> A fully funded PhD position in Computational Neuroscience is available with Prof. Mark Humphries at the School of Psychology, University of Nottingham. Deadline: October 31st Full details and to apply: https://www.nottingham.ac.uk/psychology/news/funded-phd-opportunity-prof-mark-humphries.aspx The Humphries? lab interrogates how the joint activity of many neurons encodes the past, present, and future, in order to guide behaviour. We combine simulations of neural circuits with ?neural data science? ? the development and use of machine-learning approaches to systems neuroscience data. We are particularly interested in PhD projects on the following research questions: * ?Mapping the wires from neural activity?. How to use the next generation of imaging techniques that directly record neuron voltages to accurately infer the wiring between neurons. * ?How to write activity into neurons". What features of neural activity should we change with optogenetics in order to test hypotheses about population activity? * ?Dynamic control of the striatum in health and disease?. How the influence of the striatal interneurons is controlled by dopamine, and how that influence goes haywire when dopamine is lost in Parkinson?s disease. For a primer on our research, and our recent publications, visit our lab website: /https://www.humphries-lab.org/ To discuss these or other projects, please contact Prof Mark Humphries (mark.humphries at nottingham.ac.uk). Professor Mark Humphries | MRC Senior non-Clinical Fellow | Chair in Computational Neuroscience humphries-lab.org [0da17e2a-9ed5-496a-b161-9fd4491ce5c7]@markdhumphries Public blog: https://medium.com/the-spike -------------- next part -------------- An HTML attachment was scrubbed... URL: From rsalakhu at cs.toronto.edu Thu Oct 11 16:03:59 2018 From: rsalakhu at cs.toronto.edu (Ruslan Salakhutdinov) Date: Thu, 11 Oct 2018 16:03:59 -0400 (EDT) Subject: Connectionists: ICML 2019 Call for Papers Message-ID: https://icml.cc/Conferences/2019/CallForPapers ICML 2019 Call for Papers NOTE: This year, ICML will adopt a single reviewing cycle, with an abstract submission deadline of Jan. 18, 2019, 3:59 p.m. Pacific, 23:59 Universal time and a full paper submission deadline of Jan. 23, 2019, 3:59 p.m. Pacific, 23:59 Universal time. The 36th International Conference on Machine Learning (ICML 2019) will be held in Long Beach, CA, USA from June 10th to June 15th, 2019. The conference will consist of one day of tutorials (June 10), followed by three days of main conference sessions (June 11-13), followed by two days of workshops (June 14-15). We invite submissions of papers on all topics related to machine learning for the conference proceedings, and proposals for tutorials and workshops. This year, ICML will adopt a single reviewing cycle, with an abstract submission deadline of Jan. 18, 2019, 3:59 p.m. Pacific, 23:59 Universal time and a full paper submission deadline of Jan. 23, 2019, 3:59 p.m. Pacific, 23:59 Universal time. Submissions will open on Jan. 7, 2019, noon pacific time and are managed through CMT: https://cmt3.research.microsoft.com/ICML2019/ Authors should include a full title for their paper, as well as a complete abstract by the abstract submission deadline. Submissions that have placeholder (test, xyz, etc.) titles or abstracts (or none at all) at the abstract submission deadline will be deleted. Authors of these types of submissions will not be allowed to submit a full paper on January 23, 2019. Submitted papers can be up to eight pages long, not including references, and up to twelve pages when references and acknowledgments are included. Any paper exceeding this length will automatically be rejected. Authors have the option of submitting one supplementary manuscript containing further details of their work and a separate file containing code that supports experimental findings; it is entirely up to the reviewers to decide whether they wish to consult this additional material. To foster reproducibility, we highly encourage authors to submit code. Reproducibility of results and easy availability of code will be taken into account in the decision-making process. All submissions must be electronic, anonymized and must closely follow the formatting guidelines in the templates; otherwise they will automatically be rejected. This year, the author list at the submission deadline will be considered final, and no changes in authorship will be permitted for accepted papers. Dual Submission Policy It is not appropriate to submit papers that are identical (or substantially similar) to versions that have been previously published, or accepted for publication, or that have been submitted in parallel to other conferences. Such submissions violate our dual submission policy, and the organizers have the right to reject such submissions, and remove them from the proceedings. There are several exceptions to this rule: * Submission is permitted of a short version of a paper that has been submitted to a journal, but will not be published in that journal on or before June 2019. Authors must declare such dual-submissions either through the CMT submission form, or via email to the program chairs (icml2019pc at gmail.com). It is the authors responsibility to make sure that the journal in question allows dual concurrent submissions to conferences. * Submission is permitted for papers presented or to be presented at conferences or workshops without proceedings (e.g., ICML or NIPS workshops), or with only abstracts published. * Submission is permitted for papers that are available as a technical report (or similar, e.g., in arXiv). In this case we suggest the authors not cite the report, so as to preserve anonymity. Finally, note that previously published papers with substantial overlap written by the authors must be cited in such a way so as to preserve author anonymity. Differences relative to these earlier papers must be explained in the text of the submission. For example, (This work develops [our earlier work], which showed that). Reviewing Criteria Accepted papers must contain significant novel results. Results can be either theoretical or empirical. Results will be judged on the degree to which they have been objectively established and/or their potential for scientific and technological impact. Reproducibility of results and easy availability of code will be taken into account in the decision-making process. Program Chairs: Kamalika Chaudhuri (University of California, San Diego) Ruslan Salakhutdinov (Carnegie Mellon University) General Chair: Eric Xing (Carnegie Mellon University) From li.zhaoping at tuebingen.mpg.de Fri Oct 12 05:26:35 2018 From: li.zhaoping at tuebingen.mpg.de (Zhaoping Li) Date: Fri, 12 Oct 2018 11:26:35 +0200 Subject: Connectionists: Student/postdoc/scientist positions available in computational/experimental sensory and sensorimotor research in Tuebingen Germany Message-ID: Our team is in the University of Tuebingen and in the Max Planck Institute for Biological Cybernetics, and we are recruiting for highly motivated students and postdocs (or scientists) to join us for computational and/or experimental studies in sensory and sensorimotor systems. The positions are available immediately and till they are filled. The research topics include: visual/olfactory attention/orienting, visual perception, sensory coding and decoding, in human and animals (rodents and zebrafish), for more information see_http://www.kyb.tuebingen.mpg.de/research/dep/zl.html _ (still under construction, more details will appear). We have both theoretical and experimental projects, and the experimental projects employ behavioral (e.g., psychophysics, fMRI, EEG, TMS) and/or neuroscience (e.g., electrophysiology, imaging) ?methods. Each team member does not have to be skilled in all of the topics or methods, but should be highly skilled in at least one of them and interested in communicating and/or working with other team members. Please direct your enquiry to Li Zhaoping at_li.zhaoping at tuebingen.mpg.de _ -------------- next part -------------- An HTML attachment was scrubbed... URL: From s.purcell at exeter.ac.uk Fri Oct 12 08:05:06 2018 From: s.purcell at exeter.ac.uk (Purcell, Sarah) Date: Fri, 12 Oct 2018 12:05:06 +0000 Subject: Connectionists: Opportunities to collaborate with the EPSRC Centre for Predictive Modelling in Healthcare Message-ID: Dear Colleagues, I would like to highlight the following opportunities for collaboration with the EPSRC Centre for Predictive Modelling in Healthcare at the University of Exeter, UK: The EPSRC Centre for Predictive Modelling in Healthcare brings together a world-leading team of mathematicians, statisticians and clinicians with a range of industrial partners, people with lived experience of chronic health conditions and other stakeholders to focus on the development of new methods for managing and treating noncommunciable disorders using predictive mathematical and statistical models. Our focus is on 'dynamic' health conditions such as autoimmune disease, cardiac arrhythmias, diabetes and epilepsy. We aim to revolutionise the clinical management of these disorders through better understanding the fundamental mechanisms of these disorders, as well as the development of mathematically-underpinned decision support systems. Visitor programme The Centre runs a lively visitor programme where both short term seminar speakers and longer term visitors can interact with the team. Whether you are an academic, a student, a healthcare professional or involved in healthcare technologies, if you are interested to visit or work with us, please get in touch by completing our visitor contact form. Visiting fellowship We have some funding available to support the visits of interested parties who will contribute to the work of the Centre. Please use the contact form to tell us more about your plans, the problem you would like to solve and who you would like to work with. Requests for funding will be dealt with on an individual basis. For further information or any queries, you can also contact Sarah Purcell (Centre Manager). Best wishes, Sarah Purcell Centre Manager EPSRC Centre for Predictive Modelling in Healthcare University of Exeter Tel: 01392 726447 Web: www.exeter.ac.uk/pmh Twitter: twitter.com/CPMH_UoE -------------- next part -------------- An HTML attachment was scrubbed... URL: From hafner at informatik.hu-berlin.de Sat Oct 13 03:18:41 2018 From: hafner at informatik.hu-berlin.de (Verena V. Hafner) Date: Sat, 13 Oct 2018 09:18:41 +0200 Subject: Connectionists: Junior Professorship in Machine Learning at HU Berlin Message-ID: <06AC6987-F76D-4928-9C75-24BB5B53BC4D@informatik.hu-berlin.de> The Faculty of Mathematics and Natural Sciences, Department of Computer Science, of Humboldt-Universitaet zu Berlin, Germany, invites applications for a *** Junior Professorship in Machine Learning *** (W1 Tenure Track leading to W2) starting as soon as possible. The ideal candidate for this position is an acknowledged expert in foundational and/or applied topics in machine learning. We expect independent teaching, an outstanding research profile, and the (proven) willingness to engage in collaborative and interdisciplinary research projects. We are particularly interested in researchers specializing in topics in the life sciences, geoscience or natural language processing / text mining. We offer numerous possibilities to participate in ongoing and future research initiatives (such as the newly founded Cluster of Excellence ?Science of Intelligence?, www.scienceofintelligence.de), a vibrant research environment and highly engaged and dedicated students. The complete announcement can be found here: German: https://www.personalabteilung.hu-berlin.de/stellenausschreibungen/juniorprofessur-fuer-maschinelles-lernen English: https://www.personalabteilung.hu-berlin.de/stellenausschreibungen/junior-professorship-for-machine-learning201d -- http://adapt.informatik.hu-berlin.de/ From thang.buivn at gmail.com Mon Oct 15 06:07:24 2018 From: thang.buivn at gmail.com (Thang Bui) Date: Mon, 15 Oct 2018 21:07:24 +1100 Subject: Connectionists: CFP: 1st Symposium on Advances in Approximate Bayesian Inference (AABI 2018) Message-ID: We invite researchers in machine learning and statistics to participate in the: 1st Symposium on Advances in Approximate Bayesian Inference Sunday December 2 2018, Montreal, Canada www.approximateinference.org Submission deadline: *19 October 2018* *1. Call for Participation* We invite researchers to submit their recent work on the development, analysis, or application of approximate Bayesian inference. A submission should take the form of an extended abstract of 2-4 pages in PDF format using the PMLR one-column style [ http://approximateinference.org/pmlr/aabi_template.zip ]. For questions and troubleshooting, visit CTAN [ https://ctan.org/tex-archive/macros/latex/contrib/jmlr ]. Author names do not need to be anonymized and references may extend as far as needed beyond the 4-page upper limit. If authors' research has previously appeared in a journal, workshop, or conference (including the NIPS 2018 conference), their symposium submission should extend that previous work. Submissions may include a supplement/appendix, but reviewers are not responsible for reading any supplementary material. All submissions will be reviewed by at least three reviewers from the field. Accepted submissions will be accepted to presentation only. The authors of selected submissions will be invited to publish their paper in a PMLR volume. We aim to keep a general inclusive nature of the symposium for presentations. However, we will only invite the top-rated accepted papers to be published through PMLR. Papers should be submitted by 19 October through easychair [ https://easychair.org/conferences/?conf=aabi2018 ]. Final versions of the symposium submissions are due by 1 December and will be posted on the symposium website. If you have any questions, please contact us at aabisymposium2018 at gmail.com. *2. Symposium Overview* Probabilistic modeling is a useful tool to analyze and understand real-world data. Central to the success of Bayesian modeling is posterior inference, for which approximate inference algorithms are typically needed in most problems of interest. The two pillars of approximate Bayesian inference are variational and Monte Carlo methods. In recent years, there have been numerous advances in both methods, which have enabled Bayesian inference in increasingly challenging scenarios involving complex probabilistic models and large datasets. In this symposium, besides recent advances in approximate inference, we will discuss the impact of Bayesian inference, connecting approximate inference methods with other fields. In particular, we encourage submissions that relate Bayesian inference to the fields of reinforcement learning, causal inference, decision processes, Bayesian compression, or differential privacy, among others. We also encourage submissions that contribute to connecting different approximate inference methods, such as variational inference and Monte Carlo. This symposium can be seen as a continuation of previous workshops at NIPS: + NIPS 2017 Workshop: Advances in Approximate Bayesian Inference + NIPS 2016 Workshop: Advances in Approximate Bayesian Inference + NIPS 2015 Workshop: Advances in Approximate Bayesian Inference + NIPS 2014 Workshop: Advances in Variational Inference *3. Key Dates* Paper submission: *19 October 2018 (11:55pm GMT)* Acceptance notification: 13 November 2018 Final paper submission: 1 December 2018 Symposium organizers: Cheng Zhang (Microsoft Research) Dawen Liang (Netflix) Francisco Ruiz (University of Cambridge / Columbia University) Thang Bui (University of Sydney) Advisory committee: Christian Robert (Universit? Paris Dauphine / University of Warwick) David Blei (Columbia University) Dustin Tran (Google Brain / Columbia University) James McInerney (Spotify) Stephan Mandt (University of California Irvine) -------------- next part -------------- An HTML attachment was scrubbed... URL: From mgalle at gmail.com Mon Oct 15 10:50:36 2018 From: mgalle at gmail.com (=?UTF-8?Q?Matthias_Gall=C3=A9?=) Date: Mon, 15 Oct 2018 16:50:36 +0200 Subject: Connectionists: internships in neural machine translation (Naver Labs + University of Grenoble) Message-ID: Are you current a student and interested in Neural Machine Translation? We have two exciting internships openings in that topic, co-supervised with Laurent Besacier from the University of Grenoble. Naver Labs Europe is the largest AI research centre in France, located in southern France. For more information and application procedure, please visit the links below http://www.europe.naverlabs.com/NAVER-LABS-Europe/Internships/Contextual-Neural-Machine-Translation-of-User-Generated-Contents http://www.europe.naverlabs.com/NAVER-LABS-Europe/Internships/Multiscale-Neural-Machine-Translation -------------- next part -------------- An HTML attachment was scrubbed... URL: From r.pascanu at gmail.com Mon Oct 15 16:38:47 2018 From: r.pascanu at gmail.com (Razvan Pascanu) Date: Mon, 15 Oct 2018 21:38:47 +0100 Subject: Connectionists: Reminder: CfP -- Continual Learning workshop at NIPS 2018 Message-ID: TL;DR: We invite you to our workshop on Continual Learning at this year?s NIPS. Submission deadline for 4-page extended abstracts is October 19th 25th. --------------------- Description: Continual learning (CL) is the ability to learn continually from a stream of experiential data, building on what was learnt previously, while being able to reapply, adapt and generalize it to new situations. CL is a fundamental step towards artificial intelligence, as it allows the learning agent to continually extend its abilities and adapt them to a continuously changing environment, a hallmark of natural intelligence. It also has implications for supervised or unsupervised learning. For example, if a dataset is not randomly shuffled, or the input distribution shifts over time, a learned model might overfit to the most recently seen data, forgetting the rest -- a phenomenon referred to as catastrophic forgetting, which is a core issue CL systems aim to address. Continual learning is characterized in practice by a series of desiderata. A non-complete list of which includes: - Online learning -- learning occurs at every moment, with no fixed tasks or data sets and no clear boundaries between tasks; - Presence of transfer (forward/backward) -- the learning agent should be able to transfer and adapt what it learned from previous experience, data, or tasks to new situations, as well as make use of more recent experience to improve performance on capabilities learned earlier; - Resistance to catastrophic forgetting -- new learning should not destroy performance on previously seen data; - Bounded system size -- the agent?s learning capacity should be fixed, forcing the system to use its resources intelligently, gracefully forgetting what it has learned so as to minimize potential loss of future reward; - No direct access to previous experience -- while the model can remember a limited amount of experience, a continual learning algorithm cannot assume direct access to all of its past experience or the ability to rewind the environment (i.e., t=0 exactly once). In the first (2016) meeting of this workshop, the focus was on defining a complete list of desiderata of what a continual learning (CL) enabled system should be able to do. The focus of the 2018 workshop will be on: 1. how to evaluate CL methods; and 2. how CL compares with related ideas (e.g., life-long learning, never-ending learning, transfer learning, meta-learning) and how advances in these areas could be useful for continual learning. In particular, different desiderata of continual learning seem to be in opposition (e.g., fixed model capacity vs non-catastrophic forgetting vs the ability to generalize and adapt to new situations), which also raises the question of what a successful continual learning system should be able to do. What are the right trade-offs between these different opposing forces? How do we compare existing algorithms in the face of conflicting objectives? What metrics are most useful to report? In some cases, trade-offs will be tightly defined by the way we choose to test the algorithms. What would be the right benchmarks, datasets or tasks for productively advancing this topic? We encourage submission of four-page abstracts describing work in progress or completed work on topics (1) and (2) above, including work from related areas, such as: - Transfer learning - Multi-task learning - Meta learning - Lifelong learning - Few-shot learning Finally, we will also encourage presentation of both novel approaches to CL and implemented systems, which will help concretize the discussion of what CL is and how to evaluate CL systems. Confirmed speakers: - Marc?Aurelio Ranzato (Facebook AI Research) - John Schulman (OpenAI) - Raia Hadsell (DeepMind) - Chelsea Finn (Berkeley & Google Brain) - Yarin Gal (Oxford) - Juergen Schmidhuber (IDSIA) Dates: - Submission deadline: Friday October 19 Thursday October 25th - Workshop: Friday December 7th Submission format: 4 page extended abstracts, which can include previously published work. More details at the website: https://sites.google.com/corp/view/continual2018/ Submissions will be managed through EasyChair here: https://easychair.org/conferences/?conf=cl20180 We look forward to seeing you in December! Razvan Pascanu, Yee Whye Teh, Mark Ring and Marc Pickett. -------------- next part -------------- An HTML attachment was scrubbed... URL: From t.hauser at ucl.ac.uk Mon Oct 15 09:54:08 2018 From: t.hauser at ucl.ac.uk (Hauser, Tobias) Date: Mon, 15 Oct 2018 13:54:08 +0000 Subject: Connectionists: PostDoc in Computational Psychiatry at UCL Message-ID: The Developmental Computational Psychiatry lab (www.devcompsy.org) at the Max Planck UCL Centre for Computational Psychiatry & Ageing Research is hiring. Tobias Hauser is looking for a postdoc to enrich his your and growing group. We looking for someone who has a strong background in decision neuroscience or psychiatry (primarily OCD), or both. The postdoc will be joining a young and interdisciplinary lab that works at the intersection of computational neuroscience, psychiatry, pharmacology and cognitive development. This means that the position offers the freedom to pursue own projects under Tobias' supervision. The position is for two years initially. It is based at the Max Planck UCL Centre for Computational Psychiatry & Ageing Research and the Wellcome Centre for Human Neuroimaging at UCL. This is a unique environment with access to the cutting-edge neuroimaging facilities (3 & 7T fMRI, MEG, etc.) and embedded in the very collaborative and dynamic UCL neuroscience community. All the details about the position (application deadline: 25/10/2018) can be found here: https://atsv7.wcn.co.uk/search_engine/jobs.cgi?amNvZGU9MTc1MjY3NiZ2dF90ZW1wbGF0ZT05NjUmb3duZXI9NTA0MTE3OCZvd25lcnR5cGU9ZmFpciZicmFuZF9pZD0wJmpvYl9yZWZfY29kZT0xNzUyNjc2JnBvc3RpbmdfY29kZT0yMjQ&jcode=1752676&vt_template=965&owner=5041178&ownertype=fair&brand_id=0&job_ref_code=1752676&posting_code=224 Potential applicants are encouraged to get in touch with Tobias to discuss potential projects. Best Tobias --- Dr Tobias U. Hauser Sir Henry Dale Fellow, Principal Investigator Developmental Computational Psychiatry lab Max Planck UCL Centre for Computational Psychiatry & Ageing Research Wellcome Centre for Human Neuroimaging University College London 10-12 Russell Square London WC1B 5EH +44 207 679 5264 (internal: 45264) t.hauser at ucl.ac.uk www.tobiasuhauser.com www.devcompsy.org -------------- next part -------------- An HTML attachment was scrubbed... URL: From iceis at insticc.info Tue Oct 16 04:52:09 2018 From: iceis at insticc.info (iceis at insticc.info) Date: 16 Oct 2018 09:52:09 +0100 Subject: Connectionists: CFP ICEIS 2019 - 21st Int.l Conf. on Enterprise Information Systems (Heraklion, Crete/Greece) Message-ID: <20181016085206.1.D9DD77CEBED4B41F@insticc.info> SUBMISSION DEADLINE 21st International Conference on Enterprise Information Systems Submission Deadline: December 10, 2018 http://www.iceis.org/ May 3 - 5, 2019 Heraklion, Crete, Greece. ICEIS is organized in 6 major tracks: - Databases and Information Systems Integration - Artificial Intelligence and Decision Support Systems - Information Systems Analysis and Specification - Software Agents and Internet Computing - Human-Computer Interaction - Enterprise Architecture In Cooperation with: ACM SIGCAS, EDSO, Cluster Habitat Sustent?vel, OSGP Alliance and Siemens.
Proceedings will be submitted for indexation by: DBLP, Thomson Reuters, EI, SCOPUS and Semantic Scholar.
A short list of presented papers will be selected so that revised and extended versions of these papers will be published by Springer. All papers presented at the congress venue will also be available at the SCITEPRESS Digital Library (http://www.scitepress.org/DigitalLibrary/). Should you have any question please don't hesitate contacting me. Kind regards, ICEIS Secretariat Address: Av. D. Manuel I, 27A, 2? esq. 2910-595 Setubal, Portugal Tel: +351 265 520 184 Fax: +351 265 520 186 Web: http://www.iceis.org/ e-mail: iceis.secretariat at insticc.org From complexis at insticc.info Tue Oct 16 04:51:58 2018 From: complexis at insticc.info (complexis at insticc.info) Date: 16 Oct 2018 09:51:58 +0100 Subject: Connectionists: CFP COMPLEXIS 2019 - 4th Int.l Conf. on Complexity, Future Information Systems and Risk (Heraklion, Crete/Greece) Message-ID: <20181016085155.1.91FCE4749F3C0C2E@insticc.info> SUBMISSION DEADLINE 4th International Conference on Complexity, Future Information Systems and Risk Submission Deadline: December 10, 2018 http://www.complexis.org/ May 2 - 4, 2019 Heraklion, Crete, Greece. COMPLEXIS is organized in 7 major tracks: - Complexity in Informatics, Automation and Networking - Complexity in Biology and Biomedical Engineering - Complexity in Social Sciences - Complexity in Computational Intelligence and Future Information Systems - Complexity in EDA, Embedded Systems, and Computer Architecture - Network Complexity - Complexity in Risk and Predictive Modeling In Cooperation with: ACM SIGCAS, EDSO, Cluster Habitat Sustent?vel, OSGP Alliance and Siemens.
Proceedings will be submitted for indexation by: DBLP, Thomson Reuters, EI, SCOPUS and Semantic Scholar.
With the presence of internationally distinguished keynote speakers: Francisco Herrera, University of Granada, Spain A short list of presented papers will be selected so that revised and extended versions of these papers will be published by Springer. All papers presented at the congress venue will also be available at the SCITEPRESS Digital Library (http://www.scitepress.org/DigitalLibrary/). Should you have any question please don't hesitate contacting me. Kind regards, COMPLEXIS Secretariat Address: Av. D. Manuel I, 27A, 2? esq. 2910-595 Setubal, Portugal Tel: +351 265 520 184 Fax: +351 265 520 186 Web: http://www.complexis.org/ e-mail: complexis.secretariat at insticc.org From s.purcell at exeter.ac.uk Tue Oct 16 12:34:34 2018 From: s.purcell at exeter.ac.uk (Purcell, Sarah) Date: Tue, 16 Oct 2018 16:34:34 +0000 Subject: Connectionists: Funded Mathematics PhD at the University of Exeter - Designing the dynamics of coupled oscillators Message-ID: Designing the dynamics of coupled oscillators Mathematics PhD (funded) University of Exeter Supervisors: Dr Christian Bick - University of Exeter Dr Kyle Wedgwood - University of Exeter The University of Exeter's College of Engineering, Mathematics and Physical Sciences is inviting applications for a fully-funded PhD studentship to commence in January 2019 or as soon as possible thereafter. For eligible students the studentship will cover tuition fees (UK/EU/International) in full plus an annual tax-free stipend of at least ?14,777 for 3.5 years full-time, or pro rata for part-time study. The student would be based in the Department of Mathematics in the College of Engineering, Mathematics and Physical Sciences in Exeter. Networks of interacting oscillatory units are abundant in nature and technology. Their function and dynamics governs crucial aspects of our lives, ranging from the stability of power grids to the dynamics of the human brain. The dynamics of oscillator networks depends on (1) which oscillators interact with which other oscillator and (2) how oscillators interact with one another. This project will contribute to the question how the interplay between these two factors shape the network dynamics. The main aim of this PhD project is to develop theoretical and numerical approaches how oscillator networks can be designed to have specific interactions. This will allow to generate networks that exhibit a range of synchronized and locally synchronized dynamics. Moreover, the supervisor is currently collaborating with the experimental group of Istvan Z Kiss in St Louis (USA) who are working on electrochemical oscillators. Hence, there may be an opportunity to help implement the theoretical results in real-world experimental systems. Entry requirements Applicants for this studentship must have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK, in an appropriate area of science or technology. If English is not your first language you will need to have achieved at least 6.5 in IELTS and no less than 6.0 in any section by the start of the project. Alternative tests may be acceptable (see http://www.exeter.ac.uk/postgraduate/apply/english/). For more information, please contact Dr. Christian Bick (C.Bick at exeter.ac.uk) or Dr. Kyle Wedgwood (K.C.A.Wedgwood at exeter.ac.uk) or see http://www.exeter.ac.uk/studying/funding/award/?id=3301 -------------- next part -------------- An HTML attachment was scrubbed... URL: From ted.carnevale at yale.edu Tue Oct 16 17:33:06 2018 From: ted.carnevale at yale.edu (Ted Carnevale) Date: Tue, 16 Oct 2018 17:33:06 -0400 Subject: Connectionists: NEURON course at SFN 2018 meeting Message-ID: A few seats remain open for the NEURON course that we will be presenting at the SFN 2018 meeting in San Diego. However, the registration deadline is Friday, October 19--just three days from today, so you'll have to act quickly if you are interested in learning things like * why you should be using NEURON to model biological neurons and neural circuits * how to get started building models with NEURON's GUI and/or Python * advanced tips for getting the most out of using Python as NEURON's interpreter, and using NEURON's GUI for interactive modeling and debugging of models implemented with Python * using the Import3d tool to convert Neurolucida, Eutectic, and SWC morphometric data files to NEURON models * how to add new ion channels and other biophysical mechanisms to NEURON For the course description and registrion form, see https://neuron.yale.edu/neuron/static/courses/sd2018/sd2018.html --Ted This message was composed in plain text and may contain plain text formatting of source code, tables, and lists. Reading it in a client that ignores "excess" whitespace characters or line breaks may destroy that formatting, making this message unreadable. Outlook does that by default; learn how to disable the "Auto Remove Line Breaks" ""feature"" at support.microsoft.com From erishabh at gmail.com Tue Oct 16 18:11:33 2018 From: erishabh at gmail.com (Rishabh Mehrotra) Date: Wed, 17 Oct 2018 03:41:33 +0530 Subject: Connectionists: Research Internships at Spotify Research, London Message-ID: *TL;DR:* Research internships at Spotify Research in London. Deadline: 3rd December. Contact: rishabhm at spotify.com or mounial at spotify.com for details. We are looking for Research Scientist Interns for Spotify?s research lab based in London to work on a number of interesting problems in machine learning, deep learning, recommendations, user modeling/engagement, and large scale experimentation. We are part of a high impact team that is building the next generation technologies aimed at making every user interaction with Spotify amazing through personalization and discovery. We?re looking for talented research interns who have applied experience in the field of Machine Learning, Machine Intelligence, User Behavioral Analysis, IR, NLP, and more broadly, AI. The User Engagement team works on some of Spotify?s key features ? personalized playlists such as Discover Weekly and Daily Mix, the Home view, and Search. Our projects are intended to take on some of technology?s greatest challenges and make impact on millions of users. Some of the challenges our team is working on include developing terascale solutions for understanding and interpreting user interaction signals, understanding user success with short term & long term metrics, developing algorithmically curated playlists and other challenges in machine learning and user understanding. *Who you are* - You are currently enrolled in a PhD programme in Computer Science, Data Science, or related areas with a strong computational focus. - You will have a strong knowledge of data mining, machine learning or evaluation with experience in machine learning, deep learning, optimization techniques, information retrieval and/or natural language understanding. - You have publications in communities such as WWW, SIGIR, WSDM, RecSys, CHI, KDD, AAAI, ACL, NIPS, ICML, UbiComp, or related, in the following topics: - user understanding: music cognition, metrics and evaluation, large scale experimentation - matching: information retrieval, recommendation, machine learning - You possess solid hands-on skills in sourcing, cleaning, manipulating, analyzing, visualizing and modeling of large scale data. *Application Deadline:* 3rd December 2018 *Applications: * https://www.spotifyjobs.com/job/research-science-phd-summer-internship-uk-oqqy8fwg/ https://www.linkedin.com/jobs/view/914747471/ *Contact:* Feel free to get in touch with Mounia Lalmas (mounial at spotify.com) or Rishabh Mehrotra (rishabhm at spotify.com) for details/questions. -- Rishabh. Web: www.rishabhmehrotra.com Github: https://github.com/rishabhmehrotra/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From francisco.pereira at gmail.com Wed Oct 17 15:47:55 2018 From: francisco.pereira at gmail.com (Francisco Pereira) Date: Wed, 17 Oct 2018 15:47:55 -0400 Subject: Connectionists: Data Science position available at NIMH, Bethesda, MD In-Reply-To: <2E0A50D6-D44F-4569-BD27-E103D757EF6F@nih.gov> References: <2E0A50D6-D44F-4569-BD27-E103D757EF6F@nih.gov> Message-ID: Posted on behalf of Adam Thomas at NIMH, please contact DATASCI-JOBSEARCH at mail.nih.gov directly. Francisco Subject: [FSL] Data Science Job Avail @NIMH, Bethesda, MD For links and better formatting see: https://github.com/nih-fmrif/dataSci_job_ad/ The National Institute of Mental Health (NIMH) is the largest funder of research on mental disorders in the world, with a current budget of over $1.4B. Our mission is to to transform the understanding and treatment of mental illnesses through basic and clinical research, paving the way for prevention, recovery, and cure. The NIH is a highly rated employer at glassdoor.com with very competitive salary and benefits packages. The Data Science and Sharing Team (DSST) is a new group created to develop and support data sharing and other data-intensive scientific projects within the NIMH Intramural Research Program (IRP). Working closely with the NIH Data Science Community the goal of the DSST is to make the NIMH IRP a leader in open science and data sharing practices. We are looking for a talented Data Scientist to add to our team. Typical compensation for NIH staff scientists is available at Glassdoor. What you?ll do? BUILD You will work with a team of researchers and developers to build and deploy neuroimaging data processing pipelines for investigators within the NIMH IRP. You will collaborate with and contribute to other projects throughout the world that are building standards and tools for open and reproducible neuroscience (e.g. NiPy, BIDS, Jupyter, etc). You'll have the resources of the NIH HPC Cluster at your disposal as well as additional help from the AWS cloud. Everything we make is open source and freely distributed. TEACH You will work to bolster data science skills within the NIMH IRP by teaching courses to scientists on best data practices (e.g. Data Carpentry and ReproNim) as well as interfacing with specific neuroimaging repositories (e.g. The Human Connectome Project, OpenfMRI, UK Biobank, The NIMH Data Archive). SCIENCE Our team is committed to the NIMH Mission of understanding and treating mental illness and we believe open, clean data (and lots of it) is crucial to realizing that mission. You will work closely with (and sit next to) the Machine Learning Team who are building the models needed to understand complex brain function. Who you are? EXPERIENCED You should be very comfortable on the command line and with quickly manipulating large datasets with lots of files. You should also have experience coding in modern languages currently used in data-intensive, scientific computing such as Python or R. Alternatively, you may be more proficient in front-end development and visualization with Javascript. Experience with distributed, high-performance computing tools such as Docker/Singularity and batch processing systems such as SLURM is a plus. PROVEN Ideally we would like to see a recent degree (BS, MS, or PhD) in a STEM field, but if you can prove you have an equivalent amount of expertise with your publications, projects, or github/kaggle ranking, we?re all ears. We are also interviewing students and part-time staff if you?re still working on your degree. DRIVEN We're looking for someone who's motivated to develop and research their own ideas. You should be willing and able to argue for the priorities you think the team should focus on, and work together to achieve those goals. You should be a self-learner and a self-starter. Please provide some examples of things you have worked on independently. How to apply? Email your resume, a cover letter, and a code sample that demonstrates you are all three of the above to: DATASCI-JOBSEARCH at mail.nih.gov The National Institutes of Health is an equal opportunity employer. -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image001.png Type: image/png Size: 16352 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image002.png Type: image/png Size: 71426 bytes Desc: not available URL: From richard.jiang at northumbria.ac.uk Wed Oct 17 17:18:24 2018 From: richard.jiang at northumbria.ac.uk (Richard Jiang) Date: Wed, 17 Oct 2018 21:18:24 +0000 Subject: Connectionists: Call for Book Chapters on Deep Biometrics In-Reply-To: References: , Message-ID: Dear Colleagues, We would like to invite you to contribute a chapter for the upcoming volume entitled "Deep Biometrics" to be published by Springer, the largest global scientific, technical, and medical ebook publisher. The volume will be available both in print and in ebook format by late 2018/early 2019 on SpringerLink, one of the leading science portals that includes more than 8 million documents, an ebook collection with more than 160,000 titles, journal archives digitized back to the first issues in the 1840s, and more than 30,000 protocols and 290 reference works. Below is a short description of the volume: Recent development in machine learning, particularly deep learning, has brought out drastic impact on Biometrics, which is a classic topic to utilize Machine Learning for biometric identification. Particularly, Deep Learning can benefit from the training with large unlabelled datasets via semi-supervised or unsupervised learning. This book aims to highlight recent research advances in biometrics using semi-supervised and unsupervised new methods such as Deep Neural Networks, Deep Stacked Autoencoder, Convolutional Neural Networks, Generative Adversary Networks, Ensemble Methods, and so on, and exploit these novel methods in the emerging new areas such as privacy and security issues, cancellable biometrics and soft biometrics, smart cities, big biometric data, biometric banking, medical biometrics, and healthcare biometrics, etc.. The goal of this volume is to summarize the recent advances in using Deep Learning in the area of biometric security and privacy. Topics of interest include: (but not limited to) * Deep Learned Biometric Features * Convolutional Neural networks * Deep Stacked Autoencoder * Deep Face Detection * Deep Gait Recognition * Biometrics in Cybersecurity * Biometrics in Cognitive Robot * Healthcare Biometrics * Medical Biometrics * Biometrics in Social Computing * Biometric Block Chain * Privacy and Security Issues * Iris, Fingerprints, DNA, Palmprints * Gait, EEG, Heart rates * Multimodal Fusion * Soft Biometrics * Cancellable Biometrics * Big data issues in Biometrics * Biometrics for Internet of things Each contributed chapter is expected to present a novel research study, a comparative study, or a survey of the literature. Note that there will be no publication fees for accepted chapters. Important Dates: Submission of abstracts Nov 15, 2018 Notification of initial editorial decisions Nov 20, 2018 Submission of full-length chapters Dec 15, 2018 Notification of final editorial decisions Jan 15, 2019 Submission of revised chapters Feb 15, 2019 All submissions should be done via EasyChair: https://easychair.org/conferences/?conf=deepbio2019 Original artwork and a signed copyright release form will be required for all accepted chapters. For author instructions, please visit: http://www.springer.com/authors/book+authors?SGWID=0-154102-12-417900-0 Please feel free to contact us via email (perceptualscience at outlook.com, or any editors below) regarding your chapter ideas. Editorial Board * Dr Richard Jiang Computer and Information Sciences, Northumbria University, United Kingdom Email: richard.jiang at unn.ac.uk * Dr Weizhi Meng Applied Mathematics & Computer Science Technical University of Denmark, Denmark Email: weme at dtu.dk * Professor Chang-Tsun Li School of Computing and Mathematics, Charles Sturt University, Australia Email: chli at csu.edu.au * Professor Christophe Rosenberger Computer Security ENSICAEN - GREYC, France Email: christophe.rosenberger at ensicaen.fr Contact: All questions about submissions can be emailed to perceptualscience at outlook.com or any editor in the board. Many thanks! Kind Regards, Editors of the Book This message is intended solely for the addressee and may contain confidential and/or legally privileged information. Any use, disclosure or reproduction without the sender's explicit consent is unauthorised and may be unlawful. If you have received this message in error, please notify Northumbria University immediately and permanently delete it. Any views or opinions expressed in this message are solely those of the author and do not necessarily represent those of the University. Northumbria University email is provided by Microsoft Office365 and is hosted within the EEA, although some information may be replicated globally for backup purposes. The University cannot guarantee that this message or any attachment is virus free or has not been intercepted and/or amended. -------------- next part -------------- An HTML attachment was scrubbed... URL: From piratepeel at gmail.com Thu Oct 18 08:56:57 2018 From: piratepeel at gmail.com (Leto Peel) Date: Thu, 18 Oct 2018 14:56:57 +0200 Subject: Connectionists: Winter Workshop on Complex Systems 2019 - Call for applications Message-ID: The next Winter Workshop on Complex Systems will be held in Zakopane (Poland) from 4th to 8th February 2019. The event is tailored for PhD students and young scientists working in the broad area of complex systems. The aim of the workshop is to encourage new interdisciplinary collaborations. The call for participation in the 2019 edition is now open and the application deadline is 31st of October. All the details are available at: http://wwcs2019.org The cost of the workshop is just 100 euros, which includes accommodation, food, transport from Cracow, social events and more. Participants will also have the chance to interact and hear lectures from exciting scientists, namely: Fabrizio Lillo, Chiara Poletto, Pere Colet and Piotr Fronczak. Best wishes, the WWCS 2019 organising committee Mateusz Wili?ski Tomasz Raducha Jaros?aw Klamut Grzegorz Siudem -------------- next part -------------- An HTML attachment was scrubbed... URL: From avellido at cs.upc.edu Thu Oct 18 04:04:55 2018 From: avellido at cs.upc.edu (Alfredo Vellido) Date: Thu, 18 Oct 2018 10:04:55 +0200 Subject: Connectionists: WSOM+ 2019, 1st call for papers, 13th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization In-Reply-To: References: Message-ID: <65be3125-79cc-7827-45ef-f1d73c59c762@cs.upc.edu> ************ WSOM+ 2019 ************ 13th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization Barcelona, Spain, 26-28 June 2019 https://wsom2019.cs.upc.edu 1st Call for Papers Paper submission deadline: January 20, 2019 WSOM+ invites contributions related to the theoretical and methodological aspects of Unsupervised Learning, Self-Organizing Maps, Learning Vector Quantization, Clustering, Data Visualization and closely related topics. We also call for and encourage scientific and application-oriented papers that demonstrate the use of the aforementioned methods and models in fields of knowledge. For the full CFP and further details on dates, submission, registration, venue, committees, and the city at large, please visithttps://wsom2019.cs.upc.edu The WSOM+ 2019 proceedings will be published as a book in Springer?s Advances in Intelligent Systems and Computing (AISC) series. Barcelona awaits your participation in the 13th WSOM+ conference! This is a welcoming and inclusive city, home to thriving Machine Learning and Computational Intelligence communities. Hosted by the Intelligent Data Engineering and Artificial Intelligence (IDEAI) Research Center at Universitat Polit?cnica de Catalunya (UPC BarcelonaTech), WSOM+ 2019 aims to build on a successful string of editions that started more than two decades ago with WSOM?97 in Helsinki. The conference is meant to be an international reference for research in unsupervised learning, self-organizing systems, Learning Vector Quantization and data visualization. Submit your contributions to WSOM+2019 and meet us in the Barcelona summer! ************ WSOM+ 2019 ************ Organizing Committee Alfredo Vellido, Chair (IDEAI, UPC BarcelonaTech) Karina Gibert (IDEAI, UPC BarcelonaTech) Cecilio Angulo (IDEAI, UPC BarcelonaTech) Jos? David Mart?n (Universitat de Val?ncia) Steering Committee: Teuvo Kohonen (Honorary Chairman, Finland) Marie Cottrell (France) Pablo Estevez (Chile) Timo Honkela (Finland) Jean Charles Lamirel (France) Thomas Martinetz (Germany) Erzsebet Merenyi (USA) Madalina Olteanu (France) Michel Verleysen (Belgium) Thomas Villmann (Germany) Takeshi Yamakawa (Japan) Hujun Yin (UK) From richard.jiang at northumbria.ac.uk Wed Oct 17 17:18:24 2018 From: richard.jiang at northumbria.ac.uk (Richard Jiang) Date: Wed, 17 Oct 2018 21:18:24 +0000 Subject: Connectionists: Call for Book Chapters on Deep Biometrics In-Reply-To: References: , Message-ID: Dear Colleagues, We would like to invite you to contribute a chapter for the upcoming volume entitled "Deep Biometrics" to be published by Springer, the largest global scientific, technical, and medical ebook publisher. The volume will be available both in print and in ebook format by late 2018/early 2019 on SpringerLink, one of the leading science portals that includes more than 8 million documents, an ebook collection with more than 160,000 titles, journal archives digitized back to the first issues in the 1840s, and more than 30,000 protocols and 290 reference works. Below is a short description of the volume: Recent development in machine learning, particularly deep learning, has brought out drastic impact on Biometrics, which is a classic topic to utilize Machine Learning for biometric identification. Particularly, Deep Learning can benefit from the training with large unlabelled datasets via semi-supervised or unsupervised learning. This book aims to highlight recent research advances in biometrics using semi-supervised and unsupervised new methods such as Deep Neural Networks, Deep Stacked Autoencoder, Convolutional Neural Networks, Generative Adversary Networks, Ensemble Methods, and so on, and exploit these novel methods in the emerging new areas such as privacy and security issues, cancellable biometrics and soft biometrics, smart cities, big biometric data, biometric banking, medical biometrics, and healthcare biometrics, etc.. The goal of this volume is to summarize the recent advances in using Deep Learning in the area of biometric security and privacy. Topics of interest include: (but not limited to) * Deep Learned Biometric Features * Convolutional Neural networks * Deep Stacked Autoencoder * Deep Face Detection * Deep Gait Recognition * Biometrics in Cybersecurity * Biometrics in Cognitive Robot * Healthcare Biometrics * Medical Biometrics * Biometrics in Social Computing * Biometric Block Chain * Privacy and Security Issues * Iris, Fingerprints, DNA, Palmprints * Gait, EEG, Heart rates * Multimodal Fusion * Soft Biometrics * Cancellable Biometrics * Big data issues in Biometrics * Biometrics for Internet of things Each contributed chapter is expected to present a novel research study, a comparative study, or a survey of the literature. Note that there will be no publication fees for accepted chapters. Important Dates: Submission of abstracts Nov 15, 2018 Notification of initial editorial decisions Nov 20, 2018 Submission of full-length chapters Dec 15, 2018 Notification of final editorial decisions Jan 15, 2019 Submission of revised chapters Feb 15, 2019 All submissions should be done via EasyChair: https://easychair.org/conferences/?conf=deepbio2019 Original artwork and a signed copyright release form will be required for all accepted chapters. For author instructions, please visit: http://www.springer.com/authors/book+authors?SGWID=0-154102-12-417900-0 Please feel free to contact us via email (perceptualscience at outlook.com, or any editors below) regarding your chapter ideas. Editorial Board * Dr Richard Jiang Computer and Information Sciences, Northumbria University, United Kingdom Email: richard.jiang at unn.ac.uk * Dr Weizhi Meng Applied Mathematics & Computer Science Technical University of Denmark, Denmark Email: weme at dtu.dk * Professor Chang-Tsun Li School of Computing and Mathematics, Charles Sturt University, Australia Email: chli at csu.edu.au * Professor Christophe Rosenberger Computer Security ENSICAEN - GREYC, France Email: christophe.rosenberger at ensicaen.fr Contact: All questions about submissions can be emailed to perceptualscience at outlook.com or any editor in the board. Many thanks! Kind Regards, Editors of the Book This message is intended solely for the addressee and may contain confidential and/or legally privileged information. Any use, disclosure or reproduction without the sender's explicit consent is unauthorised and may be unlawful. If you have received this message in error, please notify Northumbria University immediately and permanently delete it. Any views or opinions expressed in this message are solely those of the author and do not necessarily represent those of the University. Northumbria University email is provided by Microsoft Office365 and is hosted within the EEA, although some information may be replicated globally for backup purposes. The University cannot guarantee that this message or any attachment is virus free or has not been intercepted and/or amended. -------------- next part -------------- An HTML attachment was scrubbed... URL: From barros at informatik.uni-hamburg.de Thu Oct 18 09:42:13 2018 From: barros at informatik.uni-hamburg.de (Pablo Barros) Date: Thu, 18 Oct 2018 15:42:13 +0200 Subject: Connectionists: CFP: TAC | Special Issue on Automated Perception of Human Affect from Longitudinal Behavioral Data Message-ID: CALL FOR PAPERS IEEE Transactions on Affective Computing Special Issue on Automated Perception of Human Affect from Longitudinal Behavioral Data Website: https://www2.informatik.uni-hamburg.de/wtm/omgchallenges/tacSpecialIssue2018.html I. Aim and Scope Research trends within artificial intelligence and cognitive sciences are still heavily based on computational models that attempt to imitate human perception in various behavior categorization tasks. However, most of the research in the field focuses on instantaneous categorization and interpretation of human affect, such as the inference of six basic emotions from face images, and/or affective dimensions (valence-arousal), stress and engagement from multi-modal (e.g., video, audio, and autonomic physiology) data. This diverges from the developmental aspect of emotional behavior perception and learning, where human behavior and expressions of affect evolve and change over time. Moreover, these changes are present not only in the temporal domain but also within different populations and more importantly, within each individual. This calls for a new perspective when designing computational models for analysis and interpretation of human affective behaviors: the computational models that can timely and efficiently adapt to different contexts and individuals over time, and also incorporate existing neurophysiological and psychological findings (prior knowledge). Thus, the long-term goal is to create life-long personalized learning and inference systems for analysis and perception of human affective behaviors. Such systems would benefit from long-term contextual information (including demographic and social aspects) as well as individual characteristics. This, in turn, would allow building intelligent agents (such as mobile and robot technologies) capable of adapting their behavior in a continuous and on-line manner to the target contexts and individuals. This special issue aims at contributions from computational neuroscience and psychology, artificial intelligence, machine learning, and affective computing, challenging and expanding current research on interpretation and estimation of human affective behavior from longitudinal behavioral data, i.e., single or multiple modalities captured over extended periods of time allowing efficient profiling of target behaviors and their inference in terms of affect and other socio-cognitive dimensions. We invite contributions focusing on both the theoretical and modeling perspective, as well as applications ranging from human-human, human-computer and human-robot interactions. II. Potential Topics Given computational models, the capability to perceive and understand emotion behavior is an important and popular research topic. That is why recent special issues on the IEEE Journal on Transactions on Affective Computing covered topics from emotion behavior analysis ?in-the-wild? to personality analysis. However, most of the research published by these specific calls treat emotion behavior as an instantaneous event, relating mostly to emotion recognition, and thus neglect the development of complex emotion behavior models. Our special issue will foster the development of the field by focusing excellent research on emotion models for long-term behavior analysis. The topics of interest for this special issue include, but are not limited to: - New theories and findings on continuous emotion recognition - Multi- and Cross-modal emotion perception and interpretation - Lifelong affect analysis, perception, and interpretation - Novel neural network models for affective processing - New neuroscientific and psychological findings on continuous emotion representation - Embodied artificial agents for empathy and emotion appraisal - Machine learning for affect-driven interventions - Socially intelligent human-robot interaction - Personalized systems for human affect recognition III. Submission Prospective authors are invited to submit their manuscripts electronically, adhering to the IEEE Transactions on Affective Computing guidelines ( https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5165369). Please submit your papers through the online system ( https://mc.manuscriptcentral.com/taffc-cs) and be sure to select the special issue: Special Issue/Section on Automated Perception of Human Affect from Longitudinal Behavioral Data. IV. IMPORTANT DATES: Submissions Deadline: 15th of January 2019 Deadline for reviews and response to authors: 06th of April 2019 Camera-ready deadline: 05th of August 2019 V. Guest Editors Pablo Barros, University of Hamburg, Germany Stefan Wermter, University of Hamburg, Germany Ognjen (Oggi) Rudovic, Massachusetts Institute of Technology, United States of America Hatice Gunes, University of Cambridge, United Kingdom -------------------------- -- Dr. Pablo Barros Postdoctoral Research Associate - Crossmodal Learning Project (CML) Knowledge Technology Department of Informatics University of Hamburg Vogt-Koelln-Str. 30 22527 Hamburg, Germany Phone: +49 40 42883 2535 Fax: +49 40 42883 2515 barros at informatik.uni-hamburg.dehttp://www.pablobarros.nethttps://www.inf.uni-hamburg.de/en/inst/ab/wtm/people/barros.htmlhttps://www.inf.uni-hamburg.de/en/inst/ab/wtm/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From bisant at umbc.edu Thu Oct 18 14:16:29 2018 From: bisant at umbc.edu (David Bisant) Date: Thu, 18 Oct 2018 14:16:29 -0400 Subject: Connectionists: CFP: FLAIRS 2019, Sarasota, FL, Datamining Track In-Reply-To: References: Message-ID: CALL FOR PAPERS FLAIRS 2019, Florida Artificial Intelligence Research Symposium Special Track on Data mining Sarasota, Florida https://sites.google.com/view/flairs-32homepage/home Paper submission deadline: November 19, 2018. Notifications: January 21, 2019. Camera ready version due: February 25, 2019. FLAIRS is an interdisciplinary artificial intelligence conference which especially encourages novel ideas and which features a double-blind review process. Data Mining Track This special track will be devoted to data mining with the aim of presenting new and important contributions in this area. Papers and contributions are encouraged for any work related to Data Mining. Topics of interest may include (but are in no way limited to): 1. Applications such as Intelligence analysis, medical and health applications, text, video, and multi-media mining, E-commerce and web data, financial data analysis, cyber security, remote sensing, earth sciences, bioinformatics, and astronomy. 2. Modeling algorithms such as hidden Markov models, decision trees, neural networks, statistical methods, or probabilistic methods; case studies in areas of application, or over different algorithms and approaches. 3. Feature extraction and selection. 4. Post-processing techniques such as visualization, summarization, or trending. 5. Preprocessing and data reduction. 6. Knowledge engineering or warehousing. Papers dealing with Cloud-based unstructured data or Cloud-based tool suites, such as Mahout, Amazon AWS, or Apache Spark, are also encouraged. Note: We invite original papers (i.e. work not previously submitted, in submission, or to be submitted to another conference during the reviewing process). Submission Guidelines Interested authors should format their papers according to AAAI formatting guidelines. Papers should not exceed 6 pages (or 4 pages for short paper, to be presented as a poster) and are due by November 19, 2018. FLAIRS reviewing is a double blind process. Author names and affiliations should be substituted X?d out on the submitted draft to provide double-blind reviewing. Papers must be submitted as PDF through the EasyChair conference system, which can be accessed through the main conference web site (https://sites.google.com/view/flairs-32homepage/home). Note: use your real name for your EasyChair login - your EasyChair account information is hidden from reviewers. Authors should indicate which special track they are submitting to. The proceedings of FLAIRS will be published by the AAAI. Authors of accepted papers will be required to sign a form transferring copyright of their contribution to AAAI. FLAIRS requires that there be at least one full author registration per paper. Further information about the track may be on the main conference website or at: https://userpages.umbc.edu/~bisant/gl/FLAIRS32_DM_CFP.htm From boubchir at ai.univ-paris8.fr Thu Oct 18 15:35:38 2018 From: boubchir at ai.univ-paris8.fr (Larbi Boubchir) Date: Thu, 18 Oct 2018 21:35:38 +0200 Subject: Connectionists: Special Issue on Intelligent Industrial Digital Forensics and Biocybernetics: Practices and Challenges - Pattern Recognition Letters In-Reply-To: References: Message-ID: <1d072f95-f17a-52cf-85a5-e7ffe18b0bdf@ai.univ-paris8.fr> *Special Issue on "Intelligent Industrial Digital Forensics and Biocybernetics: Practices and Challenges"*** ***in Pattern Recognition Letters journal*** https://www.journals.elsevier.com/pattern-recognition-letters/call-for-papers/virtual-special-issue-on-intelligent-industrial-digital-fore *Motivations: * Digital forensic methodologies are widely used in industries to ensure authentication of multimedia data. Biocybernetics has emerged as a tool to secure systems from cyber threats via biometric based processes. Jointly, digital forensics and biocybernetics can ensure support system for high level security. The mechanisms of digital forensics and biocybernetic technologies presently need human expert interference, and cannot perform in automated way. Thereby these processes cannot be suited for in large scale industrial need in their present form. Hence a lot of research has been conducted in this domain during last few years, mostly all studies yielding sub-optimal solutions, which still encourages current researchers to conduct further research in this area. This special issue solicits original research articles, extensive reviews, and case studies in the aforementioned field of research. *Topics include, but are not limited to:* - Digital Forensic techniques applicable to large scale systems - Biocybernetic architecture management - Biosignal processing and biosensing systems - Brain-human-interface - Knowledge sharing systems for forensic analysis - Biocybernetic surveillance in industry - Anti-pattern search for biocybernetic spoofing - Biometric technologies for large scale industry - Industrial biometric data management - Parallel and distributed processing of forensic data - Cybercrime detection and mitigation - Uberveillance technologies for smart industry - Standards and protocols for industrial forensics *Important dates: * Submission period: 1-31 March 2019 Submission deadline: 31 March 2019 First review notification: 1 June 2019 Revision submission: 1 August 2019 Second review notification: 1 September 2019 Final notification to authors: 30 September 2019 Online publication: October 2019 *Submission Guidelines: * All submissions have to be prepared according to the Guide for Authors as published in the Journal Web Site at http://www.elsevier.com/journals/pattern-recognition-letters/0167-8655/guide-for-authors. Submissions should be sent through http://ees.elsevier.com/prletters/. Authors should select the acronym "VSI:IIDFB-PC" as the article type, from the "Choose Article Type" pull-down menu during the submission process. The maximal length of a paper is 7 pages in the PRLetters layout and may become 8 in the revised version if referees explicitly request significant additions. The submitted papers should not have been previously published or be under consideration for publication elsewhere. If one submission is the extended work of one conference paper, the original work should be included and a description of the changes should be provided. The PRLetters submission should include at least 30% new contribution of high relevance (more experiments, proofs of theorems not included in the conference paper, more comparisons with other methods in the literature and so on); and the title of the PRLetters paper should be different, the same figures cannot be used and the common part of the conference paper and of the extended version cannot be verbatim the same. *Review Process: * The review process will follow the standard PRLetters scheme. Each paper will be reviewed by at least two referees and that, in general, only two reviewing rounds will be possible, out of which major revision is possible for the first reviewing round. Submissions will probably being rejected if major revision is still required after the second reviewing round. *Guest Editors: * Asso. Prof., Dr., Larbi Boubchir (Managing Guest Editor) University of Paris 8, France E-mail: larbi.boubchir at ai.univ-paris8.fr Prof. Abdesselam Bouzerdoum University of Wollongong, NSW, Australia E-mail: a.bouzerdoum at uow.edu.au Prof. Esma A?meur University of Montreal, Montreal, Canada E-mail: aimeur at iro.umontreal.ca Dr. Abdenour Hadid University of Oulu, Finland E-mail: hadid.abdenour at oulu.fi Dr. Sambit Bakshi National Institute of Technology Rourkela, India E-mail: bakshisambit at nitrkl.ac.in -- _____________________________________________________ Larbi Boubchir, PhD, SMIEEE Associate Professor LIASD - University of Paris 8 2 rue de la Libert?, 93526 Saint-Denis, France Tel. (+33) 1 49 40 67 95 Email. larbi.boubchir at ai.univ-paris8.fr http://www.ai.univ-paris8.fr/~boubchir/ _____________________________________________________ -------------- next part -------------- An HTML attachment was scrubbed... URL: From kripa.ghosh at gmail.com Fri Oct 19 08:51:38 2018 From: kripa.ghosh at gmail.com (Kripa Ghosh) Date: Fri, 19 Oct 2018 18:21:38 +0530 Subject: Connectionists: [[Final CFP] CIKM 2018 Workshop on Legal Data Analytics and Mining (LeDAM 2018) Message-ID: [apologies for cross-posting ] CALL FOR PARTICIPATION Workshop on Legal Data Analytics and Mining (LeDAM 2018) In conjunction with ACM International Conference on Information and Knowledge Management (CIKM) 2018 Turin, Italy | 22nd October 2018 Website : https://sites.google.com/site/legaldam2018/ Legal data mining is the subarea of data mining applied to legal texts, such as legislation, case law, patents, and scholarly works. Legal data mining systems are key to providing easier access to law for both common persons and legal professionals. This area is becoming increasingly important, because of the rapidly growing volume of legal cases and documents available in digital formats. The broad goals of the LeDAM workshop are: -- to promote research in legal data analytics by fostering collaboration between the legal data mining practitioners and the data mining research community at large, -- to improve awareness among the legal community about the state of the art models, techniques and algorithms developed by the data mining community that can potentially benefit the problems, and -- to identify new research opportunities in data mining that arise from legal applications. ============= INVITED TALKS ============= Speaker: Giovanni Sartor, Professor of Legal Informatics and Legal Theory, European University Institute, Italy Title: Using Machine Learning to Support Law Enforcement to the Benefit of Consumers and Data Subject: the CLAUDETTE Project Abstract: The project CLAUDETTE aims to support the detection of potentially unfair and unlawful clause, both in consumer contacts and in privacy policies, through automated tools, based on computational linguistic and artificial intelligence. The purpose is to enable consumer protection bodies and data protection authorities to engage more proactively and effectively in monitoring compliance and in enforcing the law. With regard to both contract terms and privacy policy we have collected a corpus of contract terms, identified different kinds of unlawful and unfair terms through legal analysis, and annotated the documents accordingly. Then we have applied and tested different computational approaches, including various machine learning algorithms, to detect such terms. The better performing algorithms have been implemented in an application available to the public through the project's website. The system is complemented by a crawler, that detects changes in the contract and policies already submitted to the system. ***** Speaker: Luigi Di Caro, Assistant Professor, Department of Computer Science, University of Turin, Italy Title: Natural Language Processing and Ontology Learning in the Legal Domain Abstract: Legal ontologies aim to provide a structured representation of legal concepts and their interconnections. These ontologies are then exploited to support tasks such as information extraction and question answering in the legal domain. Given the increasing importance of the Web of Data in public administration and in companies, being able to provide machine-readable legal information is becoming a valuable and desired contribution. However, concepts and relations within existing ontologies usually represent limited subjective and application-oriented views of specific sub-domains of interest. The talk will discuss recent research on natural language technologies and text mining approaches towards the creation, the reuse and the enrichment of legal ontologies. ***** Speaker: Jack G. Conrad, Lead Research Scientist, Center for AI and Cognitive Computing, Thomson Reuters, USA Title: 30 Years of AI and Law: Legal Data Analytics in the Long View -- Looking Back, Looking Forward Abstract: This talk will begin by examining the roots of Artificial Intelligence and Law -- including applications involving NLP, data mining, machine learning, and more broadly, data analytics -- noting that it has been around for much longer than the recent buzz would suggest. We will explore the field of AI and Law in terms of its development and expansion starting in the 1980s and study how seminal research was conducted and reported on in conference proceedings such as ICAIL and publications such as the AI and Law journal. After having established the foundations of today's field of AI and Law, we will look to the future and sketch some of the practical application scenarios that the capabilities from the field promise to deliver. These include next-generation tools for legal professionals that can augment their skill sets by providing analytical abilities to help in the crafting of legal strategies. We will illustrate such instruments through the visualization of expected outcomes, while varying key parameters such as trial length, expected costs, and likely award or settlement figures. Lastly, we will investigate the prospective role that prediction tools can play in AI and Law application spaces, while looking still further into the future. ==================== PAPER PRESENTATIONS ==================== Structural Analysis of Contract Renewals Frieda Josi and Christian Wartena (University of Applied Sciences and Arts Hanover, Germany) Concept Hierarchy Extraction from Legal Literature Sabine Wehnert, David Broneske, Stefan Langer and Gunter Saake (Otto von Guericke University and Legal Horizon AG, Germany) Use of Pseudo Relevance Feedback for Patent Clustering with Fuzzy C-means Noushin Fadaei and Thomas Mandl (Hildesheim University, Germany) Argumentation-driven information extraction for online crime reports Marijn Schraagen, Bas Testerink, Daphne Odekerken and Floris Bex (Utrecht University, The Netherlands, and Dutch National Police) Deep Ensemble Learning for Legal Query Understanding Arunprasath Shankar and Venkata Nagaraju Buddarapu (LexisNexis, USA) ================= Organizing Committee ================= Arindam Pal, TCS Research and Innovation, India (http://www.cse.iitd.ernet.in/~arindamp/) Arnab Bhattacharya, Indian Institute of Technology Kanpur, India (https://www.cse.iitk.ac.in/users/arnabb/) Indrajit Bhattacharya, TCS Research and Innovation, India (https://sites.google.com/site/indrajitb/) Kripabandhu Ghosh, Indian Institute of Technology Kanpur, India (https://www.cse.iitk.ac.in/users/kripa/) Lipika Dey, TCS Research and Innovation, India (http://sites.tcs.com/blogs/research-and-innovation/author/dr-lipika-dey) Marie-Francine Moens, KU Leuven, Belgium (https://people.cs.kuleuven.be/~sien.moens/) Saptarshi Ghosh, Indian Institute of Technology Kharagpur, India (http://cse.iitkgp.ac.in/~sghosh/) For details, see https://sites.google.com/site/legaldam2018/ Kind Regards, Kripabandhu Ghosh Co-organizer LeDAM 2018 Workshop CIKM 2018 -------------- next part -------------- An HTML attachment was scrubbed... URL: From luca.oneto at unige.it Fri Oct 19 12:14:01 2018 From: luca.oneto at unige.it (Luca Oneto) Date: Fri, 19 Oct 2018 18:14:01 +0200 Subject: Connectionists: [INNS-BDDL 2019] - Last Call for Papers Message-ID: [Apologies if you receive multiple copies of this CFP] ########################################################### CALL FOR PAPERS INNS BIG DATA AND DEEP LEARNING 2019 April 16-18 SESTRI LEVANTE, GENOA, ITALY Website: https://innsbddl2019.org/ ######################Description########################## The 2019 INNS Big Data and Deep Learning (INNSBDDL 2019) conference will be held in Sestri Levante, Italy, April 16 ? 18, 2019. The conference is organized by the International Neural Network Society, with the aim of representing an international meeting for researchers and other professionals in Big Data, Deep Learning and related areas. It will feature invited plenary talks by world renowned speakers in the area, in addition to regular and special technical sessions with oral and poster presentations. Moreover, workshops and tutorials will also be featured. ######################Invited Speakers##################### * Hava Siegelmann, DARPA, USA * Paolo Ferragina, University of Pisa, Italy * Guang-Bin Huang, Nanyang Technological University, Singapore ########################################################### ######################Tutorials############################ * Alessio Micheli (University of Pisa), Davide Bacciu (University of Pisa), Deep Learning for Graphs * Silvia Chiappa (DeepMind), Luca Oneto (University of Genoa), Fairness in Machine Learning * Claudio Gallicchio (University of Pisa), Simone Scardapane (Sapienza University of Rome), Deep Randomized Neural Networks * V?ra K?rkov? (Czech Academy of Sciences), Complexity of Shallow and Deep Networks * Danilo P. Mandic, Ilia Kisil, and Giuseppe G. Calvi (Imperial College London), Tensor Decompositions and Applications. Blessing of Dimensionality * German I. Parisi and Stefan Wermter (University of Hamburg), Continual Lifelong Learning with Neural Networks ########################################################### #######################IMPORTANT DATES##################### * Deadline of full paper submission: October 31, 2018 * Notification of paper acceptance: December 31, 2018 * Camera-ready submission: January 31, 2019 * Early registration deadline: January 15, 2019 * Registration deadline: January 31, 2019 * Conference date: April 16 - 18, 2019 ########################################################### ##########################SCOPE############################ We solicit both solid contributions or preliminary results which show the potentiality and the limitations of new ideas, refinements, or contaminations in any aspect of Big Data and Deep Learning. Both theoretical and practical results are welcome. Example topics of interest includes but is not limited to the following: Big Data Science and Foundations * Novel Theoretical Models for Big Data * New Computational Models for Big Data * Data and Information Quality for Big Data Big Data Mining * Social Web Mining * Data Acquisition, Integration, Cleaning, and Best Practices * Visualization Analytics for Big Data * Computational Modeling and Data Integration * Large-scale Recommendation Systems and Social Media Systems * Cloud/Grid/StreamData Mining * Big Velocity Data * Link and Graph Mining * Semantic-based Data Mining and Data Preprocessing * Mobility and Big Data * Multimedia and Multistructured Data-Big Variety Data Modern Practical Deep Networks * Deep Feedforward Networks * Regularization for Deep Learning * Optimization for Training Deep Models * Convolutional Networks * Sequence Modeling: Recurrent and Recursive Nets * Practical Methodology Deep Learning Research * Linear Factor Models * Autoencoders * Representation Learning * Structured Probabilistic Models for Deep Learning * Monte Carlo Methods * Confronting the Partition Function * Approximate Inference * Deep Generative Models ####################PROCEEDINGS & SPECIAL ISSUE############ Works submitted as a regular paper will be published in a serie indexed by Scopus. Submitted papers will be reviewed by some PC members based on technical quality, relevance, originality, significance and clarity. At least one author of an accepted submission should register to present their work at the conference. Selected papers presented at INNS BDDL 2019 will be included in special issues of top journals in the field (prospected journals: Big Data Research, Transaction on Neural Networks and Learning System, Neurocomputing, etc). ########################################################### ----------------------------------------------------------------------------------- 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 luca.oneto at unige.it Fri Oct 19 12:14:01 2018 From: luca.oneto at unige.it (Luca Oneto) Date: Fri, 19 Oct 2018 18:14:01 +0200 Subject: Connectionists: ESANN 2019 SS - Societal Issues in Machine Learning: When Learning from Data is Not Enough Message-ID: [Apologies if you receive multiple copies of this CFP] Call for papers: special session on "Societal Issues in Machine Learning: When Learning from Data is Not Enough" at ESANN 2019 European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2019). 24-26 April 2019, Bruges, Belgium - http://www.esann.org DESCRIPTION: It has been argued that Artificial Intelligence (AI) is experiencing a fast process of commodification. This characterization is on the interest of big IT companies, but it correctly reflects the current industrialization of AI. This phenomenon means that AI systems and products are reaching the society at large and, therefore, that societal issues related to the use of AI and Machine Learning (ML) cannot be ignored any longer. Designing ML models from this human-centered perspective means incorporating human-relevant requirements such as safety, fairness, privacy, and interpretability, but also considering broad societal issues such as ethics and legislation. These are essential aspects to foster the acceptance of ML-based technologies, as well as to be able to comply with an evolving legislation concerning the impact of digital technologies on ethically and privacy sensitive matters. This special session aims to put forward the state-of-the-art on these increasingly relevant topics among ML theoretician and practitioners. For this purpose, we welcome both solid contributions and preliminary relevant results showing the potential, the limitations and the challenges of new ideas, refinements, or contaminations between the different fields of research, ML, and related approaches in facing real-world problems involving societal issues. We welcome works on ML theory, applications to topics listed below as well as other topics of social relevance. Studies stemming from major research initiatives and projects focusing on the session topics are particularly welcome. TOPICS OF INTEREST: - Fairness as an element in the development of ML techniques; - Ethical issues in the application of ML and related techniques in areas of social impact; - Privacy as a challenge in ML application to problems in the social domain; - Interpretability and explainability of ML and related approaches; - Safety and Security of ML and related methods in safety critical contexts; - Legislative challenges to the use of ML and related methods; - The challenge of complex data for ML and related methods; - Transparency and open data. SUBMISSION: Prospective authors must submit their paper through the ESANN portal following the instructions provided in https://www.elen.ucl.ac.be/esann/index.php?pg=submission Each paper will undergo a peer reviewing process for its acceptance. Authors should send as soon as possible an e-mail with the tentative title of their contribution to the special session organisers. IMPORTANT DATES: Submission of papers: 19 November 2018 Notification of acceptance: 31 January 2019 ESANN conference: 24 - 26 April 2019 SPECIAL SESSION ORGANISERS: Davide Bacciu, University of Pisa (Italy) Battista Biggio, University of Cagliari (Italy) Jos? D. Mart?n, Universitat de Val?ncia (Spain) Luca Oneto, University of Genoa (Italy) Alfredo Vellido, Universitat Polit?cnica de Catalunya (Spain) Paulo J. G. Lisboa, Liverpool John Moores University (UK) ----------------------------------------------------------------------------------- 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 boris.gutkin at ens.fr Fri Oct 19 09:42:32 2018 From: boris.gutkin at ens.fr (boris gutkin) Date: Fri, 19 Oct 2018 15:42:32 +0200 Subject: Connectionists: Masters Program in Cognitive Sciences and Technologies at the Higher School of Economics, Moscow, Russia Message-ID: Dear Applicants,We are pleased to invite you to apply for our master?s program ?Cognitive Sciences and Technologies: From Neuron to Cognition.? Admissions: The admission period for 2019 is from October 15th until August 12th. All deadlines for the admission process can be found at the following link: https://www.hse.ru/admissions/graduate-apply. We encourage you to submit your application early during the admissions process. Fees: There are 5 scholarship places and 10 tuition fee places available, with a flexible discount system. Please find further information about tuition fees at: https://www.hse.ru/admissions/graduate-apply/financial-aid#pagetop Course Requirements: Course requirements can be found at the following link: https://www.hse.ru/en/ma/cogito/cognrequirements. How to Apply: Information about how to apply for the program can be found at: https://www.hse.ru/en/ma/cogito/application Student Profiles: You will find interviews from some of our current masters students on the program website. If you have any questions regarding the application process or tuition fees, please feel free to contact either the HSE international admissions office at inter at hse.ru, or Dr. Tadamasa Sawada the program professor at tsawada at hse.ru or the masters program cogito at hse.ru. -------------- next part -------------- An HTML attachment was scrubbed... URL: From fzenke at gmail.com Fri Oct 19 05:45:45 2018 From: fzenke at gmail.com (Friedemann Zenke) Date: Fri, 19 Oct 2018 10:45:45 +0100 Subject: Connectionists: PhD fellowships in computational neuroscience at the FMI in Basel, Switzerland Message-ID: <6e0b9ad8-a419-7c8a-94ca-adead2d96edd@gmail.com> The FMI PhD program now welcomes applications in computational neuroscience. Submission deadline is the 16th of November 2018. The FMI PhD program offers students the opportunity to carry out cutting-edge research in a stimulating, highly international and collaborative atmosphere. Affiliated with the Novartis Institutes for BioMedical Research and the University of Basel in Switzerland, the FMI provides interdisciplinary training and access to state-of-the-art technology platforms and high-performance computing facilities. Several research groups at the FMI offer exciting PhD projects for students with a computational background. PhD students whose primary interest is in computational neuroscience, will be able to join a new group led by Friedemann Zenke which focuses on memory formation and information processing in biologically inspired neural network models. Students will have the opportunity to directly collaborate with experimental groups in system neuroscience at the FMI (https://www.fmi.ch/Research/Neurobiology/). A wide range of theoretical and practical courses are available at both the FMI and the University of Basel. After completion of their thesis work, students are awarded a PhD from the University of Basel. Candidates should be curious about the neural underpinnings of computation and learning, have a strong analytical and quantitative background, and hold a relevant first degree in, for instance, computer science, engineering, mathematics, neuroscience, physics, psychology, or statistics. Funding is available regardless of current residence and nationality. Applications should be submitted online via https://www.fmi.ch/training/phd/apply/ Additional information PhD program: https://www.fmi.ch/training/PhD/ Zenke group (from 2019): https://www.fmi.ch/research/groupleader/zenke.html Neurobiology groups: https://www.fmi.ch/Research/Neurobiology/ For questions, please contact Elida Keller (fmiphdprogram at fmi.ch). -- Friedemann Zenke, PhD Sir Henry Wellcome Fellow Centre for Neural Circuits and Behaviour University of Oxford Tinsley Building Mansfield Road Oxford OX1 3SR United Kingdom https://fzenke.net From vito.trianni at istc.cnr.it Fri Oct 19 09:24:05 2018 From: vito.trianni at istc.cnr.it (Vito Trianni) Date: Fri, 19 Oct 2018 15:24:05 +0200 Subject: Connectionists: [jobs] research position: collective decision making, ISTC-CNR, Rome, Italy Message-ID: <7E41E78C-D9F3-43F3-8511-64B89A75E783@istc.cnr.it> I?m recruiting a postdoctoral researcher to work within the newly founded project "CODE: Collective Decisions in Dynamic Environments" to be carried out the Institute of Cognitive Sciences and Technologies of the Italian National Research Council, in Rome. The position is for one year, and is renewable for two more years. The research program aims to the study of collective decision making in dynamical contexts, where the possible alternatives display time-varying features. The study has a theoretical component based on dynamical systems theory, and an experimental component based on multi-agent and multi-robot systems. Dynamical systems are useful to determine the time evolution of collective decision-making under a given parameterisation, with the goal of identifying optimal conditions to maximise efficiency and decision accuracy. Multi-agent models allow to validate the predictions made by analytical models, and to consider heterogeneous interaction topologies that can emerge, for instance, from a complex and dynamic distribution of agents in space, as resulting from non-random motion patterns. The research also includes the possibility to test the identified collective decision strategies with multi-robot systems, exploiting a swarm of kilobot robots. The ideal candidate should have knowledge of dynamical systems theory and expertise in using tools for such studies (e.g., Wolfram Mathematica). Good programming skills are also required (Python, C++), as well as abilities in data visualisation. The deadline to submit an application is November the 9th. PhD students nearing the end of their doctoral program are also welcome to participate. The interested candidate may place an informal inquiry by contacting me, or read the instructions for the application provided in the notice of selection: http://www.istc.cnr.it/sites/default/files/vacancies/bandi/notice_of_selection_n._istc-adr-247-2018-rm.doc ======================================================================== Vito Trianni, Ph.D. vito.trianni@(no_spam)istc.cnr.it ISTC-CNR http://www.istc.cnr.it/people/vito-trianni Via San Martino della Battaglia 44 Tel: +39 06 44595277 00185 Roma Fax: +39 06 44595243 Italy ======================================================================== From jonizhong at msn.com Sat Oct 20 05:44:53 2018 From: jonizhong at msn.com (Joni Zhong) Date: Sat, 20 Oct 2018 09:44:53 +0000 Subject: Connectionists: [CFP] WS: From Robotic Dexterous Manipulation to Manual Intelligence co-located Humanoids 2018 Message-ID: CFP IEEE Humanoids 2018 WS: From Robotic Dexterous Manipulation to Manual Intelligence https://ni.www.techfak.uni-bielefeld.de/ICHR2018WS/home ****************************************************************** Call for participation: >From Robotic Dexterous Manipulation to Manual Intelligence, Nov 6, Beijing, China , held at IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids 2018) (http://humanoids2018.csp.escience.cn/dct/page/1) ******************************************************************** Motivation and Topics Within recent 30 years, we have witnessed the progress of dexterous robotic hands from its designing and controlling aspects. However, how to use these advanced robot hands to implement skillful tasks like human are still very challengeable. Our expectations on the use of the robotic hands are rather high, the use cases in the robotic application are very few. We are considering the following three challenges for available robotic hands: ? It is still difficult to robustly, adaptively and dexterously control a robotic hand given the high mechanical complexity of the devices ? It is not clear how to implement complex tasks using the robotic hand equipped with limited sensing capability in the unstructured environment ? It is still an open question to represent and transfer human?s manipulation skills to a robotic hand which has a similar configuration space In order to solve the aforementioned challenges, one solution will be merging the newest findings in neuroscience, cognitive science, machine representation, and learning domains, e.g. how human are using their hands skillfully and how humans are using their hands as an important recognition tool to explore and learn the unknown world. We believe this can lead to the real ?manual intelligence? which not only can largely improve dexterous control of the robotic hand but also exploiting the robotic hand?s action-perception loop to autonomously understand the unstructured environment. Within this workshop we will bring together experts from the different domains, e.g. the developers of dexterous hands, control scientists focusing on grasping, planning and computer scientists studying machine learning to discuss progress and challenges of hand?s dexterous manipulation, foster potential collaborations, and reinforce the strict link among such interdisciplinary research fields to facilitate progress in this community. Central to the discussion will be three key questions: ? How to integrate multi-modal sensing for improving the robotic hand?s dexterous capability autonomously ? How to represent human?s manual skills and transfer them to robotic hands? ? How to define the benchmark to evaluate the dexterous capability of robotic hands? The workshop topics include but are not limited in the following ? New type of dexterous robotic hand ? Human?s manual skill representation ? Robotic hand?s grasping planning and control ? Unknown objects in-hand manipulation ? Sensory-based robotic hand grasping and manipulation ? Neuro-inspired control for grasping and manipulation ? Machine learning techniques for grasping and manipulation Invited speakers Prof. Tamim Asfour, Karlsruhe Institute of Technology, Germany, confirmed Prof. Hong Liu, Harbin Institute of Technology, China, confirmed Prof. Huaping Liu, Tsinghua University, China, confirmed Prof. Abderrahmane Kheddar, CNRS-UM LIRMM, France, confirmed Prof. Tetsuya Ogata, Waseda University, Japan, confirmed Dr. Qiang Li, Bielefeld University, Germany, confirmed Dr. Maximo Roa, German Aerospace Center, Germany, confirmed Dr. Filipe Veiga, Technische Universitaet Darmstadt, Germany, confirmed Prof. Robert Platt, Northeastern University, USA, tentatively confirmed Prof. Jianwei Zhang, Hamburg University, Germany, tentatively confirmed Submission information Prospective participants are required to submit an extended abstract (maximum 2 pages in length), but videos are also welcome! All submissions will be reviewed using a single-blind review process. Accepted contributions will be presented during the workshop as posters. Submissions must be sent in pdf, following the IEEE conference style (two-columns), to: qli_AT_techfak_DOT_uni-bielefeld_DOT_de indicating [Humanoids 2018 Workshop] in the e-mail subject. Important Dates Paper Submission Deadline (extended): October 25 Notification of acceptance: October 30 Workshop day: November 6 Organizers Dr. Qiang Li, Neuroinformatics Group / CITEC, Bielefeld University, Germany Dr. Zhaopeng Chen, Robotics and Mechatronics Center, German Aerospace Center (DLR), Germany Dr. Junpei Zhong, AI Research Center, National Institute of Advanced Industrial Science and Technology (AIST), Japan Prof. Chenguang Yang, College of Engineering, Swansea University, UK Prof. Helge Ritter, Neuroinformatics Group / CITEC, Bielefeld University, Germany Supported by IEEE TCs: - On Robotic Hands, Grasping and Manipulation - On Robot Learning - On Neuro Robotics System -------------- next part -------------- An HTML attachment was scrubbed... URL: From tat at tchumatchenko.de Sat Oct 20 11:32:31 2018 From: tat at tchumatchenko.de (Tatjana Tchumatchenko) Date: Sat, 20 Oct 2018 17:32:31 +0200 Subject: Connectionists: Open Master, PhD and Postdoc positions at the "Theory of Neural Dynamics" at the MPI for Brain Research Message-ID: <0c883598-c135-cfb6-8dc2-65023e9d6b45@tchumatchenko.de> Dear friends and colleagues, I would appreciate if you could spread the word among your Students and Postdocs. My group "Theory of Neural Dynamics" at the MPI for Brain Research is looking for Master Students, PhD Students and Postdocs Master Students, PhD Students or Postdocs interested in understanding how neuronal networks work, how they respond to stimuli and what role connectivity and single neuron dynamics play for the activity of the brain. Though the focus of my research is on the theory side, my lab has close ties to experimentally oriented labs and Master projects could include both theory and experiments. We are looking for bright and hard-working students with a life-science or quantitative background (physics, math, biology etc). When applying please attach CV (with a publication record) and a current copy of academic transcripts. For more information, please contact Dr. Tatjana Tchumatchenko via email tatjana.tchumatchenko at brain.mpg.de https://brain.mpg.de/research/theory-of-neural-dynamics-group.html www.tchumatchenko.de -------------- next part -------------- An HTML attachment was scrubbed... URL: From felipe at cos.ufrj.br Sat Oct 20 15:02:04 2018 From: felipe at cos.ufrj.br (Felipe Maia Galvao Franca) Date: Sat, 20 Oct 2018 16:02:04 -0300 Subject: Connectionists: CFP: "60 Years of Weightless Neural Systems" at ESANN 2019 Message-ID: [Apologies if you receive multiple copies of this CFP] Call for papers: special session on "60 Years of Weightless Neural Systems" at ESANN 2019 European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2019). 24-26 April 2019, Bruges, Belgium - http://www.esann.org Mimicking biological neurons by focusing on the decoding performed by the dendritic trees is an attractive alternative to the integrate-and-fire McCullogh-Pitts neuron stylisation. RAM-based, or Boolean neurons, and weightless neural systems have been studied and applied in a broad spectrum of situations, resulting in theoretical findings and the development of exciting applications to an ample set of domains, ranging from natural language processing to game playing, including memory transfer mechanisms, biomedical applications, computational vision, hardware security, and quantum learning. The year of 2019 marks the 60-years anniversary of the seminal paper on n-tuple classifiers by Bledsoe and Browning, as well as the 35-years of the WiSARD model, and the tenth anniversary of the first special session on weightless neural systems at ESANN. This session invites original contributions on theoretical and practical aspects of weightless neural systems at all levels of abstraction, as well as their relationship to themes of current interest such as: deep learning, convolutional neural models, adversarial learning, etc. SUBMISSION: Prospective authors must submit their paper through the ESANN portal following the instructions provided in https://www.elen.ucl.ac.be/esann /index.php?pg=submission Each paper will undergo a peer reviewing process for its acceptance. Authors should send as soon as possible an e-mail with the tentative title of their contribution to the special session organisers. IMPORTANT DATES: Submission of papers: 19 November 2018 Notification of acceptance: 31 January 2019 ESANN conference: 24 - 26 April 2019 SPECIAL SESSION ORGANISERS: Priscila M. V. Lima, Universidade Federal do Rio de Janeiro (Brazil) Felipe M. G. Fran?a, Universidade Federal do Rio de Janeiro (Brazil) Massimo De Gregorio, Ist. di Sci. Appl. e Sistemi Intelligenti (Italy) Wilson R. de Oliveira, Univ. Fed. Rural Pernambuco (Brazil) -- ??????????????????????????????? Felipe M. G. Fran?a, PhD Professor of Computer Science and Engineering Systems Engineering and Computer Science Program, COPPE Universidade Federal do Rio de Janeiro P.O. Box 68511, 21941-972, Rio de Janeiro, RJ, Brazil felipe at ieee.org felipe at cos.ufrj.br ??????????????????????????????? -------------- next part -------------- An HTML attachment was scrubbed... URL: From Adina.Roskies at dartmouth.edu Mon Oct 22 11:36:16 2018 From: Adina.Roskies at dartmouth.edu (adina roskies) Date: Mon, 22 Oct 2018 15:36:16 +0000 Subject: Connectionists: Postdoctoral Researcher sought for neuroethics project on Agency and Neurointerventions Message-ID: <2BCB56C9-A0A2-4287-94BC-0206A841CB9A@dartmouth.edu> Postdoctoral Researcher sought for neuroethics project on Agency and Neurointerventions Applications are invited for the position of Postdoctoral Research Associate at Dartmouth College, to take the lead on a project funded by the BRAIN Initiative entitled ?Assessing the Effects of Deep Brain Stimulation on Agency.? The position is associated with the programs in Cognitive Science and Philosophy at Dartmouth College, and the Dartmouth Geisel School of Medicine. The aim of this project is to use insights from clinical medicine, philosophy, psychology and neuroscience to develop a computerized assay of agency that can be used to track changes in agency due to neurodegenerative and neuropsychiatric diseases and therapies aimed at combatting these changes. In particular, we are interested in being able to describe both desired and unforeseen changes due to deep brain stimulation (DBS) in Parkinson?s Disease, OCD, and treatment-resistant depression. Machine learning techniques will be employed to assess and improve the predictive power of the assay, and the assay will be piloted on normal and clinical populations. Work with DBS patients will be undertaken in collaboration with several clinical centers. A more detailed description of the project is below. The competitive candidate will have interdisciplinary interests and a strong track record of work in data science, with experience in statistical analysis and programming. Experience in machine learning is a plus, but the position will provide opportunities to develop expertise in machine learning. This position is renewable for a period of 3 years from January 2019 (start date flexible). Applicants should submit cover letter, curriculum vitae, one piece of written work, and a statement of research interests, as well as three letters of reference. Applications will be reviewed beginning November 7, 2018, and will continue to be accepted until the position is filled. International applicants are encouraged, as are applications from women and minorities. Dartmouth College is an equal opportunity/affirmative action employer with a strong commitment to diversity and inclusion. We prohibit discrimination on the basis of race, color, religion, sex, age, national origin, sexual orientation, gender identity or expression, disability, veteran status, marital status, or any other legally protected status. Applications by members of all underrepresented groups are encouraged. Further details and a link to the online application portal are available at https://apply.interfolio.com/56650. Project Description Recent advances in neurotechnologies have provided us with the ability to modulate brain function by direct and indirect interventions. Deep Brain Stimulation (DBS) is one such intervention that has already been FDA-approved for certain disorders, and its use has already raised ethical questions about ways in which direct brain stimulation may affect personal identity, autonomy, authenticity and, more generally, agency. Thus far the neuroethical worries have been largely based on anecdotal clinical reports. Further neurotechnological interventions developed as part of the BRAIN initiative are bound to raise similar questions, but we lack a clear framework in which to think of the ethical consequences of these interventions. The overall goal of this project is to articulate such a framework, to enable us to better evaluate and respond to the neuroethical challenges raised by our abilities to alter brain function. The more concrete objectives of our proposal are to 1) develop comprehensive assessment tools to measure changes in agency due to direct brain interventions, 2) to use this tool to assess changes in agency due to brain interventions using DBS patient populations as a test case; and 3) to develop a database to house the data we acquire with these tools to allow us to catalogue the effects and side effects of DBS. This will also make it possible to correlate the effects of DBS with electrode placement and white matter tractography, enabling better prediction of outcomes and aid in understanding of the mechanisms by which DBS works. We will analyze this data machine with machine learning methods to inform a more comprehensive neuroethical analysis of how brain interventions affect agency. Our approach is innovative in that it applies neurophilosophical insights about agency and employs deep learning algorithms in constructing and evaluating these assessment instruments. This contribution is significant in that it will provide a broad-based assessment tool and database that will be a resource for researchers and clinicians using DBS, which could be used to improve therapeutic approaches and informed consent. The data will also inform a framework for further neuroethical thought about brain interventions, allowing us to better identify, articulate and measure changes on ?dimensions of agency.? Finally, the approach is generalizable, and thus could be adapted for use with other brain intervention techniques, such as brain-computer interfaces (BCIs) or pharmacological treatments. Informal enquiries may be directed to Dr. Adina Roskies at adina.roskies at dartmouth.edu. -------------- next part -------------- An HTML attachment was scrubbed... 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Name: Postdoctoral Researcher sought for neuroethics project on Agency and Neurointerventions.pdf Type: application/pdf Size: 39753 bytes Desc: Postdoctoral Researcher sought for neuroethics project on Agency and Neurointerventions.pdf URL: From nguyensmai at gmail.com Mon Oct 22 20:44:46 2018 From: nguyensmai at gmail.com (Nguyen, Sao Mai) Date: Tue, 23 Oct 2018 02:44:46 +0200 Subject: Connectionists: [journals] CfP : Special Issue on Continual Unsupervised Sensorimotor Learning In-Reply-To: References: Message-ID: Dear Colleagues, IEEE Transactions on Cognitive and Developmental Systems is currently running a Special Issue entitled " Continual Unsupervised Sensorimotor Learning" : http://projects.au.dk/socialrobotics/news-events/show/artikel/special-issue-on-continual-unsupervised-sensorimotor-learning/ We would like to invite you to prepare a research article or a comprehensive review to be published in this special issue. AIM AND SCOPE Although machine learning algorithms continue to improve at a rapid pace enabling technologies and products such as autonomous driving cars and sophisticated image and speech recognition, it is often forgotten that these applications represent tailored solutions to specific tasks. Thus it is not clear if or how these autonomous systems can pave the road to general purpose machines envisioned by many. The pursuit for higher levels of autonomy and versatility in robotics is arguably lead by two main factors. Firstly, as we push robots out of the labs and productions lines, it becomes increasingly difficult to design for all possible scenarios that a particular robot might encounter. Secondly, the cost of designing, manufacturing, and maintaining such systems becomes prohibitive. As the algorithms for learning single tasks in restricted environments are improving, new challenges have gained relevance in order to get more autonomous artificial systems. These challenges include multi-task learning, multimodal sensorimotor learning and lifelong adaptation to injury, growth and ageing. Addressing these challenges promise higher levels of autonomy and versatility of future robots. This special issue on Continual Unsupervised Sensorimotor Learning is primarily concerned with the developmental processes involved in unsupervised sensorimotor learning in a life-long perspective, and in particular the emergence of representations of action and perception in humans and artificial agents in continual learning. These processes include action-perception cycle, active perception, continual sensory-motor learning, environmental-driven scaffolding, and intrinsic motivation. The special issue will highlight behavioural and neural data, and cognitive and developmental approaches to research in the areas of robotics, computer science, psychology, neuroscience, etc. Contributions might focus on mathematical and computational models to improve robot performance and/or attempt to unveil the underlying mechanisms that lead to continual adaptation to changing environment or embodiment and continual learning in open-ended environments. Contributions from multiple disciplines including cognitive systems, cognitive robotics, developmental and epigenetic robotics, autonomous and evolutionary robotics, social structures, multi-agent and artificial life systems, computational neuroscience, and developmental psychology, on theoretical, computational, application-oriented, and experimental studies as well as reviews in these areas are welcome. THEMES This special issue aims to report state-of-the-art approaches and recent advances on Continual Unsupervised Sensorimotor Learning with a cross-disciplinary perspective. Topics relevant to this special issue include but are not limited to: Emergence of representations via continual interaction Continual sensory-motor learning Action-perception cycle Active perception Environmental-driven scaffolding Intrinsic motivation Neural substrates, neural circuits and neural plasticity Human and animal behaviour experiments and models Reinforcement learning and deep reinforcement learning for life-long learning Multisensory robot learning Multimodal sensorimotor learning Affordance learning Prediction learning SUBMISSION Manuscripts should be prepared according to the ?Information for Authors? of the journal found at http://cis.ieee.org/component/content/article/7/131-ieee-transactions-on-autonomous-mental-development-information-for-authors.html. Submissions must be done through the IEEE TCDS Manuscript center: https://mc.manuscriptcentral.com/tcds-ieee. During the submission process, please select the category ?SI: Continual Unsupervised Sensorimotor Learning?. IMPORTANT DATES 6th January 2019 ? Paper submission deadline 15th March 2019 ? Notification for authors 31st May 2019 ? Deadline revised papers submission 30th June 2019 ? Final notification for authors 31st July 2019 ? Deadline for camera-ready versions September 2019 ? Expected publication date More information on Continual Unsupervised Sensorimotor Learning http://projects.au.dk/socialrobotics/news-events/show/artikel/special-issue-on-continual-unsupervised-sensorimotor-learning/ GUEST EDITORS Nicol?s Navarro-Gerrero Aarhus University, Aarhus, Denmark nng at eng.au.dk Sao Mai Nguyen IMT Atlantique, Francenguyensmai at gmail.com Erhan ?ztop ?zye?in University, Turkeyerhan.oztop at ozyegin.edu.tr Junpei Zhong National Institute of Advanced Industrial Science and Technology (AIST), Japanjoni.zhong at aist.go.jp ---- Nguyen Sao Mai nguyensmai at gmail.com Researcher in Cognitive Developmental Robotics http://nguyensmai.free.fr -------------- next part -------------- An HTML attachment was scrubbed... URL: From Pavis at iit.it Tue Oct 23 05:40:14 2018 From: Pavis at iit.it (Pavis) Date: Tue, 23 Oct 2018 09:40:14 +0000 Subject: Connectionists: PostDoc on Visual Understanding for Cultural Heritage Technologies (CCHT@Ca'Foscari) - [ Postdoc ] BC 75119 In-Reply-To: References: Message-ID: <3548fa02f9e64edc8b6b69a3d47c0de4@iit.it> PostDoc on Visual Understanding for Cultural Heritage Technologies (CCHT at Ca'Foscari) - [ Postdoc ] BC 75119 Workplace: Venezia, IIT, Italy Added on: 22/10/2018 - Expires on 21/11/2018 The IIT center at Ca' Foscari University of Venice - Center for Cultural Heritage Technology at Ca'Foscari (CCHT at Ca'Foscari) has the mission to research and promote new technologies and to extend existing techniques for preservation and analysis of the invaluable Cultural Heritage assets managed by cities, galleries, libraries, archives and museums across different fields of art. CCHT at Ca'Foscari is currently seeking to appoint a Visual Understanding Postdoc. The selected candidate will join an interdisciplinary team of researchers, contributing to the development of next-generation 3D digitization and machine learning approaches applied to the Cultural Heritage (CH) and Digital Humanities (DH) domain. Required qualifications: *A Ph.D. in computer science or related field (with specialization in either computer vision, information retrieval or machine learning); *Proficiency in programming languages, in particular, Python, C/C++, and MATLAB; *Experience of visual recognition or understanding in 2D & 3D, e.g. attribute recognition, object recognition, relationship detection, and their multi-view equivalence; *Practical experience on Deep Learning algorithms and relevant platforms for geometric learning (e.g. TensorFlow, PyTorch, Theano, Caffe); *Publication in major Computer Vision and/or Computer Graphics conferences/journals (e.g. CVPR, ICCV, ECCV, SIGGRAPH, Eurographics, ToG, TPAMI, IJCV, IVC, CVIU); *Good communication skills and ability to cooperate; *Proficient in English language (written and oral). Desirable skills: *Knowledge of OpenCV, PCL, and Open3D libraries; *Experience in graph structure applications e.g. matching, retrieval or inference; *Knowledge of SPARQL / CIDOC; *Experience in cultural heritage knowledge data. The successful candidate will be offered a salary commensurate to experience and skills. The call will remain open until the position is filled but the first deadline for evaluation of candidates will be November 21, 2018. Please send your application to ccht at iit.it and applications at iit.it quoting "CCHT Visual Understanding Postdoc - BC 75119" in the e-mail subject. Your application shall contain a detailed CV, a one-page research statement and contact information of two referees. Fondazione Istituto Italiano di Tecnologia (http://www.iit.it) is a non-profit institution created with the objective of promoting technological development and higher education in science and technology. Research at IIT is carried out in highly innovative scientific fields with state-of-the-art technology. Istituto Italiano di Tecnologia is an equal opportunity employer that actively seeks diversity in the workforce. Please note that the data that you provide will be used exclusively for the purpose of professional profiles' evaluation and selection and in order to meet the requirements of Istituto Italiano di Tecnologia. Your data will be processed by Istituto Italiano di Tecnologia, based in Genoa, Via Morego 30, acting as Data Controller, in compliance with the rules on protection of personal data, including those related to data security. Please also note that, pursuant to articles 15 et. seq. of European Regulation no. 679/2016 (General Data Protection Regulation), you may exercise your rights at any time by contacting the Data Protection Officer (phone +39 010 71781 - email: dpo at iit.it) -------------- next part -------------- An HTML attachment was scrubbed... URL: From d.goodman at imperial.ac.uk Tue Oct 23 11:31:55 2018 From: d.goodman at imperial.ac.uk (Dan Goodman) Date: Tue, 23 Oct 2018 16:31:55 +0100 Subject: Connectionists: PhD positions in the group of Dan Goodman at Imperial College Message-ID: <845257dc-2571-cd69-7e9e-cc4c6f5d7370@imperial.ac.uk> One or more PhD positions in theoretical and computational neuroscience are available in the group of Dan Goodman at Imperial College London (http://neural-reckoning.org). I am interested in supervising students with a strong mathematical, computational or neuroscience background. Projects could be carried out in several possible areas relating to the work in the group. Some suggestions for topics that would be interesting to me are below, but I'm very happy to consider other possibilities. In addition to working within the group, studying at Imperial College provides excellent opportunities for interacting with other theoretical and experimental researchers, both at Imperial and in the many neuroscience groups in London. Suggested areas include: * Spiking neural networks * Auditory and other sensory systems * Machine learning and neuroscience * Simulation and data analysis For more detail, see: http://neural-reckoning.org/openings.html Applicants should initially send me a brief CV and cover letter with a description of research interests or a proposed project, and will eventually have to formally apply through the standard Imperial College mechanism (http://www.imperial.ac.uk/electrical-engineering/study/phd/). There are no strict deadlines, although chances of success are higher for earlier applications as I will consider them as they arrive. EU students from outside the UK are particularly encouraged to apply before Christmas. Funded offers made before Brexit day (March 29) will be honoured by Imperial no matter what happens in the Brexit negotiations, and the last funding panel meeting before that will probably be in early February. So, applying before Christmas means we will have time to process the application and arrange an interview before that meeting. Imperial College requirements: * General requirements: https://www.imperial.ac.uk/study/pg/apply/requirements/ * Country-specific minimum grades: https://www.imperial.ac.uk/study/pg/apply/requirements/pgacademic/ Dan Goodman From stevejryan at gmail.com Tue Oct 23 12:34:54 2018 From: stevejryan at gmail.com (Steve Ryan) Date: Tue, 23 Oct 2018 12:34:54 -0400 Subject: Connectionists: 2 PostDoc opportunities in canine neuroimaging at Harvard Message-ID: The new Evolutionary Neuroscience Lab in the Harvard University Department of Human Evolutionary Biology will be opening in 2019 and looking for two new postdocs, with positions available for research techs and undergraduates to follow. See description below and attached. https://projects.iq.harvard.edu/evolutionaryneurosciencelab/positions-available Positions Available The Evolutionary Neuroscience Lab will be opening in the Department of Human Evolutionary Biology in January 2019. The following positions are available. Postdoctoral Fellow Position in Neuroimaging of Learned Skills The focus of the position will be to study neurodevelopmental adaptations for the acquisition of learned skills. The project involves longitudinal neuroimaging of military working dogs, from puppyhood through adulthood, as they progress through a formal on-base training regimen. Several weeks of paid travel per year will be required to a research site in Texas. This is a one-year position, expected to begin in spring or summer 2019, with possibility of renewal dependent upon adequate funding and satisfactory performance. The research will take place in the Evolutionary Neuroscience Laboratory directed by Dr. Hecht and located in the Peabody Museum on Harvard University?s Cambridge, Massachusetts campus, and on-site at the Lackland Air Force Base outside San Antonio. A doctoral degree is required for this position. Desired qualifications include research in neuroscience, neuroimaging, development, and/or animal behavior. The project will require working with dogs and coordinating with an interdisciplinary research team that will include scientists, veterinarians, dog handlers and trainers, and military personnel. This research is non-invasive. Postdoctoral Fellow Position in Neural Adaptations for Social Behavior The focus of the position will be to study neuroanatomical adaptations related to social behavior using histology and digital microscopy. This is a one-year position, expected to begin in spring or summer 2019, with possibility of renewal dependent upon adequate funding and satisfactory performance. The research will take place in the Evolutionary Neuroscience Laboratory directed by Dr. Hecht and located in the Peabody Museum on Harvard University?s Cambridge, Massachusetts campus. A doctoral degree is required for this position. Desired qualifications include research in neuroscience, neuroanatomy, histology, microscopy, and social behavior. The project will require working with fixed brain specimens in a wet lab. To Apply Please submit a letter of interest, an updated CV, and the names of three references by email to Dr. Erin Hecht at erin_hecht at fas.harvard.edu. Evaluation will begin at the time the advertisement is placed and will continue until the position is filled. Other Positions Positions will be available for undergraduate researchers and one or two graduate students. Students who are interested in working in the lab should email Dr. Hecht at erin_hecht at fas.harvard.edu. Additionally, a position will be available for a research technician with experience in histology. A job listing will be posted soon. Best, -Steve Ryan -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: Hecht Neuroimaging Postdoctoral Fellow Advertisement 2018.pdf Type: application/pdf Size: 77214 bytes Desc: not available URL: From T.Nowotny at sussex.ac.uk Wed Oct 24 04:22:12 2018 From: T.Nowotny at sussex.ac.uk (Thomas Nowotny) Date: Wed, 24 Oct 2018 08:22:12 +0000 Subject: Connectionists: =?utf-8?q?8_studentships_available_from_the_Unive?= =?utf-8?q?rsity_of_Sussex=E2=80=99s_Leverhulme_Doctoral_Scholarship_Progr?= =?utf-8?q?amme=3A_From_Sensation_and_Perception_to_Awareness?= Message-ID: <9131D95D-8AC6-4B15-8DF5-2072EAE9084E@sussex.ac.uk> Dear Connectionists, The University of Sussex invites applications for PhD studentship awards within its Leverhulme Doctoral Scholarship Programme entitled ?From Sensation and Perception to Awareness?. Projects are offered within and across a large variety of disciplines. The Programme will support an intake of 8 students starting in September 2019. For more details and how to apply, see https://www.findaphd.com/search/PhdDetails.aspx?CAID=3783 Suggested PhD topics are here: https://www.sussex.ac.uk/sensation/applications The deadline for applications is 31 January 2019. Best regards, Thomas -- Prof Thomas Nowotny Director of Research and Knowledge Exchange School of Engineering and Informatics University of Sussex Falmer, Brighton BN1 9QJ, UK Phone: +441273678593 FAX: +441273877873 -------------- next part -------------- An HTML attachment was scrubbed... URL: From m.plumbley at surrey.ac.uk Thu Oct 25 05:01:19 2018 From: m.plumbley at surrey.ac.uk (m.plumbley at surrey.ac.uk) Date: Thu, 25 Oct 2018 09:01:19 +0000 Subject: Connectionists: Making Sense of Sounds Data Challenge deadline soon: 30 Oct 2018 Message-ID: Dear Connectionists, The submission deadline for the "Making Sense of Sounds" (MSoS) Data Challenge (http://cvssp.org/projects/making_sense_of_sounds/site/challenge/) is fast approaching: ** Submission deadline: 30 October 2018 ** Direct links: * Development & Evaluation data: http://cvssp.org/projects/making_sense_of_sounds/site/challenge/#download * Submission system: http://cvssp.org/projects/making_sense_of_sounds/site/challenge/#submission_opened We have also provided a deep learning baseline: http://cvssp.org/projects/making_sense_of_sounds/site/challenge/#baseline The task in the MSoS Challenge is to classify audio files as belonging to one of five broad categories derived from human classification experiments: Nature, Human, Music, Effects, or Urban. We call for machine systems to attempt to replicate this human ability of category generalisation. The MSoS Challenge is jointly organized by University of Salford and University of Surrey. The results of the MSoS Challenge will be announced at the DCASE 2018 Workshop: http://dcase.community/workshop2018/ For more information about the challenge and how to take part, see: http://cvssp.org/projects/making_sense_of_sounds/site/challenge/ Important dates: * Submission deadline: 30 Oct 2018 * Results announced: 19/20 Nov 2018 (at DCASE 2018 Workshop) Contact: MSoS.challenge at gmail.com We look forward to your submission! Mark Plumbley On behalf of the MSoS Challenge organisers -- Prof Mark D Plumbley Professor of Signal Processing Centre for Vision, Speech and Signal Processing (CVSSP) University of Surrey, Guildford, Surrey, GU2 7XH, UK Email: m.plumbley at surrey.ac.uk =================================================================================== DCASE 2018 Workshop on Detection and Classification of Acoustic Scenes and Events 19 - 20 November 2018, Surrey, UK http://dcase.community/workshop2018/ =================================================================================== From amir.aly at em.ci.ritsumei.ac.jp Thu Oct 25 06:36:47 2018 From: amir.aly at em.ci.ritsumei.ac.jp (Amir Aly) Date: Thu, 25 Oct 2018 19:36:47 +0900 Subject: Connectionists: SoAIR 2019: IEEE-RAS Spring School on "Social and Artificial Intelligence for User-Friendly Robots" in Japan Message-ID: CALL FOR APPLICATIONS **Apologies for cross posting ** We are pleased to call for applications for the IEEE-RAS spring school on: "*Social and Artificial Intelligence for User-Friendly Robots*" * Which will be held from 17-24 March, 2019 in Shonan Village, Japan *after the Human-Robot Interaction (HRI) conference that will be held in the near South Korea. *Webpage: **https://inic8.bitbucket.io/SoAIR19/* *I. Aim and Scope *Autonomous and intelligent systems are progressively moving into spaces, which have previously been predominantly shaped by human agency. Unlike in the past where machines obediently served their human operators, machines now increasingly act without the intervention of a human. Artificial intelligence is meeting new challenges in the world, though human-like intelligence may still be a distant goal. Robots in factories are coming out of their cages. Autonomous cars are being tested on streets with regular human-driven cars. The private household is changing with the appearance of not only robotic vacuum cleaners, but also with the first-generation of social robots and smart devices. The challenges that face both the robotics and artificial intelligence communities are how the necessary intelligence for such new environments can be created as well as how to make artificial agents capable of not only solving tasks at hand but also considering social environments around them during interaction with human users so as to behave appropriately. Within the school, we plan to address the tension created by the balance between task-specific artificial intelligence and the demands of sociability required to function effectively in human-centered environments. ** *This spring school is a Technical Education Program (TEP) endorsed and supported by IEEE-RAS*. ** *The school aims at bridging the gap between social and cognitive Human-Robot Interaction (HRI), Artificial Intelligence (AI), and Autonomous Vehicles (AV) through high-level talks and hands-on workshops (the program will be announced soon).* *II. Keynote Speakers (More Speakers in HRI, AI, and Autonomous Vehicles will join the list soon): * 1. * Jun Tani *? Okinawa Institute of Science and Technology (OIST), Japan 2. *Daniele Magazzeni *? King's College London, UK 3. * Yukie Nagai *? National Institute of Information and Communications Technology (NICT), Japan 4. * Tetsuya Ogata* ? Waseda University, Japan 5. *Maya Cakmak *? University of Washington, USA 6. *Mohamed Chetouani *? University of Pierre and Marie Curie (UPMC), France 7. *Agnieszka Wykowska *? Italian Institute of Technology (IIT), Italy 8. *Tetsunari Inamura *? National Institute of Informatics (NII), Japan 9. *Amit Kumar Pandey *? SoftBank (Aldebaran) Robotics, France 10. *Francesco Maurelli *? Jacobs University, Germany (*A special talk about preparing funding proposals*) *III. Submission * The applications must include the following files (combined into one file). No other documents would be necessary (More information is available on the school's webpage). 1. *Curriculum vitae*: A two pages or less of CV detailing relevant aspects of the candidate's academic career that demonstrates her/his relevance to the school theme. 2. *Research abstract*: A 200 word research abstract that the candidate intends to present during the school. 3. *Letter of recommendation*: A short letter from the academic advisor or the employer of the candidate supporting her/his application. *Application submission*: Please use the following EasyChair web link:* Application Submission .* *IV. Important Dates * 1. Application submission: *20-December, 2018 * 2. Notification of acceptance: *28-December, 2018 * 3. Spring School: *17-24 March, 2019* *V. Organizers * 1. *Amir Aly *? Ritsumeikan University ? Japan 2. *Franziska Kirstein *? Blue Ocean Robotics, Denmark 3. * Shashank Pathak *? Visteon Corporation, Germany --------------------- *Amir Aly, Ph.D.* Senior Researcher Emergent Systems Laboratory College of Information Science and Engineering Ritsumeikan University 1-1-1 Noji Higashi, Kusatsu, Shiga 525-8577 Japan -------------- next part -------------- An HTML attachment was scrubbed... URL: From kyunghyun.cho at nyu.edu Thu Oct 25 07:31:30 2018 From: kyunghyun.cho at nyu.edu (Kyunghyun Cho) Date: Thu, 25 Oct 2018 07:31:30 -0400 Subject: Connectionists: =?utf-8?q?NYU_Shanghai_-_TENURED/TENURE-TRACK_?= =?utf-8?q?=E2=80=93_DATA_SCIENCE?= Message-ID: *TENURED/TENURE-TRACK ? DATA SCIENCE* *Position Description* NYU Shanghai welcomes applications for three Tenured or Tenure-Track position in Data Science. The search is not restricted to any rank and outstanding candidates at all levels are encouraged to apply. NYU Shanghai is adding new open-rank faculty positions to build its strength in data sciences, computational and statistical sciences, through a cluster hire. We seek outstanding data scientists with experience either in the mathematical or CS foundations of Data Science and Machine Learning, or in applying advanced statistical and computational methods to the sciences or the social sciences. A compelling vision for their research program at NYU Shanghai, and a demonstrated commitment to interdisciplinary research and education will be needed. NYU Shanghai has a vibrant undergraduate program in Data Science, and the Data Science group at NYU Shanghai is built in collaboration with the Center for Data Sciences, and with the Courant Institute of Mathematics, at NYU in New York. Affiliated, associated, or joint positions may be possible. Terms of employment at NYU Shanghai are comparable to U.S. institutions with respect to research start-up funds and compensation, and they include housing subsidies and educational subsidies for children. Faculty may also spend time at NYU New York and other sites of the NYU Global Network, engaging in both research and teaching. *Qualifications* Candidates must hold a PhD in Data Science, Mathematics, Computer Science, Statistics, or a related field (or expect it by the start date). *Application Instructions* Candidates must submit: ? (1) Cover Letter ? (2) CV ? (3) Statement on Current/Future Research Interests ? (4) Statement on Teaching Interests ? (5) Names and Email Addresses for Three (3) References (junior candidates only) Review of applications will begin immediately and will continue until the position is filled. Please visit our website at *http://shanghai.nyu.edu/en/about/work-here/open-positions-faculty * for instructions and other information on how to apply. Additional information about the position can be obtained through writing to *nyush.faculty.recruitment at nyu.edu *. *About NYU Shanghai* NYU Shanghai is the third degree-granting campus within New York University?s global network. It is the first higher education joint venture in China authorized to grant degrees that are accredited in the U.S. as well as in China. All teaching is conducted in English. A research university with liberal arts and science at its core, it resides in one of the world's great cities with a vibrant intellectual community. NYU Shanghai recruits scholars of the highest caliber who are committed to NYU's global vision of transformative teaching and innovative research and who embody the global society in which we live. NYU?s global network includes degree-granting campuses in New York, Shanghai, and Abu Dhabi, complemented by eleven additional academic centers across five continents. Faculty and students circulate within the network in pursuit of common research interests and cross-cultural, interdisciplinary endeavors, both local and global. NYU Shanghai is an equal opportunity employer committed to equity, diversity and social inclusion. We strongly encourage applications from individuals who are under-represented in the profession, across color, creed, race, ethnic and national origin, physical ability, and gender and sexual identity. NYU Shanghai affirms the value of differing perspectives on the world as we strive to build the strongest possible university with the widest reach. EOE/AA/Minorities/Females/Vet/Disabled/Sexual Orientation/Gender Identity Employer -------------- next part -------------- An HTML attachment was scrubbed... URL: From sergio.escalera.guerrero at gmail.com Thu Oct 25 14:21:06 2018 From: sergio.escalera.guerrero at gmail.com (Sergio Escalera) Date: Thu, 25 Oct 2018 20:21:06 +0200 Subject: Connectionists: 3-year full-funded Postdoc position in Computer vision for monitoring people with reduced autonomy Message-ID: A spin-off company in Barcelona is looking for candidates for a full-funded 3-years postdoc position in computer vision. The work consists on developing and applying innovative computer vision methods for monitoring and perform intelligent recognition of risks events of people with reduced autonomy in indoor environments. While the work is within the scope of the company business model, it is expected the new implementations to have innovative value and publish associated research articles. Long-term contract after post-doc position will be also considered. The candidate should demonstrate a high knowledge in computer vision models and their low-level implementation, including advanced knowledge in the design of deep learning architectures. Candidate should send a letter of interest and curriculum to: sergio.escalera.guerrero at gmail.com -- *Dr. Sergio Escalera Guerrero*Head of Human Pose Recovery and Behavior Analysis Lab Project Manager at the Computer Vision Center Director of ChaLearn Challenges in Machine Learning Associate professor at University of Barcelona / Universitat Oberta de Catalunya / Aalborg Univ. / Dalhousie University Phone:+34934020853 Email: sergio.escalera.guerrero at gmail.com / Webpage: http://www.sergioescalera.com/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From sageev at vectorinstitute.ai Thu Oct 25 11:00:13 2018 From: sageev at vectorinstitute.ai (Sageev Oore) Date: Thu, 25 Oct 2018 12:00:13 -0300 Subject: Connectionists: Tenure-Stream Position in Artificial Intelligence for Medicine (Dalhousie University, Canada) Message-ID: <81A09D58-233C-4803-A184-28BDB09E1DF5@vectorinstitute.ai> The Faculty of Computer Science at Dalhousie University (https://www.dal.ca/faculty/computerscience.html ) invites applications for a Tenure-Stream Assistant Professor Position. We are seeking outstanding candidates with a strong demonstrated track record of expertise in Artificial Intelligence, with a focus on medical applications. The ideal candidate will preferably also have some background in one or more subfields of machine learning, such as (but not limited to) any of the following: Bayesian reasoning, reinforcement learning, human-in-the-loop, transfer learning, interpretable machine learning. The successful candidate will be expected to develop collaborations with researchers in the Faculty of Medicine, where more than 300 researchers work in areas as diverse as neuroscience, vaccinology, cancer research, drug development, and other areas of Medicine. Dalhousie University is located in Halifax, Nova Scotia (http://www.halifaxinfo.com ), which is the largest city in Atlantic Canada and affords its residents a high quality of life. Dalhousie University is a member of the U15 research-intensive universities in Canada. The Faculty of Computer Science is a research-intensive faculty within Dalhousie, with 40 faculty members, including Tier I and Tier II CRCs, and over 1400 students, one third of whom are graduate students at the Master?s or Doctoral level. The Faculty offers Bachelor of Computer Science, Bachelor of Applied Computer Science, Master of Computer Science, Master of Applied Computer Science, and PhD programs. The Faculty also partners with other Faculties in the University to offer the Master of Electronic Commerce, Master of Health Informatics, and Master of Science, Computational Biology and Bioinformatics programs, and is an active participant in the Interdisciplinary PhD program. The full advertisement is available at https://tinyurl.com/FCSAIforMedicine Review of applications will commence November 10th, 2018, and will continue until the position is filled. -------------- next part -------------- An HTML attachment was scrubbed... URL: From arokem at gmail.com Thu Oct 25 12:03:39 2018 From: arokem at gmail.com (Ariel Rokem) Date: Thu, 25 Oct 2018 09:03:39 -0700 Subject: Connectionists: Postdoc in computational neuroscience and data science at the University of Washington (Seattle) Message-ID: A post-doc position is available at the University of Washington (Seattle) to work with Adrienne Fairhall (Computational Neuroscience Center ) and Ariel Rokem (eScience Institute ). The successful applicant will develop open-source software and build and maintain systems for sharing, integration and cutting-edge analysis of datasets from a large-scale collaboration focused on the neural circuits involved in learning in human and non-human primate. This distributed collaboration, funded through a grant from the BRAIN Initiative, includes researchers from UW, as well as from UC Berkeley, NYU, The University of Chicago, and UC Irvine. The position is initially offered for 1 year, with the possibility of extension beyond this period, based on mutual agreement. Desired qualifications: PhD in neuroscience, computer science, electrical engineering, statistics or related fields. Extensive experience programming in Python/Matlab and in neural data analysis. Experience contributing to open-source software for data analysis is a plus, as is experience working in cloud-computing environments (e.g., AWS) and experience with tools for scalable data analysis (e.g., Spark). We will be at the Society for Neuroscience conference. To arrange meetings for informational interviews during the conference, please contact Ariel Rokem: arokem at uw.edu -------------- next part -------------- An HTML attachment was scrubbed... URL: From robert.guetig at charite.de Thu Oct 25 16:02:39 2018 From: robert.guetig at charite.de (=?Windows-1252?Q?G=FCtig=2C_Robert?=) Date: Thu, 25 Oct 2018 20:02:39 +0000 Subject: Connectionists: Open PhD and Postoc positions in Berlin: Learning in spiking neural networks References: <82E2AF1F2BDD6A4BA2407311EEE44A862354FB@s-mx14-mb0106.charite.de> Message-ID: <82E2AF1F2BDD6A4BA2407311EEE44A8623550D@s-mx14-mb0106.charite.de> The newly formed research group "Mathematical modeling of neuronal learning", headed by Robert G?tig is seeking highly motivated researchers at the PhD and postdoctoral level to study information processing and learning in spiking neural networks. The group is funded by the Berlin Institute of Health and located at the Charit? Medical School in the center of Berlin. Our close proximity to the NeuroCure Cluster of Excellence and the Bernstein Center for Computational Neuroscience facilitates close interactions between our group and Berlin?s vibrant and growing neuroscience community. We use analytical and numerical modeling techniques to identify the computational principles underlying spike based information processing and learning in the central nervous system and to understand how these principles are implemented by biological processes. Open projects center around, but are not limited to, the recently developed tempotron family of spiking neuronal network models (e.g. G?tig & Sompolinsky 2006; G?tig 2016). The positions are available immediately. Applicants should have a strong background in physics, mathematics, computer science, computational neuroscience or a related field and a keen interest in neurobiology and machine learning. Good programming skills (e.g. in C and/or Python) are important and experience with numerical simulations highly beneficial. Previous exposure to neuroscience is preferred but not required. Applications will be considered until all positions are filled. Please send your application or questions to Robert G?tig (robert.guetig at charite.de). When applying please include a detailed CV (including degrees, current academic transcripts, and publication record) and the names and contact information of two referees. From bpaassen at techfak.uni-bielefeld.de Thu Oct 25 16:05:36 2018 From: bpaassen at techfak.uni-bielefeld.de (Benjamin Paassen) Date: Thu, 25 Oct 2018 22:05:36 +0200 Subject: Connectionists: Call for Papers: Embeddings and Representation Learning for Structured Data (ESANN 2019 Special Session) Message-ID: <23836e5c-046a-6666-5a3a-1c5eb7a9ea80@techfak.uni-bielefeld.de> Dear Connectionists subscribers, this is a reminder regarding our call for papers for contributions on 'Embeddings and Representation Learning for Structured Data', such as sequences, trees, and graphs. We will host a special session on this topic at next year's European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2019; 24 - 26 April 2019 in Bruges, Belgium). We cordially invite you to submit your work to this special session. The submission deadline is at *November 19th, 2018*. # DESCRIPTION Learning models of structured data, such as sequences, trees, and graphs, has become a rich and promising research objective in many fields of machine learning, such as (deep) neural networks, probabilistic models, kernels, metric learning, and dimensionality reduction. All these seemingly disparate approaches are connected by their construction of vectorial representations and embeddings of structured data, be it implicit or explicit, fixed or learned, deterministic or stochastic. Such embeddings can not only be utilized for classification or regression, but for generation of structured data, visualization, and interpretation. # TOPICS OF INTEREST This session calls for contributions which provide novel methods to construct embeddings of structured data, new methods to utilize existing embeddings, and theoretic research regarding the properties of such embeddings. More specifically, topics of interest include, but are not limited to, the following: * Recurrent and recursive neural networks for structured data * Neural networks for graphs * Auto-Encoding models for structured data * Generative adversarial networks for structured data * Representation Learning for structured data * Deep models of structured data * Sequence, tree, and graph kernels with explicit vectorial representations * Kernel methods for structured data * Markov models for representation of sequences, trees, or graphs * Theoretical considerations on learning theory and dimensionality of embeddings of structured data * Metric learning for structured data * Dimensionality reduction techniques for structured data * Interpretability of vectorial representations of structured data # SUBMISSION Submissions must be made on the ESANN website via the following link: https://www.elen.ucl.ac.be/esann/index.php?pg=submission Each paper submission will be peer-reviewed and authors will receive a notification of acceptance at *January 31st, 2019* as either an oral or poster presentation. All papers are six pages and will be published in the ESANN proceedings ( https://www.elen.ucl.ac.be/esann/proceedings/electronicproceedings.htm ). # IMPORTANT DATES Submission of papers: 19 November 2018 Notification of acceptance: 31 January 2019 ESANN conference: 24 - 26 April 2019 # SPECIAL SESSION ORGANIZERS * Benjamin Paa?en, Bielefeld University, Germany * Claudio Gallicchio, University of Pisa, Italy * Alessio Micheli, University of Pisa, Italy * Alessandro Sperduti, University of Pisa, Italy From n.strisciuglio at rug.nl Thu Oct 25 16:46:52 2018 From: n.strisciuglio at rug.nl (Nicola Strisciuglio) Date: Thu, 25 Oct 2018 22:46:52 +0200 Subject: Connectionists: Extended deadline 7 Nov - [CfP] APPIS 2019 in Las Palmas Message-ID: The 2nd International Conference on Applications of Intelligent Systems, APPIS 2019 , will be held on 7-12 January 2019 in Las Palmas de Gran Canaria, Spain. APPIS 2019 is organized by the University of Groningen and the University of Las Palmas de Gran Canaria, and includes a Winter School on Machine Learning (WISMAL 2019) . APPIS 2019 welcomes submission of *abstracts* (1-2 pages) and*full papers* (4-6 pages) related, but not limited to the following topics: * Machine learning and representation learning * Images, videos and time-series analysis * Statistical and structural pattern recognition * Data visualization and dimensionality reduction * Robotics * Intelligent systems in health and medicine * Cyber computing and security * Bio-informatics * Data mining * Cognitive discovery * Algorithms for embedded and real-time systems * Semantic technologies * Intelligent buildings * Intelligent sensors and sensor networks * Augmented reality * Adaptive systems * Fuzzy systems * Human-machine interaction * Natural language processing * Situation awareness systems * Recommender systems Papers must be submitted electronically, with *deadline November 7th (23:59:59 CET)*, through the APPIS 2019 conference web site in pdf format and must conform to the ACM template and style file. Proceedings will be published in ACM ICPS. Each accepted paper must be presented by one of the authors and accompanied by at least one full registration fee payment (250 Euro), to guarantee publication in the proceedings. In order to be published in the conference proceedings, *abstract submissions* need to be extended to full papers before the conference (*deadline January 5, 2019*) Find more information in the submission page . We look forward to meet you in Las Palmas de Gran Canaria! Best regards, Nicolai Petkov Nicola Strisciuglio Carlos Travieso-Gonzalez -------------- next part -------------- An HTML attachment was scrubbed... URL: From C.Campbell at bristol.ac.uk Fri Oct 26 05:58:15 2018 From: C.Campbell at bristol.ac.uk (Colin Campbell) Date: Fri, 26 Oct 2018 09:58:15 +0000 Subject: Connectionists: Research Associate / Senior Research Associate in Bioinformatics Message-ID: We are offering an exciting new position for a research associate or senior research associate in the Intelligent Systems Laboratory at the University of Bristol. Please get in touch with me if you are interested in finding out more, and please forward to anyone else you think may be interested. Colin Campbell (contact details: https://seis.bristol.ac.uk/~enicgc/index.htm) Summary below: for full details and to apply please visit: www.bristol.ac.uk/jobs Job reference: ACAD103613 Closing date: 9th December 2018. Research Associate/ Senior Research Associate in Bioinformatics We are seeking a talented research associate / senior research associate with extensive experience in bioinformatics, machine learning or computational statistics and who is interested in the application of these techniques within genomic medicine. Within this area an ongoing theme has been the development of integrative classifiers for predicting the functional impact of human genetic variation i.e. if variation is pathogenic (a disease-driver) or neutral (see e.g. fathmm.biocompute.org.uk, cscape.biocompute.org.uk). We are very interested in using bioinformatics and machine learning methods to find disease subtypes via unsupervised learning, find variants acting as disease-drivers, predict course of disease, predict response to treatment and find drug targets, for example. A further interest is the development of novel machine learning based methods which support this overall objective. The project is linked to a large MRC Stratified Medicine Initiative grant with the goal of using bioinformatics and machine learning to define more personalized treatment regimes. A major objective of the project will be to work with Prof. Moin Saleem (University of Bristol) and his team to use these methods to identify disease-drivers responsible for nephrotic syndrome and chronic kidney disease and to further our understanding and ability to treat these diseases. The successful candidate will be appointed at either Senior Research Associate (grade J) or Research Associate (grade I) depending on experience and prior publications. The post-holder will have the opportunity to develop their own research portfolio within the programme and will be supported in their career progression. Candidates for the position should have strong mathematical and computational skills with experience in Python, R and other programming languages, experience working with a range of bioinformatic data sources and having the capability to devise novel methods. The successful applicant will be based within the Intelligent Systems Laboratory of the University of Bristol and will also work with Dr. Tom Gaunt (MRC IEU Bioinformatics Lead). Salary: ?33,199-?37,345 (Grade I) or ?37,345-?42,036 (Grade J) Contract type: open ended. The University is committed to creating and sustaining a fully inclusive culture. We welcome applicants from all backgrounds and communities. -------------- next part -------------- An HTML attachment was scrubbed... URL: From george at cs.ucy.ac.cy Fri Oct 26 09:56:05 2018 From: george at cs.ucy.ac.cy (George Angelos Papadopoulos) Date: Fri, 26 Oct 2018 16:56:05 +0300 Subject: Connectionists: The 27th ACM Conference on User Modeling, Adaptation and Personalization (UMAP 2019): Second Call for Papers In-Reply-To: <9D907F9B-A04A-43F0-8623-6D92E4132AC9@cs.ucy.ac.cy> References: <9D907F9B-A04A-43F0-8623-6D92E4132AC9@cs.ucy.ac.cy> Message-ID: <46CA4E92-4B9B-4D1B-8B60-A1D0C2701DE3@cs.ucy.ac.cy> *** SECOND CALL FOR PAPERS *** 27th ACM International Conference on User Modeling, Adaptation and Personalization (ACM UMAP 2019) Golden Bay Beach Hotel 5*, Larnaca, Cyprus, June 9-12, 2019 https://www.um.org/umap2019/ Abstracts due: January 25, 2019 (mandatory) Papers due: February 1, 2019 BACKGROUND AND SCOPE ACM UMAP, "User Modeling, Adaptation and Personalization", is the premier international conference for researchers and practitioners working on systems that adapt to individual users, to groups of users, and that collect, represent, and model user information. ACM UMAP is sponsored by ACM SIGCHI and SIGWEB. The proceedings are published by ACM and will be part of the ACM Digital Library. ACM UMAP covers a wide variety of research areas where personalization and adaptation may be applied. This include (but is in no way limited to) a number of domains in which researchers are engendering significant innovations based on advances in user modeling and adaptation, recommender systems, adaptive educational systems, intelligent user interfaces, e-commerce, advertising, digital humanities, social networks, personalized health, entertainment, and many more. This year the conference hosts three new tracks, one on privacy and fairness, one on personalized music access, and one on personalized health. CONFERENCE TRACKS For details, see the conference website ( https://www.um.org/umap2019/ ). ? Track 1 - Personalized Recommender Systems ? Track 2 - Adaptive Hypermedia and the Semantic Web ? Track 3 - Intelligent User Interfaces ? Track 4 - Personalized Social Web ? Track 5 - Technology-Enhanced Adaptive Learning ? Track 6 - Privacy and Fairness ? Track 7 - Personalized Music Access ? Track 8 - Personalized Health SUBMISSION AND REVIEW PROCESS Papers have to be submitted through EasyChair: https://easychair.org/conferences/?conf=acmumap2019 Long (8 pages + references) and Short (4 pages + references) papers in ACM style, peer reviewed, original, and principled research papers addressing both the theory and practice of UMAP and papers showcasing innovative use of UMAP and exploring the benefits and challenges of applying UMAP technology in real-life applications and contexts are welcome. Long papers should present original reports of substantive new research techniques, findings, and applications of UMAP. They should place the work within the field and clearly indicate innovative aspects. Research procedures and technical methods should be presented in sufficient detail to ensure scrutiny and reproducibility. Results should be clearly communicated and implications of the contributions/findings for UMAP and beyond should be explicitly discussed. Short papers should present original and highly promising research or applications. Merit will be assessed in terms of originality and importance rather than maturity, extensive technical validation, and user studies. Papers must be formatted using the ACM SIG Standard (SIGCONF) proceedings template: https://www.acm.org/publications/proceedings-template . All accepted papers will be published by ACM and will be available via the ACM Digital Library. At least one author of each accepted paper must register for the conference and present the paper there. IMPORTANT DATES ? Abstracts: January 25, 2019 (mandatory) ? Full paper: February 1, 2019 ? Notification: March 11, 2019 ? Camera-ready: April 3, 2019 Note: The submission time is 11:59pm AoE time (Anywhere on Earth). GENERAL CHAIRS ? George A. Papadopoulos, University of Cyprus, Cyprus ? George Samaras, University of Cyprus, Cyprus ? Stephan Weibelzahl, PFH Private University of Applied Sciences, G?ttingen, Germany RELATED EVENTS Separate calls will be later sent for Workshops and Tutorials, Doctoral Consortium, Posters, Late Breaking Results and Theory, Opinion and Reflection works, as they have different deadlines and submission requirements. -------------- next part -------------- An HTML attachment was scrubbed... URL: From falk.lieder at berkeley.edu Fri Oct 26 14:45:59 2018 From: falk.lieder at berkeley.edu (Falk Lieder) Date: Fri, 26 Oct 2018 20:45:59 +0200 Subject: Connectionists: Fwd: Learning how to decide In-Reply-To: References: Message-ID: The Rationality Enhancement Group at the MPI for Intelligent System in T?bingen currently has openings for a Ph.D. student interested in combining reinforcement learning and program induction methods to discover bounded-optimal decision strategies. Furthermore, we also have openings for a postdoc and/or Ph.D. student for projects on reverse-engineering and improving how people learn how to decide. Finally, the rationality enhancement lab can offer paid internships as well as B.Sc. and M.Sc. theses at the intersection of psychology, AI, and machine learning. For more information, please take a look at the attached job ads. ? Falk Lieder, Ph.D. Max Planck Research Group Leader for Rationality Enhancement MPI for Intelligent Systems, T?bingen, Germany -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: PhD Robust Strategy Discovery_IMPRS.pdf Type: application/pdf Size: 77185 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... 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Name: Internships.pdf Type: application/pdf Size: 60928 bytes Desc: not available URL: From terry at salk.edu Sat Oct 27 04:31:21 2018 From: terry at salk.edu (Terry Sejnowski) Date: Sat, 27 Oct 2018 01:31:21 -0700 Subject: Connectionists: NEURAL COMPUTATION - November 1, 2018 In-Reply-To: Message-ID: Neural Computation - Volume 30, Number 11 - November 1, 2018 Available online for download now: http://www.mitpressjournals.org/toc/neco/30/11 ----- Review Applications of Recurrent Neural Networks in Environmental Factor Forecasting: A Review Yingyi Chen, Qianqian Cheng, Yanjun Cheng, Hao Yang, and Huihui Yu Article Diplomats' Mystery Illness and Radiofrequency/ Microwave Radiation Beatrice Golomb Letters Robust Closed-loop Control of a Cursor in a Person With Tetraplegia Using Gaussian Process Regression David M Brandman, Michael C Burkhart, Jessica Kelemen, Brian Franco, Matthew T. Harrison, and Leigh R Hochberg A Simple Model for Low Variability in Neural Spike Trains Ulisse Ferrari, Stephane Deny, Olivier Marre, and Thierry Mora Circuit Polarity Effect of Cortical Connectivity, Activity and Memory Yoram Baram Adaptive Gaussian Process Approximation for Bayesian Inference With Expensive Likelihood Functions Hongqiao Wang, Jinglai Li Convex Coupled Matrix and Tensor Completion Kishan wimalawarne, Makoto Yamada, and Hiroshi Mamitsuka CEP: Cross Entropy Pruning for Compressing Convolutional Neural Networks Zhikui Chen, Rongxin Bao, and Xu Yuan ------------ ON-LINE -- http://www.mitpressjournals.org/neuralcomp MIT Press Journals, One Rogers Street, Cambridge, MA 02142-1209 Tel: (617) 253-2889 FAX: (617) 577-1545 journals-cs at mit.edu ------------ From george at cs.ucy.ac.cy Sat Oct 27 08:10:07 2018 From: george at cs.ucy.ac.cy (George Angelos Papadopoulos) Date: Sat, 27 Oct 2018 15:10:07 +0300 Subject: Connectionists: The 27th ACM Conference on User Modeling, Adaptation and Personalization (UMAP 2019): Call for Workshop Proposals In-Reply-To: <46CA4E92-4B9B-4D1B-8B60-A1D0C2701DE3@cs.ucy.ac.cy> References: <9D907F9B-A04A-43F0-8623-6D92E4132AC9@cs.ucy.ac.cy> <46CA4E92-4B9B-4D1B-8B60-A1D0C2701DE3@cs.ucy.ac.cy> Message-ID: *** CALL FOR WORKSHOP PROPOSALS *** 27th ACM International Conference on User Modeling, Adaptation and Personalization (ACM UMAP 2019) Golden Bay Beach Hotel 5*, Larnaca, Cyprus, June 9-12, 2019 https://www.um.org/umap2019/ Proposals due: December 14, 2018 ACM UMAP 2019, the premier international conference for researchers and practitioners working on systems that adapt to individual users or to groups of users, and which collect, represent, and model user information, is pleased to invite proposals for workshops to be held in conjunction with the conference. The workshops provide a venue to discuss and explore emerging areas of User Modelling and Adaptive Hypermedia research with a group of like-minded researchers and practitioners from industry and academia. In this edition, our goal is to have a balanced workshop program comprising different workshop formats and combining emerging and established research topics. Different full-day and half-day workshop schemas are possible, such as: ? Working group meetings around a specific problem or topic; participants may be asked to submit a white paper or position statement. ? Mini-conferences on specialized topics, having their own paper submission and review processes. ? Mini-competitions or challenges around selected topics with individual or team participation. ? Interactive discussion meetings focusing on subtopics of the UMAP general research topics. PROPOSAL FORMAT Workshop proposals should be submitted in PDF format to both workshop chairs, not exceeding 5 pages and organized as follows: ? Workshop title and acronym. ? Workshop chair(s), including affiliation, email address, homepage, and experiences in organizing such events. ? Abstract (up to 300 words) and topics of interest. ? Motivation on why the workshop is of particular interest at this time. ? Workshop format, discussing the mix of events such as paper presentations, invited talks, panels, and general discussions. ? Intended audience and expected number of participants. ? List of (potential) members of the program committee (at least 50% have to be confirmed at the time of the proposal). ? Requested duration (half day or full day). ? When available, past editions of the workshop, including URLs, a brief statement on the development of the workshop series, e.g., in terms of topics, number of paper submissions and participants, post-workshop publications over the years and acceptance statistics. INSTRUCTIONS We encourage both researchers and industry practitioners to submit workshop proposals. Researchers interested in submitting a workshop proposal are invited to contact us in advance, so we can help to design successful proposals. In particular, for workshop proposals with novel interactive formats, we are happy to assist in further developing and implementing the ideas. We strongly suggest to have organizers from different institutions, bringing different perspectives to the workshop topic. We welcome workshops with a creative structure that may attract various types of contributions and may ensure rich interactions. The organizers of accepted workshops will prepare a workshop web site containing the call for papers and detailed information about the workshop organization and timeline. They will be responsible for their own publicity and reviewing processes. There will be a conference adjunct proceedings published by ACM where all the workshop papers will be published. Hence, the workshop organizers will need to adhere to the adjunct proceedings publication timeline. IMPORTANT DATES ? Proposal submission: December 14, 2018 ? Notification of proposal acceptance: January 9, 2019 ? Send the workshop description & website URL : January 23, 2019 ? (Suggested) 1st call for papers: January 28, 2019 ? (Suggested) 2nd call for papers: February 20, 2019 ? (Suggested) paper submission: March 13, 2019 ? (Suggested) notification to authors: March 26, 2019 ? Workshop summary camera-ready: April 3, 2019 ? Workshop papers camera-ready: April 3, 2019 ? Adjunct proceedings camera ready: April 15, 2019 WORKSHOP CHAIRS ? Milos Kravc?k, German Research Center for Artificial Intelligence (DFKI), Germany (milos.kravcik AT dfki.de) ? Iv?n Cantador, Universidad Aut?noma de Madrid, Spain (ivan.cantador AT uam.es) -------------- next part -------------- An HTML attachment was scrubbed... URL: From huanjun at baidu.com Sat Oct 27 18:35:49 2018 From: huanjun at baidu.com (Huan,Jun) Date: Sat, 27 Oct 2018 22:35:49 +0000 Subject: Connectionists: Multiple FTE and Postdoc positions available in Baidu Research Message-ID: Dear Colleagues: We have multiple fulltime employee, postdoc, and intern positions open in the Big Data lab (Beijing) at Baidu Research. The hiring locations are in both Beijing (Headquarter) and in Sunnyvale CA (Baidu Research USA). We are looking for energetic researchers who want to perform cutting-edge fundamental AI research with potential to impact billions of people. Co-located in Silicon Valley, Seattle and Beijing, Baidu Research brings together top talents from around the world to focus on future-looking fundamental research in artificial intelligence. The Big Data Laboratory focuses on studying the theoretic and computational principles of machine learning and deep learning in order to transform big data to practical knowledge. Specific topics that are studied recently include neural architecture search, deep learning model compression, transfer learning, and transparent modeling. We are looking for research scientists at all levels from senior tech leader to postdoc associates to interns. Successful candidates should have the following qualifications: * Research experience in AI fields. Publications in leading venues are preferred * General knowledge in machine learning, natural language processing, image processing and computer vision, and speech recognition, with deep insight in recent progress and practical experience in one of the fields * Understanding principles of deep learning, probabilistic inference, graphical models, reinforcement learning, transfer learning and adversarial learning, with extensive knowledge in one of the fields * Keen sense in technology advances in related fields * Strong communication skills * Ph.D. degree in the related fields If you are interested, please feel free to send your CV to me directly at huanjun at baidu.com, ccing my hiring assistants For positions located in Beijing, ccing Ms. Yang (yangming13 at baidu.com) For positions located in Sunnyvale, ccing Ms. Liu (v_liumengwen at baidu.com) Luke Huan -------------- Jun (Luke) Huan, Ph.D. Director, Baidu Big Data Lab (Beijing) Baidu Research Tel: +86-10-56795216 (China) Tel: +1-785-550-3189 (USA) Web: http://research.baidu.com/People/index-view?id=112 Email: huanjun at baidu.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From john.murray at yale.edu Mon Oct 29 00:16:56 2018 From: john.murray at yale.edu (Murray, John) Date: Mon, 29 Oct 2018 04:16:56 +0000 Subject: Connectionists: Postdoctoral Swartz Fellowship Positions in Theoretical and Computational Neuroscience at Yale University Message-ID: <0E63DDFD-3293-42BD-A0F0-D8BF5B675BB9@yale.edu> Postdoctoral Swartz Fellowship Positions in Theoretical and Computational Neuroscience at Yale University The Swartz Center in Theoretical Neurobiology at Yale University invites applications for up to two postdoctoral positions in Theoretical and Computational Neuroscience, with flexible start date from mid to late 2019. Competitive candidates include those with a strong quantitative background who wish to gain neuroscience research experience. We especially encourage candidates with an interest in collaborating directly with experimental neuroscientists. The candidates will be expected to perform theoretical/computational studies relevant to one or more laboratories of the Swartz Center at Yale (for a list of affiliated faculty, see: https://medicine.yale.edu/neuroscience/swartz/corelabs.aspx) and will be encouraged to participate in an expanding quantitative biology environment. Candidates must hold a Ph.D. or equivalent degree by the time of beginning the fellowship. Please send a Curriculum Vitae, selected reprints, contact information for three references, and a statement of research interests including the laboratories of interest at Yale. All application materials should be sent electronically to the following e-mail address: john.murray at yale.edu Applications will be reviewed as they are received, but priority will be given to those received on or before January 12th, 2019. For any questions, please contact John Murray. Yale University is an affirmative action/equal opportunity employer. Yale values diversity in its faculty, students, and staff and especially welcomes applications from women and underrepresented minorities. http://neurojobs.sfn.org/jobs/10584092/ John D. Murray ----------------------------------------------- Assistant Professor Department of Psychiatry Yale University School of Medicine murraylab.yale.edu ----------------------------------------------- -------------- next part -------------- An HTML attachment was scrubbed... URL: From aihara at sat.t.u-tokyo.ac.jp Sun Oct 28 22:15:38 2018 From: aihara at sat.t.u-tokyo.ac.jp (Kazuyuki Aihara) Date: Mon, 29 Oct 2018 11:15:38 +0900 (JST) Subject: Connectionists: Neuro-inspired Computation Course In-Reply-To: References: Message-ID: <20181029.111538.375844418.aihara@sat.t.u-tokyo.ac.jp> I am forwarding the information on a Neuro-inspired Computation Course at WPI-IRCN, UTokyo. Best wishes, Kazu Aihara -------------- next part -------------- A non-text attachment was scrubbed... Name: Neuro-inspired-Computation-Course-Mar2019_20181019.pdf Type: application/pdf Size: 404002 bytes Desc: not available URL: From education at humanbrainproject.eu Mon Oct 29 09:29:23 2018 From: education at humanbrainproject.eu (education at humanbrainproject.eu) Date: Mon, 29 Oct 2018 14:29:23 +0100 Subject: Connectionists: 3rd HBP Student Conference on Interdisciplinary Brain Research: Abstract submission deadline extended Message-ID: The abstract submission deadline for the 3rd HBP Student Conference on Interdisciplinary Brain Research has been extended until 6 November 2018. Call for submissions We invite original high-quality submissions describing innovative research in all disciplines addressed in the HBP. These contributions can emphasise theoretical or empirical works relating to a wide spectrum of fields including but not limited to: neuroscience, computer science, robotics, medicine, psychology, cognitive science or philosophy. We particularly encourage submissions with a potential to inspire collaboration in the research community by introducing new and relevant problems, concepts, and ideas, even if the work is at an early stage of development. Abstract submission Registration fee waivers are available for a maximum of five participants. Due to the kind support of IBRO, we are also able to offer a limited number of travel grants. Participants can apply for support prior to the abstract submission deadline by sending an email to education at humanbrainproject.eu . Please note that the successful submission of an abstract for presentation at the conference is a requirement in order to be eligible for support. About the conference The 3rd HBP Student Conference provides an open forum for the exchange of new ideas among young researchers working across various aspects of science relevant to the Human Brain Project (HBP). The conference offers a space for extensive scientific dialogue, both intra- and interdisciplinary, among peers and faculty through a variety of discussion sessions, lectures and social events. Date: 6-7 February 2019 Place: Ghent University, Belgium Conference programme: https://education.humanbrainproject.eu/web/3rd-hbp-student-conference/scientific-programme HBP Education Programme Medical University Innsbruck (MUI) M?llerstra?e 59, 6020 Innsbruck, Austria Email: education at humanbrainproject.eu Follow us on Twitter, Facebook and LinkedIn! Keep up with the Education Programme?s latest news, event information, job offers, videos and more. Share our news with your friends and colleagues to help spreading our education and training opportunities throughout the international research community. Where to follow: Twitter: @HBP_Education Facebook: @hbpeducation LinkedIn: HBP Education Programme -------------- next part -------------- An HTML attachment was scrubbed... URL: From k.schwarzwaelder at fz-juelich.de Mon Oct 29 09:52:44 2018 From: k.schwarzwaelder at fz-juelich.de (Kerstin Schwarzwaelder) Date: Mon, 29 Oct 2018 14:52:44 +0100 Subject: Connectionists: SfN 2018 - Visit the Bernstein Network Computational Neuroscience at booth #4325 Message-ID: Dear all, The Bernstein Network Computational Neuroscience will be an exhibitor at the SfN Meeting 2018. Please find us at the NEUROSCIENCE IN GERMANY booth #4325. The Bernstein Network will present: * research fields * study and training programs * open positions * research and funding opportunities * infrastructural facilities Furthermore, the German Neuroinformatics Node (G-Node) will present their data management services for organizing, sharing, and publishing research data. Demo presentations times are: Sunday, Monday, Wednesday (Nov 4, 5, 7) 10am - 12pm and 3pm - 5pm, or by individual appointment (mail to: info at g-node.org). We are looking forward to welcoming you at booth #4325! Best regards, Kerstin Schwarzwaelder -- Dr. Kerstin Schwarzw?lder Scientific Coordination / Management Officer Please note: Our email addresses have changed. Please use k.schwarzwaelder at fz-juelich.de Bernstein Network Computational Neuroscience | Bernstein Coordination Site (BCOS) Branch Office of the Forschungszentrum J?lich at the University of Freiburg Hansastr. 9A | 79104 Freiburg, Germany phone: (+49) 0761 203 9589 mail: k.schwarzwaelder at fz-juelich.de web: www.nncn.de Twitter: NNCN_Germany YouTube: Bernstein TV Facebook: Bernstein Network Computational Neuroscience, Germany LinkedIn: Bernstein Network Computational Neuroscience, Germany ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ 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 axel.soto at cs.uns.edu.ar Mon Oct 29 13:22:49 2018 From: axel.soto at cs.uns.edu.ar (Axel Soto) Date: Mon, 29 Oct 2018 14:22:49 -0300 Subject: Connectionists: Call for Posters and Demos: ACM IUI 2019 Message-ID: *** Please forward to anyone who might be interested *** --------------------------------------------------------------------------- Call for Posters and Demos: ACM IUI 2019 to be held in Los Angeles, CA, USA, March 17-20, 2019 http://iui.acm.org/2019/ --------------------------------------------------------------------------- ACM IUI 2019 is the 24th annual meeting of the intelligent interfaces community and serves as a premier international forum for reporting outstanding research and development on intelligent user interfaces. In 2019, IUI will be held in the Marriott Marina Del Rey in Los Angeles, CA from March 17th - 20th. ACM IUI is where the Human-Computer Interaction (HCI) community meets the Artificial Intelligence (AI) community, also accepting contributions from related fields such as psychology, behavioral science, cognitive science, computer graphics, design or the arts. This year we especially encourage submissions on explainable intelligent user interfaces for IUI 2019. ** Why you should submit to ACM IUI ** At ACM IUI, we focus on the interaction between machine intelligence and human intelligence. While other conferences focus on one side or the other, we address the complex interaction between the two. We welcome research that explores how to make the interaction between computers and people smarter, which may leverage solutions from data mining, knowledge representation, novel interaction paradigms, and emerging technologies. We strongly encourage submissions that discuss research from both HCI and AI simultaneously, but also welcome works that focus more on one side or the other. The conference brings together people from academia, industry and non-profit organizations and gives its participants the opportunity to present and see cutting-edge IUI work in a focused and interactive setting. It is large enough to be diverse and lively, but small enough to allow for extensive interaction among attendees and easy attendance to the events that the conference offers, ranging from oral paper presentations, poster sessions, workshops, panels and doctoral consortium for graduate students. IUI topics of interest include, but are not limited to: - Affective and aesthetic interfaces - Big Data and analytics - Collaborative interfaces - Education and learning-related technologies - Evaluations of intelligent user interfaces - Explainable intelligent user interfaces. - Health and intelligent health technologies - Information retrieval and search - Intelligent assistants for complex tasks - Intelligent wearable and mobile interfaces - Intelligent ubiquitous user interfaces - Intelligent visualization tools - Interactive machine learning - Knowledge-based approaches to user interface design and generation - Modeling and prediction of user behavior - Multi-modal interfaces (speech, gestures, eye gaze, face, physiological information etc.) - Natural language and speech processing - Persuasive and assistive technologies in IUI - Planning and plan recognition for IUI - Proactive and agent-based user interaction - Recommender systems - Smart environments and tangible computing - Social media analysis - User Modelling for Intelligent Interfaces - User-Adaptive interaction and personalization ** Dates ** Submission Due: Dec 21st, 2018 Notification to Authors: Jan 14th, 2019 Camera Ready Due: Jan 21st, 2019 ** Submission - Poster and Demo ** Demos The demonstrations track complements the overall program of the conference. Demonstrations show implementations of novel, interesting, and important intelligent user interface concepts or systems. We invite submissions relevant to intelligent user interfaces and which address, but are not limited to, the topics of the conference. All submissions are intended to convey a scientific result or work in progress and should not be advertisements for commercial software packages. The page limit for demo papers is 2 pages (including references). Accepted demo papers will be presented as interactive demonstrations at IUI and published in the companion proceedings of the conference. Posters Posters provide an opportunity for sharing valuable last-minute ideas, eliciting useful feedback on early-stage work and fostering discussions and collaborations among colleagues. We invite submissions on all topics of the conference. All submissions should convey a scientific result or work in progress that is not yet ready to be published as a full length research paper at a refereed conference. Submitting a draft poster along with your submission is not required but recommended. The page limit for poster papers is 2 pages (including references). Accepted poster papers will appear in the companion proceedings of the conference. Submission Instructions Demo and poster submissions do not need to be anonymized. The page limit is 2 pages (including references) in 2-column portrait ACM SIGCHI template (http://www.acm.org/publications/proceedings-template). Submitting a draft poster along with your poster submission is not required but recommended. Submit your demos and posters at PCS 2.0: https://new.precisionconference.com. Chairs - poster-iui2019 at acm.org Leo Liu, Adobe, USA Yukiko Nakano, Seikei University, Japan From shobeir at gmail.com Mon Oct 29 19:55:34 2018 From: shobeir at gmail.com (Shobeir Fakhraei) Date: Mon, 29 Oct 2018 16:55:34 -0700 Subject: Connectionists: CFP: Machine Learning with Graphs (Applied Network Science Journal Special Issue) Message-ID: Call for Papers: Applied Network Science Special Issue on Machine Learning with Graphs https://appliednetsci.springeropen.com/cfp-mlgraphs Data that are best represented as a graph such as social, biological, communication, or transportation networks, and energy grids are ubiquitous in our world today. As more of such structured and semi-structured data is becoming available, the machine learning methods that can leverage the signal in these data are becoming more valuable, and the importance of being able to effectively mine and learn from such data is growing. These graphs are typically multi-relational, dynamic, and large-scale. Understanding the different techniques applicable to graph data, dealing with their heterogeneity and applications of methods for information integration and alignment, handling dynamic and changing graphs, and addressing each of these issues at scale are some of the challenges in developing machine learning methods for graph data that appear in a variety of applications. In this special issue, we aim to publish articles that help us better understand the principles, limitations, and applications of current graph-based machine learning methods, and to inspire research on new algorithms, techniques, and domain analysis for machine learning with graphs. We encourage submissions on theory, methods, and applications focusing on a broad range of graph-based machine learning approaches in various domains. Topics of interest include but are not limited to theoretical aspects, algorithms, and methods such as: - Learning and mining algorithms - Graph mining approaches - Link and relationship strength prediction - Learning to rank in networks - Similarity measures and graph kernel methods - Graph alignment, matching, and identification - Network summarization and compression - Learning from partially-observed networks - Semi-supervised learning, active learning, transductive inference, and transfer learning in the context of graphs - Large-scale analysis and models for graph data - Evaluation issues in graph-based algorithms - Anomaly detection with graph data - Embeddings and factorization methods - Network embedding methods and manifold learning - Matrix and tensor factorization methods - Deep learning on graphs - Learning with dynamic and complex networks - Models to learn from dynamic graph data - Heterogeneous, signed, attributed, and multi-relational graph mining methods - Online learning with graphs - Statistical and probabilistic methods - Computational or statistical learning theory related to graphs - Statistical models of graph structures - Probabilistic and graphical models for structured data - Statistical relational learning - Sampling graph data - Theory - Theoretical analysis of graph-based machine learning algorithms or models - Combinatorial graph methods We also encourage submissions focused on machine learning applications that use graph data. Such applications include, but are not limited to: - Biomedicine and medical networks - Social network analysis - The World Wide Web - Neuroscience and neural networks - Transportation systems and physical infrastructure - Knowledge graphs - Recommender systems Survey and review papers as well as submissions that are significant extension (more than 30%) of previously published work are welcome. Important Dates - Abstract submission: Dec 20, 2018 We invite authors to submit a brief expression of interest containing a short outline or extended abstract (approx. 1000 words), Including the topic, key concepts, methods, expected results, and conclusions. - Abstract feedback notification: Jan 10, 2019 - Paper submission deadline: Mar 1, 2019 - Target publication: Jul 30, 2019 We encourage to submit the papers prior to these deadlines. Papers will be subject to a fast track review procedure that will start as soon as they are submitted, and are published upon acceptance, regardless of the special Issue publication date. Guest Editors Austin Benson, Computer Science Department, Cornell University, arb at cs.cornell.edu Ciro Cattuto, ISI Foundation, ciro.cattuto at isi.it Shobeir Fakhraei, Information Sciences Institute, Univ. of Southern California, fakhraei at usc.edu Danai Koutra, Computer Science & Engineering, University of Michigan, dkoutra at umich.edu Vagelis Papalexakis, Computer Science & Engineering, UC Riverside, epapalex at cs.ucr.edu Jiliang Tang, Computer Science & Engineering Dept., Michigan State Univ., tangjili at msu.edu For more information, please direct your questions to the Lead Guest Editor: Shobeir Fakhraei fakhraei at usc.edu -------------- next part -------------- An HTML attachment was scrubbed... URL: From jkrichma at uci.edu Mon Oct 29 21:55:49 2018 From: jkrichma at uci.edu (Jeff Krichmar) Date: Mon, 29 Oct 2018 18:55:49 -0700 Subject: Connectionists: PhD in Cognitive Sciences at UC Irvine References: <84b0287a-13e8-4044-4211-667bd32c5127@uci.edu> Message-ID: <00266BC1-7BCB-42CE-B2C7-D9BC17BF6DB9@uci.edu> Dear colleagues, The Department of Cognitive Sciences at UC Irvine has a number of openings for new graduate students starting Fall of 2019. We are in the process of expanding our graduate program, so please feel free to forward this information to any interested parties. All this information and more can be found in the attached leaflet and via cogs.ci . Our department specializes in Computational and mathematical cognitive modeling Cognitive neuroscience Visual and auditory perception Attention and representation Learning and development Memory and language Judgment and decision making ... and is generally strong in the use of leading technologies such as EEG, fMRI, and robotics, and of modern research tools such as computational methods, big data, and Bayesian statistics. We offer PhD degrees in Cognitive Sciences with an optional specialization in cognitive neuroscience and an optional joint degree (MS/PhD) in Statistics. We also take pride in offering excellent financial packages to our graduate students, including at least five years of guaranteed support, health insurance, research funding, and more. These positions are also open to international students with appropriate academic qualifications (i.e., a Bachelor's degree in a relevant field). This year's deadline to apply is December 1, 2018. I am happy to answer questions you or your students might have. Best, Joachim -- Joachim Vandekerckhove Associate Professor Department of Cognitive Sciences Department of Statistics University of California, Irvine -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: cogsci-spreads.pdf Type: application/pdf Size: 514585 bytes Desc: not available URL: -------------- next part -------------- An HTML attachment was scrubbed... URL: From mark.humphries at manchester.ac.uk Tue Oct 30 10:28:17 2018 From: mark.humphries at manchester.ac.uk (Mark Humphries) Date: Tue, 30 Oct 2018 14:28:17 +0000 Subject: Connectionists: Closing soon: Postdoctoral position in circuit modelling at Nottingham, deadline 7th November Message-ID: <7E954275ED82B9468C2C731FB72522F5013E11589C@MBXP09.ds.man.ac.uk> A postdoctoral position is available in the lab of Prof Mark Humphries at the University of Nottingham. We seek a postdoctoral researcher to tackle the deep question of how dopamine controls the dynamics of the striatum. As the main target of dopamine in the brain, the striatum bears the brunt of dopamine loss in Parkinson?s disease. Yet how dopamine controls the output of the striatum, and how the loss of dopamine disrupts that output, is unknown. The successful candidate will be responsible for constructing and simulating models of the striatum to investigate how dopamine controls the striatum?s dynamics, and the implications this will have for Parkinson?s disease. The project will build upon the detailed models of the striatum from the Humphries group (e.g. Humphries et al 2009 Neural Networks; 2010, PLoS Computational Biology). This is also a chance to join the newly-created computational neuroscience centre at Nottingham, which includes Profs Mark van Rossum and Stephen Coombes, 3 new research fellows, and up to 6 PhD students. Find out more about the lab and its interests here: https://www.humphries-lab.org/ The post will be available for 18 months in the first instance. More details, eligibility, and application instructions here: https://www.nottingham.ac.uk/jobs/currentvacancies/ref/SCI353818 Deadline: 7th November 2018 To discuss this or other projects, please contact Mark (mark.humphries at nottingham.ac.uk). -------------- next part -------------- An HTML attachment was scrubbed... URL: From aonken at inf.ed.ac.uk Tue Oct 30 10:34:54 2018 From: aonken at inf.ed.ac.uk (Arno Onken) Date: Tue, 30 Oct 2018 14:34:54 +0000 Subject: Connectionists: Postdoc Position in Neural Data Analysis, University of Edinburgh Message-ID: <092ab555-781f-4231-7f3f-5c001cd63849@inf.ed.ac.uk> The School of Informatics, University of Edinburgh, invites applications for a full-time, fixed term Research Associate position on the project "Novel techniques for stochastic modelling of time-dependent multivariate relationships with application to primary visual cortex", funded by the UK Engineering and Physical Sciences Research Council (EPSRC), and directed by Dr Arno Onken (PI). The successful candidate will contribute to the development of a new framework for analysing multi-modal and multi-scale neural recordings. Moreover, the candidate will apply this framework to analyse activity of large neural populations recorded from awake mice during a virtual reality task by experimental project partner Dr Nathalie Rochefort. Candidates should have a PhD (or near completion) in a quantitative discipline (Mathematics, Computer Science, Physics, Computational Neuroscience or related), good software development skills and a keen interest in interdisciplinary research. A background in neuroscience is desirable, but not essential. The post is full time and fixed term at UE07: ?33,199 - ?39,609 pa. The post is available from 1st March 2019 for 36 months until the scheduled end of the project at 28th February 2022. For further information, please visit the vacancy website at: https://www.vacancies.ed.ac.uk/pls/corehrrecruit/erq_jobspec_version_4.jobspec?p_id=045791 Informal enquires can be made to Dr Arno Onken . -- The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336. From a.checco at sheffield.ac.uk Tue Oct 30 11:27:07 2018 From: a.checco at sheffield.ac.uk (Alessandro Checco) Date: Tue, 30 Oct 2018 15:27:07 +0000 Subject: Connectionists: Research Associate Position - Machine Learning and Crowdsourcing applied to Fashion data (UK) Message-ID: Research Associate in Crowdsourcing and Human Computation Information School, University of Sheffield Salary: Grade 7: 31,302 - 39,609 GBP per annum Contract Type: Fixed term until 31 August 2021 Closing date: 13th November 2018 Further details (and to apply): https://www.jobs.ac.uk/job/BNJ425/research-associate ---------------------------------------------------------------- Are you interested in working for a world top 100 University? The FashionBrain project is funded through the H2020 framework programme of the European Commission. The aim of the project is to acquire a deep understanding of customer needs and to predict next trends of Europe?s fashion industry. The post-holder will undertake research in the areas of Crowdsourcing, Deep Learning, Machine Learning, and Human Computation applied to Fashion data. The goals are to improve the quality of Human Computation applications by developing better quality and less expensive crowdsourcing techniques; to develop novel crowdsourcing quality assurance techniques; to understand dimensions like bias and subjectivity and to deal with it developing priming and training approaches for crowdsourcing. Applicants should hold a PhD in Computer Science or a related field (or have equivalent experience) and have experience of relevant research approaches and methods in the areas of Crowdsourcing, Deep Learning, Machine Learning, and Human Computation The Information School at the University of Sheffield is recognised nationally and internationally for its world-class research, excellence in teaching, and the achievements of its graduates. It is the leader in its field in the UK, consistently ranked number one in every national Research Assessment Exercise and is a member of the international iSchools organisation, a group of leading cognate schools established to promote the role of the information field in shaping the future of the global information society. We?re one of the best not-for-profit organisations to work for in the UK. The University?s Total Reward Package includes a competitive salary, a generous Pension Scheme and annual leave entitlement, as well as access to a range of learning and development courses to support your personal and professional development. We build teams of people from different heritages and lifestyles whose talent and contributions complement each other to greatest effect. We believe diversity in all its forms delivers greater impact through research, teaching and student experience. Follow @sheffielduni and @ShefUniJobs on Twitter for more information about what makes the University of Sheffield a remarkable place to work. Alessandro Checco alessandrochecco.github.io -------------- next part -------------- An HTML attachment was scrubbed... URL: From dwang at cse.ohio-state.edu Tue Oct 30 12:07:33 2018 From: dwang at cse.ohio-state.edu (DeLiang Wang) Date: Tue, 30 Oct 2018 12:07:33 -0400 Subject: Connectionists: NEURAL NETWORKS Special Issue on Deep Reinforcement Learning Message-ID: <3d20566f-8d18-b650-d062-06f52f338e66@cse.ohio-state.edu> Neural Networks - Volume 107, November 2018 http://www.journals.elsevier.com/neural-networks SPECIAL ISSUE on Deep Reinforcement Learning Guest Editorial Ron Sun, David Silver, Gerald Tesauro, Guang-Bin Huang Sigmoid-weighted linear units for neural network function approximation in reinforcement learning Stefan Elfwing, Eiji Uchibe, Kenji Doya Novel deep generative simultaneous recurrent model for efficient representation learning M. Alam, L. Vidyaratne, K.M. Iftekharuddin Intrinsically motivated reinforcement learning for human-robot interaction in the real-world Ahmed Hussain Qureshi, Yutaka Nakamura, Yuichiro Yoshikawa, Hiroshi Ishiguro Deeply-learnt damped least-squares (DL-DLS) method for inverse kinematics of snake-like robots Olatunji Mumini Omisore, Shipeng Han, Lingxue Ren, Ahmed Elazab, ... Lei Wang Neural circuits for learning context-dependent associations of stimuli Henghui Zhu, Ioannis Ch. Paschalidis, Michael E. Hasselmo An adaptive deep Q-learning strategy for handwritten digit recognition Junfei Qiao, Gongming Wang, Wenjing Li, Min Chen From epatters at stanford.edu Tue Oct 30 13:41:02 2018 From: epatters at stanford.edu (Evan James Patterson) Date: Tue, 30 Oct 2018 17:41:02 +0000 Subject: Connectionists: Call for Papers: 2019 AAAI 2019 Spring Symposium on Towards AI for Collaborative Open Science (TACOS-19) Message-ID: Call for Papers: Towards AI for Collaborative Open Science (TACOS-19) https://www.epatters.org/tacos19/cfp/ We are announcing a call for papers, now with extended deadline, for the symposium Towards AI for Collaborative Open Science (TACOS-19), part of the AAAI 2019 Spring Symposium Series, to be held at Stanford University, March 25th to 27th, 2019. We invite submissions of research papers (6 pages), as well as short papers (2 pages) for work-in-progress or position pieces. Important Dates: Paper submission. November 16th, 2018 (deadline extended). Notification. December 3rd, 2018. Topics: The purpose of the symposium is to explore how artificial intelligence and computational tools can accelerate the pace of scientific discovery. We solicit research papers and work-in-progress papers, making novel research contributions to networked, machine-assisted science, as well as position papers about how to advance the field. Possible topics include, but are not limited to: - AI and NLP methods for mining the scientific literature - Meta-learning, meta-analysis, and model aggregation for open science - Knowledge representation for the scientific process, e.g. for datasets or data analysis - Knowledge representation for scientific knowledge, e.g. in biomedicine - Software tools and formats for disseminating scientific knowledge - Online platforms for collaborative basic science or data science - Empirical studies of open scientific collaboration and innovation - Incentives and rewards in open science Further information: https://www.epatters.org/tacos19/ From m.biehl at rug.nl Tue Oct 30 15:06:54 2018 From: m.biehl at rug.nl (Michael Biehl) Date: Tue, 30 Oct 2018 20:06:54 +0100 Subject: Connectionists: Special Session at ESANN 2019: Stait Message-ID: Apologies in advance for multiple postings. *REMINDER: **Call for papers : *Special Session *"Statistical Physics of Learning and Inference" at ESANN 2019*Deadline for submission of papers: November 19, 2018. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN2019). 24-26 April 2019, Bruges, Belgium http://www.esann.org Description: This special session is meant to attract researchers who exploit analogies and concepts from statistical physics in the context of machine learning, inference, optimization, and related fields. The exchange of ideas between statistical physics and computer science has been very fruitful and is currently gaining momentum again as a consequence of the revived interest in neural networks, machine learning and inference in general. Statistical physics methods complement other approaches to the theoretical understanding of machine learning processes and inference in stochasic modeling. They facilitate, for instance, the study of dynamical and equilibrium properties of randomized training processes in model situations. At the same time, the approach inspires novel and efficient algorithms and facilitates interdisciplinary applications in a variety of scientific and technical disciplines. The tools and concepts applied in this context include information theory, the mathematical analysis of stochastic differential equations, methods borrowed from the statistical mechanics of disorder, mean field theory, variational calculus, renormalization group and other methods. Potential topics include, but are not limited to: - Probabilistic inference in, e.g., stochastic dynamical systems and complex networks - Learning in Deep Networks and other architectures - Complex optimization problems - Emergent behavior in societies of agents - Transient dynamics and equilibrium phenomena in machine learning - The relation of statistical mechanics with information theory and mathematical statistics - Applications, for instance in: - systems biology and bioinformatics - neuroscience - environmental modelling - social systems - signal processing - complex optimization SUBMISSION: Authors must submit their paper through the ESANN portal following the instructions provided at https://www.elen.ucl.ac.be/esann/index.php?pg=submission We encourage authors to contact the organizers of the session beforehand. Each paper will undergo a peer reviewing process for its acceptance. IMPORTANT DATES: Submission of papers: 19 November 2018 Notification of acceptance: 31 January 2019 ESANN conference: 24 - 26 April 2019 SPECIAL SESSION ORGANISERS: Michael Biehl, University of Groningen, The Netherlands Nestor Caticha, University of Sao Paulo, Brazil Manfred Opper, Technical University Berlin, Germany Thomas Villmann, University of Applied Sciences Mittweida, Germany ---------------------------------------------------------- Prof. Dr. Michael Biehl Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence 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 emmanuel.vincent at inria.fr Tue Oct 30 18:17:22 2018 From: emmanuel.vincent at inria.fr (Emmanuel Vincent) Date: Tue, 30 Oct 2018 23:17:22 +0100 Subject: Connectionists: Two postdoctoral positions on privacy-friendly, decentralized learning for ASR In-Reply-To: <735d23aa-e9b4-7336-1f83-57d4e5e8e0be@inria.fr> References: <735d23aa-e9b4-7336-1f83-57d4e5e8e0be@inria.fr> Message-ID: Dear list, The application deadline for these two positions has been postponed: https://jobs.inria.fr/public/classic/en/offres/2018-01045 https://jobs.inria.fr/public/classic/en/offres/2018-01044 Note that: - the starting date is flexible (until summer 2019) - you do not need to hold a PhD yet, provided you are about to obtain one or you can demonstrate significant equivalent experience Applications will be assessed on a rolling basis; please apply as soon as possible. We are looking forward to your application. -- Emmanuel Vincent Multispeech Project-Team Inria Nancy - Grand Est 615 rue du Jardin Botanique, 54600 Villers-l?s-Nancy, France Phone: +33 3 8359 3083 - Fax: +33 3 8327 8319 Web: http://members.loria.fr/evincent/ Le 18/09/2018 ? 22:22, Emmanuel Vincent a ?crit?: > Inria is seeking 3 postdoctoral researchers for a new European (H2020 ICT) collaborative project called COMPRISE. COMPRISE is a 3-year Research and Innovation Action (RIA) aiming at new cost-effective, multilingual, privacy-driven voice interaction technology. This will be achieved through research advances in privacy-driven machine learning, personalized training, automatic data labeling, and tighter integration of speech and dialog processing with machine translation. The technology will be based on existing software toolkits (Kaldi speech-to-text, Platon dialog processing, Tilde text-to-speech), as well as new software resulting from these research efforts. > > The consortium includes academic and industrial partners in France (Inria ,Netfective Technology ), Germany (Ascora ,Saarland University ), Latvia (Tilde ), and Spain (Rooter ). The successful candidates will be part of theMultispeech team in Nancy or theMagnet team in Lille. Both teams will work in tight collaboration. > > Topics include: > > * weakly-supervised, semi-supervised learning, learning with partial feedback > * theoretical aspects and formal guarantees in private machine learning, > * representation learning and deep learning for speech processing, > * learning on the edge, federated learning and personalized learning. > > Both theoretical and practical aspects will be developed, possibly by different candidates depending on their skills. > > *Desired profile:* > > Two alternative profiles are welcome, either: > > * strong background in mathematics, machine learning, statistics and algorithms, > > or > > * strong experience with implementation and experimentation, speech processing, natural language processing, user modeling. > > *Application deadline:* October 19, 2018 > > *Starting date:* January 1, 2019 or later > *Duration:* 2 years (renewable) > *Location:* Nancy or Lille, France > *Salary:* from 2,130 to 2,520 EUR net/month, according to experience > > *For more details and to apply:* > https://jobs.inria.fr/public/classic/en/offres/2018-01045 > https://jobs.inria.fr/public/classic/en/offres/2018-01044 > https://jobs.inria.fr/public/classic/en/offres/2018-01038 > > -- > Emmanuel Vincent > Multispeech Project-Team > Inria Nancy - Grand Est > 615 rue du Jardin Botanique, 54600 Villers-l?s-Nancy, France > Phone: +33 3 8359 3083 - Fax: +33 3 8327 8319 > Web:http://members.loria.fr/evincent/ > From ohad.kammar at gmail.com Tue Oct 30 23:10:57 2018 From: ohad.kammar at gmail.com (Ohad Kammar) Date: Wed, 31 Oct 2018 03:10:57 +0000 Subject: Connectionists: LAFI 2019: Languages for Inference --- Final Call-for-Proposals Message-ID: LAFI 2019: Languages for Inference (formerly PPS) ================================================ Tuesday, 15 January 2019, Cascais/Lisbon, Portugal A workshop affiliated with POPL 2019 https://popl19.sigplan.org/track/lafi-2019 Important dates (anywhere on earth) ------------------------------------------------- LAFI submission deadline Thu 1 Nov 2018 Notification Mon 3 Dec 2018 Early Registration Deadline Thu 10 Dec 2018 Workshop Tue 15 Jan 2019 ------------------------------------------------- Submission: https://lafi19.hotcrp.com/ Registration: https://popl19.sigplan.org/attending/Registration Context ======= Inference concerns re-calibrating program parameters based on observed data, and has gained wide traction in machine learning and data science. Inference can be driven by probabilistic analysis and simulation, and through back-propagation and differentiation. Languages for inference offer built-in support for expressing probabilistic models and inference methods as programs, to ease reasoning, use, and reuse. The recent rise of practical implementations as well as research activity in inference-based programming has renewed the need for semantics to help us share insights and innovations. This workshop aims to bring programming-language and machine-learning researchers together to advance all aspects of languages for inference. Topics include but are not limited to: + design of programming languages for inference and/or differentiable programming; + inference algorithms for probabilistic programming languages, including ones that incorporate automatic differentiation; + automatic differentiation algorithms for differentiable programming languages; + probabilistic generative modelling and inference; + variational and differential modelling and inference; + semantics (axiomatic, operational, denotational, games, etc) and types for inference and/or differentiable programming; + efficient and correct implementation; + and last but not least, applications of inference and/or differentiable programming. For a sense of the talks, posters, and blogs in past years, see + PPS-2018: http://conf.researchr.org/track/POPL-2018/pps-2018 blog: http://pps2018.soic.indiana.edu/ + PPS-2017: http://conf.researchr.org/track/POPL-2017/pps-2017 blog: http://pps2017.soic.indiana.edu/) + PPS-2016: http://conf.researchr.org/track/POPL-2016/pps-2016 blog: http://pps2016.soic.indiana.edu/) This year we are explicitly expanding the focus of the workshop from statistical probabilistic programming to encompass differentiable programming for statistical machine learning. We expect this workshop to be informal, and our goal is to foster collaboration and establish common ground. Thus, the proceedings will not be a formal or archival publication, and we expect to spend only a portion of the workshop day on traditional research talks. Nevertheless, as a concrete basis for fruitful discussions, we call for extended abstracts describing specific and ideally ongoing work on probabilistic programming languages, semantics, and systems. Submission guidelines ===================== Extended abstracts are up to 2 pages in PDF format, excluding references. Please submit them by November 1(AoE) using HotCRP at: https://lafi19.hotcrp.com/ In line with the SIGPLAN Republication Policy: http://www.sigplan.org/Resources/Policies/Republication/ inclusion of extended abstracts in the programme is not intended to preclude later formal publication. Programme committee: At?l?m G?ne? Baydin University of Oxford Department of Engineering Bart van Merri?nboer University of Montreal Christine Tasson University Paris Diderot David Duvenaud University of Toronto Jeffrey Siskind (co-chair) School of Electrical and Computer Engineering, Purdue University Matthew Johnson Google Brain Ohad Kammar (co-chair) University of Oxford Department of Computer Science Praveen Narayanan Indiana University Ryan Culpepper Czech Technical University Sophia Gold Tezos Steven Holtzen University of California Los Angeles Tom Rainforth University of Oxford Department of Statistics -------------- next part -------------- An HTML attachment was scrubbed... URL: From luca.oneto at unige.it Wed Oct 31 04:28:59 2018 From: luca.oneto at unige.it (Luca Oneto) Date: Wed, 31 Oct 2018 09:28:59 +0100 Subject: Connectionists: [INNS-BDDL 2019] - Submission Deadline Postponed to the 18th of November Message-ID: [Apologies if you receive multiple copies of this CFP] Due to many requests the submission deadline has been postponed to the 18th of November. ########################################################### CALL FOR PAPERS INNS BIG DATA AND DEEP LEARNING 2019 April 16-18 SESTRI LEVANTE, GENOA, ITALY Website: https://innsbddl2019.org/ ######################Description########################## The 2019 INNS Big Data and Deep Learning (INNSBDDL 2019) conference will be held in Sestri Levante, Italy, April 16 ? 18, 2019. The conference is organized by the International Neural Network Society, with the aim of representing an international meeting for researchers and other professionals in Big Data, Deep Learning and related areas. It will feature invited plenary talks by world renowned speakers in the area, in addition to regular and special technical sessions with oral and poster presentations. Moreover, workshops and tutorials will also be featured. ######################Invited Speakers##################### * Hava Siegelmann, DARPA, USA * Paolo Ferragina, University of Pisa, Italy * Guang-Bin Huang, Nanyang Technological University, Singapore ########################################################### ######################Tutorials############################ * Alessio Micheli (University of Pisa), Davide Bacciu (University of Pisa), Deep Learning for Graphs * Silvia Chiappa (DeepMind), Luca Oneto (University of Genoa), Fairness in Machine Learning * Claudio Gallicchio (University of Pisa), Simone Scardapane (Sapienza University of Rome), Deep Randomized Neural Networks * V?ra K?rkov? (Czech Academy of Sciences), Complexity of Shallow and Deep Networks * Danilo P. Mandic, Ilia Kisil, and Giuseppe G. Calvi (Imperial College London), Tensor Decompositions and Applications. Blessing of Dimensionality * German I. Parisi and Stefan Wermter (University of Hamburg), Continual Lifelong Learning with Neural Networks ########################################################### #######################IMPORTANT DATES##################### * Deadline of full paper submission: November 18, 2018 * Notification of paper acceptance: December 31, 2018 * Camera-ready submission: January 31, 2019 * Early registration deadline: January 15, 2019 * Registration deadline: January 31, 2019 * Conference date: April 16 - 18, 2019 ########################################################### ##########################SCOPE############################ We solicit both solid contributions or preliminary results which show the potentiality and the limitations of new ideas, refinements, or contaminations in any aspect of Big Data and Deep Learning. Both theoretical and practical results are welcome. Example topics of interest includes but is not limited to the following: Big Data Science and Foundations * Novel Theoretical Models for Big Data * New Computational Models for Big Data * Data and Information Quality for Big Data Big Data Mining * Social Web Mining * Data Acquisition, Integration, Cleaning, and Best Practices * Visualization Analytics for Big Data * Computational Modeling and Data Integration * Large-scale Recommendation Systems and Social Media Systems * Cloud/Grid/StreamData Mining * Big Velocity Data * Link and Graph Mining * Semantic-based Data Mining and Data Preprocessing * Mobility and Big Data * Multimedia and Multistructured Data-Big Variety Data Modern Practical Deep Networks * Deep Feedforward Networks * Regularization for Deep Learning * Optimization for Training Deep Models * Convolutional Networks * Sequence Modeling: Recurrent and Recursive Nets * Practical Methodology Deep Learning Research * Linear Factor Models * Autoencoders * Representation Learning * Structured Probabilistic Models for Deep Learning * Monte Carlo Methods * Confronting the Partition Function * Approximate Inference * Deep Generative Models ####################PROCEEDINGS & SPECIAL ISSUE############ Works submitted as a regular paper will be published in a serie indexed by Scopus. Submitted papers will be reviewed by some PC members based on technical quality, relevance, originality, significance and clarity. At least one author of an accepted submission should register to present their work at the conference. Selected papers presented at INNS BDDL 2019 will be included in special issues of top journals in the field (prospected journals: Big Data Research, Transaction on Neural Networks and Learning System, Neurocomputing, etc). ########################################################### ----------------------------------------------------------------------------------- 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 bard at pitt.edu Wed Oct 31 11:19:12 2018 From: bard at pitt.edu (Ermentrout, G Bard) Date: Wed, 31 Oct 2018 15:19:12 +0000 Subject: Connectionists: Mathematical Neuroscience Prize Message-ID: Nominations are now open for the 2019 Math Neuro Prize -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: Call for Nominations Mathematical Neuroscience Prize 2019 .pdf Type: application/pdf Size: 262307 bytes Desc: Call for Nominations Mathematical Neuroscience Prize 2019 .pdf URL: From Pavis at iit.it Wed Oct 31 10:21:36 2018 From: Pavis at iit.it (Pavis) Date: Wed, 31 Oct 2018 14:21:36 +0000 Subject: Connectionists: =?cp1258?q?PostDoc_on_Computer_Vision_on_Cultural?= =?cp1258?q?_Heritage_Technologies_=28CCHT=40Ca=CCFoscari=29_-_=5B_Postdoc?= =?cp1258?q?_=5D_CB_75117?= In-Reply-To: <8054c5da3a6c481f856dd43df623c92b@iit.it> References: <8054c5da3a6c481f856dd43df623c92b@iit.it> Message-ID: PostDoc on Computer Vision on Cultural Heritage Technologies (CCHT at Ca?Foscari) - [ Postdoc ] Workplace: Venezia, CCHT, Italy The IIT center at Ca' Foscari University of Venice - Center for Cultural Heritage Technology at Ca'Foscari (CCHT at Ca'Foscari) has the mission to research and promote new technologies and to extend existing techniques for preservation and analysis of the invaluable Cultural Heritage assets managed by cities, galleries, libraries, archives and museums across different fields of art. CCHT at Ca'Foscari is currently seeking to appoint a Computer Vision Postdoc. The selected candidate will join an interdisciplinary team of researchers, contributing to the development of next-generation 3D digitization and machine learning approaches applied to the Cultural Heritage (CH) and Digital Humanities (DH) domain. Required qualifications: A Ph.D. in computer science or related field (with specialization in either computer vision or machine learning); Proficiency in programming languages, in particular, Python, C/C++, and MATLAB; Experience in the 3D computer vision field e.g. 3D reconstruction from RGBD data, photometric stereo, structure from motion, BRDF estimation, structured light systems. Publication in major Computer Vision and/or Computer Graphics conferences/journals (e.g. CVPR, ICCV, ECCV, SIGGRAPH, Eurographics, ToG, TPAMI, IJCV, IVC, CVIU). Good communication skills and ability to cooperate; Proficient in English language (written and oral). Desirable skills: Knowledge of OpenCV, PCL, and Open3D libraries; Practical experience on Deep Learning algorithms and relevant platforms for geometric learning (e.g. TensorFlow, PyTorch, Theano, Caffe); Experience in cultural heritage knowledge 2D and 3D digitization. The successful candidate will be offered a salary commensurate to experience and skills. The call will remain open until the position is filled but the first deadline for evaluation of candidates will be November 25, 2018. Please send your application to ccht at iit.it and applications at iit.it quoting ?CCHT Computer Vision Postdoc ? BC 75117? in the e-mail subject. Your application shall contain a detailed CV, a one-page research statement and contact information of two referees. Fondazione Istituto Italiano di Tecnologia (http://www.iit.it) is a non-profit institution created with the objective of promoting technological development and higher education in science and technology. Research at IIT is carried out in highly innovative scientific fields with state-of-the-art technology. Istituto Italiano di Tecnologia is an equal opportunity employer that actively seeks diversity in the workforce. Please note that the data that you provide will be used exclusively for the purpose of professional profiles? evaluation and selection and in order to meet the requirements of Istituto Italiano di Tecnologia. Your data will be processed by Istituto Italiano di Tecnologia, based in Genoa, Via Morego 30, acting as Data Controller, in compliance with the rules on protection of personal data, including those related to data security. Please also note that, pursuant to articles 15 et. seq. of European Regulation no. 679/2016 (General Data Protection Regulation), you may exercise your rights at any time by contacting the Data Protection Officer (phone +39 010 71781 - email: dpo at iit.it) -------------- next part -------------- An HTML attachment was scrubbed... URL: From fmschleif at googlemail.com Wed Oct 31 13:39:35 2018 From: fmschleif at googlemail.com (Frank-Michael Schleif) Date: Wed, 31 Oct 2018 18:39:35 +0100 Subject: Connectionists: (CFP-Reminder) ESANN Special Session (Streaming data analysis, concept drift and analysis of dynamic data sets ) Message-ID: -- Apologies in advance for multiple postings -- Call for Papers Special Session on 'Streaming data analysis, concept drift and analysis of dynamic data sets ' 24-26 April 2019, Bruges, Belgium https://www.elen.ucl.ac.be/esann/index.php?pg=specsess#streaming AIMS AND SCOPE Today many real life data are given in the form of streaming data. Prominent examples can be found in the context of IoT, in form of twitter feeds, click stream data, trading data and many other. Learning from this huge, heterogeneous and growing amount of data requires flexible learning models that can adapt over time and are capable to deal with potentially non-i.i.d., non-stationary input data. Additionally the underlying algorithms aim on processing of high-velocity and multi-channel data and have also to deal with a variety of phenomena like concept drift and novelty detection. This special session welcomes novel research about learning from data streams addressing common problem in the field of streaming data analysis. Computational intelligence methods have the potential to be used for efficient data streams processing but novel methods and mathematical and algorithmic approaches are needed. TOPICS We encourage submission of papers on novel methods for streaming data processing and streaming data analysis by means of computational intelligence and machine learning approaches, including but not limited to: - data analysis and pattern recognition approaches for streaming data - preprocessing approaches for streaming data - learning of heterogeneous data streams - adaptive data pre-processing and knowledge discovery - methods employing ex- and implicit data knowledge for non-stationary data - representation and modeling of multi-channel streaming data - approximation techniques for streaming data - online and incremental learning (dimensionality reduction, classification, clustering and regression, outlier detection) with a particular design for streaming data - data drift and shift handling, transfer learning - graph stream algorithms - security and privacy preservation on streaming data - active learning for data streams - application of deep learning with streaming data - particular interesting applications for streaming data analysis e.g. in IoT, recommender systems, social networks, sensor networks, web mining, text processing medicine ... IMPORTANT DATES Paper submission deadline : 19 November 2018 Notification of acceptance : 31 January 2019 Deadline for final papers : 20 February 2019 The ESANN 2019 conference : 24-26 April 2019 SPECIAL SESSION ORGANIZERS: Albert Bifet LTCI, T?l?com ParisTech - Universit? Paris-Saclay Paris, FRANCE Barbara Hammer, University of Bielefeld, Germany Frank-Michael Schleif, University of Appl. Sc. Wuerzburg-Schweinfurt, Germany and University of Birmingham, Birmingham, UK -- ------------------------------------------------------- Prof. Dr. rer. nat. habil. Frank-Michael Schleif School of Computer Science University of Applied Sciences W?rzburg-Schweinfurt Sanderheinrichsleitenweg 20 Raum I-3.35 Tel.: +49(0) 931 351 18127 97074 W?rzburg Honorable Research Fellow The University of Birmingham Edgbaston Birmingham B15 2TT United Kingdom - email: frank-michael.schleif at fhws.de http://promos-science.blogspot.de/ https://www.techfak.uni-bielefeld.de/~fschleif/ -------------------------------------------------------