From oksayakh at cs.iastate.edu Wed Oct 1 00:48:44 2008 From: oksayakh at cs.iastate.edu (Oksana Yakhnenko) Date: Tue, 30 Sep 2008 23:48:44 -0500 Subject: Connectionists: Call for papers: NIPS 2008 Workshop on Cost-Sensitive Learning Message-ID: <5E1828F7331645EAAD0EAEE21816908C@OksanaPC> Apologies if you are receiving multiple copies of this email, and please forward to interested parties. ----- Original Message ----- From: Oksana Yakhnenko To: colt at cs.uiuc.edu Sent: Friday, September 26, 2008 4:22 PM Subject: Call for papers: NIPS 2008 Workshop on Cost-Sensitive Learning ==Call for Papers: NIPS 2008 Workshop on Cost-Sensitive Learning== http://www.cs.iastate.edu/~oksayakh/cslworkshop_nips2008.html Description and background ------------------------ The goal of cost-sensitive learning is to minimize data acquisition costs while maximizing the accuracy of the learner/predictor. Many fields in machine learning attempt to solve cost-sensitive learning with strong simplifying assumptions. For example, in semi-supervised learning, class-labels are assumed to be expensive and features are implicitly assumed to have zero cost. In active learning, labels are again assumed to be expensive; however the learner may ask an oracle to reveal a label for unlabeled data for selected examples. Active feature acquisition assumes that obtaining features is expensive (but typically all features are assumed to be equally expensive), and the learner identifies instances for which complete information is most informative to classify a particular test sample. Inductive transfer learning and domain adaptation methods assume that training data for a particular task is expensive or but other data from other domains may be cheaper (although relative costs are usually not explicitly modeled). Cascaded classifier architectures are primarily designed in order to reduce the cost of acquiring features to classify a sample (a sample may be classified the moment the available data is sufficient to provide sufficient classification confidence, without waiting for all features to be obtained). There is an important but neglected common thread linking all of these different research communities. In particular, all these learning methods are motivated by the need to minimize the cost of data acquisition in many different application domains such as computer-aided medical diagnosis, computational linguistics, computational biology, and computer vision. Although all of these areas have felt the need for a principled solution to the problem, the partial solutions that have tried to solve the problem (eg semi-supervised learning, active learning, multi-task inductive transfer etc) rarely model the cost explicitly, and very little effort has been expended on modeling application specific characteristics. Recently to some papers have started modeling the acquisition costs directly, but there is a lot of scope for theoretically rigorous work on this topic. It is also important to explicitly model the requirements from real world application communities and to bridge it with the work on theory/algorithms. Goals --------------- The goal of the workshop is to bring together researchers interested in the application of cost-sensitive learning (computer vision, natural language processing, computer-aided diagnostics, computational biology) with researchers interested in theory & algorithms for learning when data acquisition is costly. The main aim is to focus attention on a practically important problem where practitioners have long sought theoretically sound algorithms but which has not been sufficiently addressed in the literature. A secondary goal is to bring together ideas from semi-supervised learning, active learning, feature acquisition, inductive transfer learning and other areas, in order that there may be more exchange of ideas across these (extremely active) communities. Topics of Interest ------------------------ We welcome both novel theory/algorithms and papers that highlight open problems and challenges in real-world applications which call for cost sensitive learning. Submissions on following topics are particularly encouraged: Algorithms/Theory: -active learning -semi-supervised learning -transfer learning -reinforcement learning -domain adaptation, -cascaded classifier learning -...and related. Applications which call for cost-sensitive learning: -computer vision -computational linguistics -natural language processing -computer-aided diagnosis -differential medical diagnosis -...and others. Paper submission ------------------------ We welcome papers of up to 8 pages in the NIPS 2008 format. The accepted papers will be available for downloading from the workshop website. Accepted papers will be either presented as a talk or poster (with poster spotlight). Papers should be emailed to the organizers at cslworkshop.nips.2008 at gmail.com. Please indicate whether you only wish to present a poster. Important Dates ------------------------ Deadline for submissions: October 17, 2008 Notification of acceptance: November 7, 2008 Workshop date: December 13, 2008 Organizers ------------------------ Balaji Krishnapuram (Siemens Medical Solutions USA) Shipeng Yu (Siemens Medical Solutions USA) Oksana Yakhnenko (Iowa State University) R. Bharat Rao (Siemens Medical Solutions USA) Lawrence Carin (Duke University) Invited Speakers ------------------------ John Shawe-Taylor (University College, London) Volker Tresp (University of Munich) Program Committee ------------------------ Chiru Bhattacharya (IISc, Bangalore) Rich Caruana (Cornell) Mario Figueiredo (IST, Portugal) Yves Grandvalet (UTC, France) Yan Liu (IBM) Prem Melville (IBM) Sunita Sarawagi (IIT Bombay) Fei Sha (USC & Yahoo research) Volker Tresp (Siemens) Kai Yu (NEC Research) Ulf Brefeld (Technische Universitaet, Berlin) Steffen Bickel (Max Planck Institute of Computer Science) Vikas Sindhwani (IBM) Johannes F?rnkranz (Darmstadt University) John Shawe-Taylor (University College, London) Sanjoy Dasgupta (University of California, San Diego) Steven Abney (University of Michigan) -------------- next part -------------- An HTML attachment was scrubbed... URL: https://mailman.srv.cs.cmu.edu/mailman/private/connectionists/attachments/20081001/c2addbd2/attachment.html From risi at cs.columbia.edu Wed Oct 1 16:50:50 2008 From: risi at cs.columbia.edu (Risi Kondor) Date: Wed, 1 Oct 2008 21:50:50 +0100 Subject: Connectionists: NIPS Symposium and Workshop on Algebraic Methods in Machine Learning Message-ID: <95BB4A70-A19C-49A7-878D-B1F99D6F5576@cs.columbia.edu> WORKSHOP ANNOUNCEMENT AND CALL FOR PRESENTATIONS Algebraic Methods in Machine Learning NIPS 08 Symposium and Workshop December 11-12, Vancouver and Whistler, BC URL: http://www.gatsby.ucl.ac.uk/~risi/AML08/ There has recently been a surge of interest in algebraic methods in machine learning. In no particular order, this includes: new approaches to ranking problems; the budding field of algebraic statistics; and various applications of non-commutative Fourier transforms. The aim of the symposium and workshop is to bring together these distinct communities, explore connections, and showcase algebraic methods to the machine learning community at large. We invite submissions for oral and poster presentations on algebraic methods in machine learning. Submissions should consist of a 1-2 page abstract and should be emailed to amlworksho... at gmail.com in pdf or ps format by 10/24/2008. Acceptance/rejection notices will be emailed by November 3. Following the symposium and workshop, we intend to invite the workshop participants to submit longer documents for inclusion as chapters in an edited book on algebraic methods in machine learning. Organizers: Risi Kondor Gatsby Computational Neuroscience Unit University College London Guy Lebanon College of Computing Georgia Institute of Technology Jason Morton Department of Mathematics Stanford University -------------- next part -------------- An HTML attachment was scrubbed... URL: https://mailman.srv.cs.cmu.edu/mailman/private/connectionists/attachments/20081001/abb92a97/attachment.html From gert at ece.ucsd.edu Thu Oct 2 11:10:46 2008 From: gert at ece.ucsd.edu (Gert Lanckriet) Date: Thu, 2 Oct 2008 08:10:46 -0700 Subject: Connectionists: Call for NIPS 2008 Kernel Learning Workshop Submissions Message-ID: <4E76E6E4-16C0-4D32-A6E7-114DE49BDAD1@ece.ucsd.edu> [please distribute - apologies for multiple postings] ******************************************************************* Call for NIPS 2008 Kernel Learning Workshop Submissions ******************************************************************* Submissions are solicited for the Kernel Learning workshop to be held on December 13th, 2008 at this year's NIPS workshop session in Whistler, Canada. The workshop will focus on automatic kernel selection; and more broadly on feature selection, multi-task learning and multi-view learning. Submissions to the workshop should be on the topic of using sampled data to select or learn a kernel function or kernel matrix appropriate for the specific task at hand. Submissions are not constrained regarding the areas in which which the learned kernel is applied: these can include classification, regression, and ranking, where the use of kernels is ubiquitous, and different settings including inductive, transductive, or semi- supervised learning. Presentations on the closely related topics of feature selection, multi-task learning and multi-view learning are also encouraged. Submissions may focus on theoretical, algorithmic or large-scale empirical results. Accepted submissions will results in a 25 minute talk or a poster presentation. The deadline for submission will be October 24 and notifications will be sent out by November 7th. The submission should be no more than four pages long in in NIPS format (though it may make reference to a longer technical report if appropriate), and should be sent to rostami at cs.nyu.edu. The program committee will consist of the workshop organizers and the invited speakers, and can be found on the workshop webpage www.cs.nyu.edu/learning_kernels as well as other important information. Your Workshop Organizers, Corinna Cortes Arthur Gretton Gert Lanckriet Mehryar Mohri Afshin Rostamizadeh -------------- next part -------------- An HTML attachment was scrubbed... URL: https://mailman.srv.cs.cmu.edu/mailman/private/connectionists/attachments/20081002/4b38e714/attachment.html From mkc at CS.Princeton.EDU Thu Oct 2 13:21:25 2008 From: mkc at CS.Princeton.EDU (Melissa Carroll) Date: Thu, 02 Oct 2008 13:21:25 -0400 Subject: Connectionists: Call for abstracts: NIPS 2008 Workshop on Statistical Learning for fMRI Message-ID: <48E50315.1010907@cs.princeton.edu> Call for Abstracts New Directions in Statistical Learning for Meaningful and Reproducible fMRI Analysis NIPS 08 Workshop, Whistler, Canada Important Dates * Submission deadline (2 page abstract): October 31 * Notification of acceptance: November 7 * Workshop date: December 13 URL: http://www.cs.princeton.edu/mlneuro/nips08 Overview Over the last several years, statistical learning methods have become mainstream in the analysis of Functional Magnetic Resonance Imaging (fMRI) data, spurred on by a growing consensus that meaningful neuroscientific models built from fMRI data should be capable of accurate predictions of behavior or neural functioning. Two years ago, the NIPS workshop "New Directions on Decoding Mental States from fMRI Data" reflected on progress so far and future directions. Most of the open questions discussed considered how to advance beyond single-subject, single-task, voxel-by-voxel, static analysis to better uncover the true underlying activation patterns and thus better characterize brain functioning. Two years later, the field has continued to see great success in predictive modeling, as the results of the 2006 and 2007 Pittsburgh Brain Activity Interpretation Competition demonstrate, convincing most neuroscientists that there is tremendous potential in the decoding of brain states using statistical learning. Along with this realization, though, has come a growing recognition of the limitations inherent in using black box methods for drawing neuroscientific interpretations. The primary challenge now in the field is how best to exploit statistical learning to answer scientific questions by incorporating domain knowledge and embodying hypotheses about various cognitive processes. Further advances in the field will require resolution of many open questions, including the following: Variability/Robustness: * To what extent do patterns in fMRI replicate across trials, subjects, tasks, and studies? * To what extent are processes that are observable through the BOLD response measured by fMRI truly replicable across these different conditions? * How similar is the neural functioning of one subject to another? Data Representations: * The most common data representation continues to consider voxels as static and independent, and examples are i.i.d.; however, voxels represent arbitrary spatial subdivisions of the brain space; hence, activation patterns almost surely do not lie in voxel space. What are the true, modular activation structures? * What is the relationship between similarity in cognitive state space and similarity in brain state space? * Brain functioning is clearly a dynamical system, and the fMRI images indirectly measuring this functioning are not static and independent, but rather a snapshot in time. To what extent can causality be inferred from fMRI? Scope This 1-day workshop will serve to engage leaders in the field in a debate about these issues while providing an opportunity for presentation of cutting-edge research addressing these questions. The workshop will begin with a tutorial introduction to the broad area of statistical learning for fMRI analysis, and will then be divided into 2 sessions roughly corresponding to the 2 topics outlined above, with each session featuring an overview talk on the issue by a leader in the field, followed by shorter submitted talks and a panel discussion. The workshop will conclude with a group discussion on controversies in generalizability, robustness, data representations, and other topics. Depending on the number of submissions, we may also have a poster session for additional submitted abstracts. The target audience will include both neuroscientists and statistical learning researchers working with fMRI, as well as a more general audience from both fields. Example topics: - Cross-subject / cross-study / cross-task analysis - Variable selection / dimensionality reduction / sparsity - Hierarchical models - Stimulus space representations - Hypothesis generation and testing / experimental design - Functional connectivity analysis / network learning - Dynamic causal modeling Submissions We invite abstracts addressing any of the questions above or other related issues. We welcome presentations of completed work or work-in-progress, as well as papers discussing potential research directions and surveys of recent developments. If you would like to present at the workshop, please send an abstract at most 2 pages long (NIPS Format), excluding citations, PDF preferred, to mkc at princeton.edu as soon as possible, and no later than October 31, 2008. Acceptance decisions will be sent on November 7, 2008. Organizing committee: Melissa Carroll, Princeton University Irina Rish, IBM Francisco Pereira, Princeton University Guillermo Cecchi, IBM Invited speakers: Tutorial: Francisco Pereira, Princeton University Lars Kai Hansen, Technical University of Denmark Jean-Baptiste Poline/Bertrand Thirion, Neurospin From jason at cs.jhu.edu Fri Oct 3 00:35:02 2008 From: jason at cs.jhu.edu (Jason Eisner) Date: Fri, 03 Oct 2008 00:35:02 -0400 Subject: Connectionists: Call for Summer Research Proposals Message-ID: <87vdwal2ix.fsf@cs.jhu.edu> JHU Summer Workshops CALL FOR TEAM RESEARCH PROPOSALS Deadline: Wednesday, October 20, 2008. One-page research proposals are invited for the 15th annual, NSF-sponsored summer research workshop at Johns Hopkins University. Proposals should be suitable for a six-week team exploration, and should aim to advance the state of the art in Machine Intelligence, with a current focus on Human Language Technology (HLT), Computer Vision (CV) and fundamental Machine Learning (ML). Research topics selected for investigation by teams in previous workshops may serve as good examples for your proposal. (See http://www.clsp.jhu.edu/workshops.) Proposals that address one of the following long-term challenges are particularly encouraged: * ROBUST TECHNOLOGY FOR SPEECH: Technologies like speech transcription, speaker identification, and language identification share a common weakness: accuracy degrades disproportionately with seemingly small changes in input conditions (microphone, genre, speaker, dialect, etc.), where humans are able to adapt quickly and effectively. The aim is to develop technology whose performance would be minimally degraded by input signal variations. * KNOWLEDGE DISCOVERY FROM LARGE UNSTRUCTURED TEXT COLLECTIONS: Scaling natural language processing (NLP) technologies including parsing, information extraction, question answering, and machine translation to very large collections of unstructured or informal text, and domain adaptation in NLP is of interest. * VISUAL SCENE INTERPRETATION: New strategies are needed to parse visual scenes or generic (novel) objects, analyzin an image as a set of spatially related components. Such strategies may integrate global top-down knowledge of scene structure (e.g., generative models) with the kind of rich bottom-up, learned image features that have recently become popular for object detection. They will support both learning and efficient search for the best analysis. * UNSUPERVISED AND SEMI-SUPERVISED LEARNING: Novel techniques that do not require extensive quantities of human annotated data to address any of the challenges above could potentially make large strides in machine performance as well as lead to greater robustness to changes in input conditions. Semi-supervised and unsupervised learning techniques with applications to HLT and CV are therefore of considerable interest. An independent panel of experts will screen all received proposals for suitability. Results of this screening will be communicated no later than October 22, 2008. Authors passing this initial screening will be invited to Baltimore to present their ideas to a peer-review panel on November 7-9, 2008. It is expected that the proposals will be revised at this meeting to address any outstanding concerns or new ideas. Two or three research topics and the teams to tackle them will be selected for the 2009 workshop. We attempt to bring the best researchers to the workshop to collaboratively pursue the selected topics for six weeks. Authors of successful proposals typically become the team leaders. Each topic brings together a diverse team of researchers and students. The senior participants come from academia, industry and government. Graduate student participants familiar with the field are selected in accordance with their demonstrated performance, usually by the senior researchers. Undergraduate participants, selected through a national search, will be rising seniors who are new to the field and have shown outstanding academic promise. If you are interested in participating in the 2009 Summer Workshop we ask that you submit a one-page research proposal for consideration, detailing the problem to be addressed. If your proposal passes the initial screening, we will invite you to join us for the organizational meeting in Baltimore (as our guest) for further discussions aimed at consensus. If a topic in your area of interest is chosen as one of the two or three to be pursued next summer, we expect you to be available for participation in the six-week workshop. We are not asking for an ironclad commitment at this juncture, just a good faith understanding that if a project in your area of interest is chosen, you will actively pursue it. Proposals should be submitted via e-mail to clsp at jhu.edu by 4PM EST on Mon, October 20, 2008. From wychen at cs.ucsb.edu Thu Oct 2 09:57:44 2008 From: wychen at cs.ucsb.edu (Wen-Yen Chen) Date: Thu, 2 Oct 2008 06:57:44 -0700 Subject: Connectionists: MATLAB spectral clustering package Message-ID: <20081002135743.GA29469@cab.cs.ucsb.edu> Dear MLers, We announce a MATLAB spectral clustering package for large data sets: http://www.cs.ucsb.edu/~wychen/sc.html Our tool can handle large data sets (200,000 RCV1 data) on a 4GB memory general machine. Spectral clustering algorithm has been shown to be more effective in finding clusters than some traditional algorithms such as k-means. To perform clustering on large data sets, we implement various ways of approximating the dense similarity matrix. An accompanying paper is available at http://www.cs.ucsb.edu/~wychen/publications/PSC08.pdf For any feedback, please feel free to contact Wen-Yen Chen and Chih-Jen Lin . Thanks, Wen-Yen From jebara at cs.columbia.edu Thu Oct 2 10:59:07 2008 From: jebara at cs.columbia.edu (Tony Jebara) Date: Thu, 2 Oct 2008 10:59:07 -0400 Subject: Connectionists: CFP: NIPS Workshop on Analyzing Graphs: Theory and Applications References: Message-ID: <07392A67-CBB1-4F6D-BC16-07E6E534ED2A@cs.columbia.edu> NIPS 2008 Workshop on Analyzing Graphs: Theory and Applications Call For Papers -- Apologies if you receive multiple copies of this announcement -- -- Please forward to anyone who might be interested -- ##################################################################### CALL FOR PAPERS Analyzing Graphs: Theory and Methods a workshop in conjunction with 22nd Annual Conference on Neural Information Processing Systems (NIPS 2008) December 12, 2008 Whistler, BC, Canada http://research.yahoo.com/workshops/nipsgraphs2008/ Deadline for Submissions: Friday, October 31, 2008 Notification of Decision: Friday, November 10, 2008 ##################################################################### Overview: Recent research in machine learning and statistics has seen the proliferation of computational methods for analyzing graphs and networks. These methods support progress in many application areas, including the social sciences, biology, medicine, neuroscience, physics, finance, and economics. This workshop will address statistical, methodological and computational issues that arise when modeling and analyzing graphs. The workshop aims to bring together researchers from applied disciplines such as sociology, economics, medicine and biology with researchers from mathematics, physics, statistics and computer science. Different communities use diverse ideas and mathematical tools; our goal is to foster cross-disciplinary collaborations and intellectual exchange. Presentations will include novel graph models, the application of established models to new domains, theoretical and computational issues, limitations of current graph methods and directions for future research. Online Submissions: ------------------- We welcome the following types of papers: 1. Research papers that introduce new models or apply established models to novel domains, 2. Research papers that explore theoretical and computational issues, or 3. Position papers that discuss shortcomings and desiderata of current approaches, or propose new directions for future research. All submissions will be peer-reviewed; exceptional work will be considered for oral presentation. We encourage authors to emphasize the role of learning and its relevance to the application domains at hand. In addition, we hope to identify current successes in the area, and will therefore consider papers that apply previously proposed models to novel domains and data sets. Submissions should be 4-to-8 pages long, and adhere to NIPS format (http://nips.cc/PaperInformation/StyleFiles). Please email your submissions to: nipsgraphs2008 at yahoo.com Deadline for Submissions: Friday, October 31 2008 Notification of Decision: Friday, November 10 2008 Format This is a one-day workshop. The program will feature invited talks, poster sessions, poster spotlights, and a panel discussion. All submissions will be peer-reviewed; exceptional work will be considered for oral presentation. Publication: Accepted papers will be distributed on a CD and made available for download. We are negotiating the publication of the accepted papers in print form. Organizers: ----------- Edo Airoldi, Princeton University, eairoldi at princeton.edu David Blei, Princeton University, blei at cs.princeton.edu Jake Hofman, Yahoo! Research, hofman at yahoo-inc.com Tony Jebara, Columbia University, jebara at cs.columbia.edu Eric Xing, Carnegie Mellon University, epxing at cs.cmu.edu Program Committee ----------------- David Banks (Duke University) Peter Bearman (Columbia University) Joseph Blitzstein (Harvard University) Kathleen Carley (Carnegie Mellon University) Aaron Clauset (Santa Fe Institute) William Cohen (Carnegie Mellon University) Stephen Fienberg (Carnegie Mellon University) Lise Getoor (University of Maryland) Peter Hoff (University of Washington) Eric Horvitz (Microsoft Research) Alan Karr (National Institute of Statistical Sciences) Jure Leskovec (Carnegie Mellon University) Kevin Murphy (University of British Columbia) Eugene Stanley (Boston University) Lyle Ungar (Universitoy of Pennsylvania) Chris Wiggins (Columbia University) Thank you, we look forward to receiving your submissions! Edo Airoldi, David Blei, Jake Hofman, Tony Jebara & Eric Xing -------------- next part -------------- An HTML attachment was scrubbed... URL: https://mailman.srv.cs.cmu.edu/mailman/private/connectionists/attachments/20081002/8dc69936/attachment.html From nuno at ece.ucsd.edu Wed Oct 1 12:42:16 2008 From: nuno at ece.ucsd.edu (Nuno Vasconcelos) Date: Wed, 1 Oct 2008 09:42:16 -0700 Subject: Connectionists: FW: Post-doctoral position at UCSD Message-ID: <005f01c923e4$ab6246b0$5441a8c0@svcdc.svcl.ucsd.edu> POSITION: Postdoctoral Fellow in Medical Image Analysis LOCATION: University of California, San Diego A postdoctoral position is immediately available in a project involving machine learning and computer vision for medical image analysis. The position is specifically related to the development of image guidance techniques in cancer radiotherapy, namely tumor tracking in fluoroscopic images. The project involves a collaboration across two UCSD departments: the Center for Advanced Radiotherapy Technologies, Department of Radiation Oncology, and the Statistical Visual Computing Laboratory, Department of Electrical Engineering. The candidate will interact with the heads of the two laboratories, Profs. Steve Jiang and Nuno Vasconcelos. A Ph.D. in engineering, computer science, physics, or related disciplines, with strong programming skills, is required. Experience with machine learning and computer vision is desirable. Topics of potential interest include interest point detection, visual tracking, dynamic textures, feature selection, graphical models, and kernel-based regression, among others. Training in clinical medical physics may be provided. Initial appointment will be for one year with potential renewal for a second year. Interested candidates should e-mail a CV to the contact below. CONTACT: Brianne Hennon Research Administrative Assistant Center for Advanced Radiotherapy Technologies Department of Radiation Oncology University of California, San Diego 3855 Health Sciences Dr. #0843 La Jolla, CA 92093-0843 Tel: (858)822-5036 Fax: (858)822-6078 http://radonc.ucsd.edu/Research/CART http://www.svcl.ucsd.edu From g.goodhill at uq.edu.au Wed Oct 1 20:35:56 2008 From: g.goodhill at uq.edu.au (Geoffrey Goodhill) Date: Thu, 2 Oct 2008 10:35:56 +1000 Subject: Connectionists: Chair of Statistics position available Message-ID: CHAIR OF STATISTICS, THE UNIVERSITY OF QUEENSLAND The Statistics and Probability Group is in the Discipline of Mathematics in the School of Physical Sciences, which is to become the School of Mathematics and Physics from the beginning of 2009. The current research interests of the Group are in a number of areas, including bioinformatics, biostatistics, computational statistics, discriminant and cluster analyses, experimental design, image analysis, machine learning, mixture modelling, multivariate analysis, and applied probability and stochastic processes. The Group has established ongoing collaborations with other disciplines, particularly in the biological and medical sciences, bioinformatics, engineering and information technology, as well as with industry and government bodies. The role: The successful appointee will be expected to provide leadership in research and teaching in Statistics, and to be a strong advocate of Statistics within the University and in the broader academic, business, industrial, and political community. He or she will be expected to further raise the University's strong international profile in Statistics, and to attract postgraduate students and postdoctoral researchers to the University. The person: Candidates with research interests in any area of Applied Statistics are encouraged to apply. The appointee must have an outstanding international research record in Statistics. He/she should possess a proven record of attracting competitive research funding plus demonstrated potential for research collaboration with other Disciplines. Applicants must have a proven record of teaching excellence plus experience in developing curricula for a broad range of courses. Remuneration: The remuneration package will be $129,654.41 p.a., plus employer superannuation contributions of 17% (total package will be $151,695.66). This is a full-time, continuing appointment at Academic Level E. Contact: Obtain the position description and selection criteria at http://seek.com.au/jobsearch/index.ascx?AdvertiserID=852832. To discuss the role, contact Professor Geoff McLachlan, telephone 07-3365 2150 or email gjm at maths.uq.edu.au. Send applications to Louise Harrison, Human Resources Officer, Faculty of Engineering, Physical Sciences & Architecture, The University of Queensland, St Lucia, Qld 4072, or email applications at epsa.uq.edu.au. Applications close 31 October 2008. From oliver.obst at csiro.au Sat Oct 4 09:23:26 2008 From: oliver.obst at csiro.au (Oliver Obst) Date: Sat, 4 Oct 2008 23:23:26 +1000 Subject: Connectionists: CfP: International Workshop on Guided Self-Organisation (GSO-2008), 24-27 Nov 08, Sydney Message-ID: <6731391D-BE2B-4F84-B3AE-7251B3912846@csiro.au> Hi, The First International Workshop on Guided Self-Organisation (GSO-2008) will be held 24-27 November 2008, in Sydney, Australia: http://www.prokopenko.net/gso.html The balance between design and self-organisation is the main theme of GSO-2008. The following topics are of special interest: - information-driven self-organisation (IDSO), - systems biology, - complex systems and networks, - computational neuroscience and neuroinformatics; - applications of GSO to cooperative and modular robotics, - applications of GSO to sensor networks and energy grids. The workshop is open to researchers in self-organising systems, though for practical considerations the total number of participants will be limited to 50 at the maximum. If you are interested in attending and/ or presenting, please send an email to by 31 October 2008, with a title and an abstract (1 page) of your possible contribution. Following the Workshop, a formal call for papers will be issued for a special journal issue. Program Committee: Mikhail Prokopenko, CSIRO, Australia (Chair) Nihat Ay, MPI, Germany Gianluca Baldassarre, ISTC-CNR, Italy Fabio Boschetti, CSIRO, Australia Michael Bruenig, CSIRO, Australia Mikhail Burtsev, RAS, Russia Ralf Der, MPI, Germany Stefano Nolfi, ISTC-CNR, Italy Oliver Obst, CSIRO, Australia Daniel Polani, University of Hertfordshire, UK Ivan Tanev, Doshisha University, Japan Larry Yaeger, Indiana University, USA Albert Zomaya, University of Sydney -- Oliver Obst form follows function (Louis Sullivan). Fon: +61 2 9325 3278 http://oliver.obst.eu/ Autonomous Systems Lab CSIRO ICT Centre http://www.ict.csiro.au/asl/ -------------- next part -------------- A non-text attachment was scrubbed... Name: smime.p7s Type: application/pkcs7-signature Size: 2423 bytes Desc: not available Url : https://mailman.srv.cs.cmu.edu/mailman/private/connectionists/attachments/20081004/57b0d975/smime-0001.bin From Dave_Touretzky at cs.cmu.edu Sun Oct 5 00:34:08 2008 From: Dave_Touretzky at cs.cmu.edu (Dave_Touretzky@cs.cmu.edu) Date: Sun, 05 Oct 2008 00:34:08 -0400 Subject: Connectionists: NIPS workshop CfP: Parallel Implementations of Learning Algorithms Message-ID: <8150.1223181248@ammon.boltz.cs.cmu.edu> NIPS08 Workshop Call for Posters: Parallel Implementations of Learning Algorithms: What Have You Done For Me Lately? Overview: Interest in parallel hardware concepts, including multicore, specialized hardware, and multimachine, has recently increased as researchers have looked to scale up their concepts to large, complex models and large datasets. In this workshop, a panel of invited speakers will present results of investigations into hardware concepts for accelerating a number of different learning and simulation algorithms. Additional contributions will be presented in poster spotlights and a poster session at the end of the one-day workshop. Our intent is to provide a broad survey of the space of hardware approaches in order to capture the current state of activity in this venerable domain of study. Approaches to be covered include silicon, FPGA, and supercomputer architectures, for applications such as Bayesian network models of large and complex domains, simulations of cortex and other brain structures, and large-scale probabilistic algorithms. Potential participants include researchers interested in accelerating their algorithms to handle large datasets, and systems designers providing such hardware solutions. The oral presentations will include plenty of time for questions and discussion, and the poster session at the end of the workshop will afford further opportunities for interaction among workshop participants. Confirmed Speakers: - David Andersen, Carnegie Mellon University Using a Fast Array of Wimpy Nodes. - Michael Arnold, Salk Institute Multi-Scale Modeling in Neuroscience - Dan Hammerstrom, Portland State University Nanoelectronics: The Original Positronic Matrix? - Kenneth Rice, Clemson University A Neocortex-Inspired Cognitive Model on the Cray XD1 - Robert Thibadeau, Seagate Research When (And Why) Storage Devices Become Computers - Additional speakers TBA. Important Dates: October 31, 2008 Poster abstract submission deadline November 7, 2008 Notification of acceptance December 12 or 13 Workshop at NIPS How To Submit: Algorithm developers, hardware developers, and researchers building large-scale applications are all encouraged to present their work at the workshop. Send a brief abstract (one page should suffice) in any format describing the approach and results you wish to present in poster form at the meeting to. David S. Touretzky, Carnegie Mellon University, dst at cs.cmu.edu. Submissions are due by October 31; decisions will be announced by November 7. Authors of accepted posters will be asked to give a 2 minute spotlight presentation before the start of the poster session. Workshop Organizing Committee: Robert Thibadeau, Seagate Research Dan Hammerstrom, Portland State University David Touretzky, Carnegie Mellon University Tom Mitchell, Carnegie Mellon University From B.Kappen at science.ru.nl Sun Oct 5 09:40:36 2008 From: B.Kappen at science.ru.nl (Bert Kappen) Date: Sun, 5 Oct 2008 15:40:36 +0200 (CEST) Subject: Connectionists: full professor stochastics/machine learning/comp.neuroscience Radboud University Nijmegen Message-ID: Radboud University Nijmegen Faculty of Science We invite applications for a position of Professor of Stochastics (Hoogleraar Stochastiek) (1.0 fte) with preference for specializations with connections to theoretical neuroscience. The Faculty of Science consists of seven research institutes covering the natural sciences, mathematics, and computer science. Mathematics is part of the Institute for Mathemat- ics, Astrophysics and Particle Physics (IMAPP) and consists of three research groups: Mathematical Physics, Algebra and Logic, and Stochastics. In the past Stochastics has been oriented towards ^Lnance but retirement makes a change of direction possible. The university has considerable strength in neuroscience research that the new professor could connect to. In this respect, the research at the Donders Center for Neuroscience is par- ticularly relevant. Job description Major tasks of the appointed professor will be to de^Lne the direction of research in stochastics, attract funding, and build up a research group. The professor will be responsible for the teaching program in probability and statistics within our B.Sc. and M.Sc. programs in mathematics, including the development of a new stochastics track at the Master's level. The ability to represent IMAPP towards other institutes inside and outside the faculty, including the international level, is also an important asset. Last but not least, the successful candidate is expected to actively and enthusiastically participate in the outreach ert of the department directed at both pupils and the general public. For a highly motivated and promising candidate close to having successfulcient credentials for a professorship, an appointment at a lower level with tracking towards the professor- ship may be considered. Qualifications excellence in research, evidenced by the publication record and invitations to speak at major conferences excellence in teaching, as evidenced by student evaluations and peer reviews good leadership and communication skills ability to obtain external funding Terms of employment This announcement is for a permanent position of full professor at 1.0 fte. The position is open and may be ^Llled immediately. The salary will be be- tween 4,803 and 6,995 gross per month on a full time basis, depending on quali^Lcations and experience. Conditions are based on the Collective Employement Agreement of the Dutch Universities. Recently a female professor in Mathematics has been appointed at Radboud University. We are committed to increasing participation of women in science and applications from female candidates are particularly encouraged. For additional information please contact Mai Gehrke, e-mail: mgehrke at math.ru.nl, tel. +31 (0)24 365-3220 or Erik Koelink, e-mail: e.koelink at math.ru.nl, tel. +31 (0)24 365-2597. How to apply The application, with reference to vacancy number 62.27.08, should include a letter of application, curriculum vitae, and contact details of at least three references. It can be sent by e-mail to pz at science.ru.nl or by post to: FNWI Personeel en Organisatie attn. mevr. Marielle Nelemans Postbus 9010 6500 GL Nijmegen The Netherlands Applications will be accepted until the position is filled. To ensure full consideration, applications must be received by November 3, 2008. -- Prof. dr. H.J. Kappen SNN Radboud University Nijmegen URL: www.snn.ru.nl/~bertk The Netherlands tel: +31 24 3614241 fax: +31 24 3541435 B.Kappen at science.ru.nl mobile: +31 6 520 78 210 From carnevalet at sbcglobal.net Sun Oct 5 11:45:57 2008 From: carnevalet at sbcglobal.net (Ted Carnevale) Date: Sun, 05 Oct 2008 11:45:57 -0400 Subject: Connectionists: Special topics at the NEURON course Message-ID: <48E8E135.10504@sbcglobal.net> A few seats are still available for this year's NEURON course at the annual SFN meeting, which will take place on Friday, Nov. 14, in Washington, DC. For the course description and online registration form, see http://www.neuron.yale.edu/dc2008.html The registration deadline is Friday, Oct. 17--less than two weeks from today--so you should act quickly to sign up. As in prior years, the course will cover a broad span of topics that range from how to get started, to expert level tips for the most productive usage of NEURON. In addition, this year's course will present the latest advances in two very rapidly moving areas: 1. Using Python with NEURON. Until recently, models have been specified with hoc and/or NEURON's GUI tools. But now it is possible to use Python in conjunction with hoc, or even instead of hoc. This is very important because it puts a very powerful, modern programming language in the hands of NEURON users, and gives them access to the large, rapidly expanding, and freely available libraries of scientific software written in Python. 2. Parallel simulations. Over the past few years, NEURON gained the ability to take advantage of parallel computer hardware in order to accelerate simulations. Efficient parallel simulation, with speedup proportional to the number of processors, is now possible for a wide range of problems on a wide range of parallel hardware. The most recent advance, with perhaps the greatest potential for benefiting the largest number of users, is multithreaded execution of simulations on multicore workstations. For some time now, all new Macs, and most new PCs, come with multicore processors. Attend the NEURON course to find out how to make your simulations take advantage of all that latent processing power! From bazhenov at salk.edu Tue Oct 14 13:48:11 2008 From: bazhenov at salk.edu (Maxim Bazhenov) Date: Tue, 14 Oct 2008 10:48:11 -0700 Subject: Connectionists: Postdoctoral position in computational neuroscience Message-ID: <48F4DB5B.9040306@salk.edu> A full-time postdoctoral position in computational neuroscience is available immediately at the Institute for Integrative Genome Biology (http://www.genomics.ucr.edu/) and the Department of Cell Biology and Neuroscience at the University of California, Riverside. Research in our laboratory focuses on understanding cellular and network mechanisms underlying normal and paroxysmal oscillations in the brain and the role of neuronal oscillations and synchrony in information processing and behavior. Specific projects include: (1) Studying cellular and network mechanisms for normal (sleep, attentive states) and abnormal (epilepsy) oscillations in the thalamocortical system; (2) Studying role of oscillations and synchrony in olfactory coding ? this project is targeted to discover the general principles and the neural circuitry involved in the encoding of sensory information in the brain. More information about our research is available at http://www.snl.salk.edu/~bazhenov/ Successful candidate will join research team including computational neuroscience labs from UC Riverside, UC San Diego and Salk Institute, and will be responsible for designing network models based on experimental data, model analysis and may be involved in experimental testing of the model predictions. Qualified applicants are expected to have experience in computational neuroscience including conductance-based neural modeling. Programming experience with C/C++ and Matlab is very desirable. The UC Riverside campus is located in the heart of Riverside County within 1-hour drive from the cities of Los Angeles, San Diego and Irvine. The University of California offers excellent benefits. Salary is based on background and research experience. The initial appointment will be for 1 year with a possibility of extension up to 3-4 years. Applicants should send a brief statement of research interests, a CV and the names of three references electronically to Maxim Bazhenov at bazhenov at salk.edu or maksim.bazhenov at ucr.edu -- Maxim Bazhenov, Ph.D. Associate Professor Department of Cell Biology and Neuroscience University of California Riverside, CA 92521 Ph: 951-827-4370 http://www.snl.salk.edu/~bazhenov/ From csadmin at physics.usyd.edu.au Tue Oct 7 21:25:07 2008 From: csadmin at physics.usyd.edu.au (Hildegunn Gaustad) Date: Wed, 08 Oct 2008 12:25:07 +1100 Subject: Connectionists: Position Vacant: Research Fellow in Theoretical/Computational Neuroscience or Sleep Research Message-ID: <48EC0BF3.1090705@Physics.usyd.edu.au> Dear Colleague, The University of Sydney is currently advertising a Research Fellowship in Theoretical/Computational Neuroscience or Sleep Research (reference number 139340). If you know of someone who might be interested, please draw the following link to their attention: http://www.usyd.edu.au/jobs/index.shtml Best regards, Prof. Peter Robinson From d.polani at herts.ac.uk Tue Oct 14 18:52:48 2008 From: d.polani at herts.ac.uk (Daniel Polani) Date: Wed, 15 Oct 2008 00:52:48 +0200 Subject: Connectionists: Call for contributions: NIPS Workshop on Principled Theoretical Frameworks for the Perception-Action Cycle Message-ID: <18677.8896.959172.990709@perm.feis.herts.ac.uk> //////////////////////////////////////////////////////////////////////// PRINCIPLED THEORETICAL FRAMEWORKS FOR THE PERCEPTION-ACTION CYCLE NIPS 2008 WORKSHOP December 12(13), Whistler, BC, Canada //////////////////////////////////////////////////////////////////////// Description ------------ A significant emphasis in trying to achieve adaptation and learning in the perception-action cycle of agents lies in the development of suitable algorithms. While partly these algorithms result from mathematical constructions, in modern research much attention is given to methods that mimic biological processes. However, mimicking the apparent features of what appears to be a biologically relevant mechanism makes it difficult to separate the essentials of adaptation and learning from accidents of evolution. This is a challenge both for the understanding of biological systems as well as for the design of artificial ones. Therefore, recent work is increasingly concentrating on identifying general principles rather than individual mechanisms for biologically relevant information processing. One advantage is that a small selection of principles can give rise to a variety of - effectively equivalent - mechanisms. The ultimate goal is to attain a more transparent and unified view on the phenomena in question. Possible candidates for such principles governing the dynamics of the perception-action cycle include but are not limited to information theory, Bayesian models, energy-based concepts or group-theoretical principles. The workshops aims at bringing together various principle-based directions for the investigation of various aspects of the perception-action cycle and at identifying promising directions of work. Participation ------------- We invite submissions for oral presentations on principled approaches to model and understand the perception-action loop. The submissions should be in the form of long (4-6 pages) or short (1/2-1 page) abstracts. Timely and novel work, as well as work in progress, or position papers will be considered, but also more mature work - please indicate in your submission for which you opt. We aim to place the abstracts on the workshop website. Submissions in PDF (NIPS format) should be emailed to d.polani at herts.ac.uk no later than 3. November (23:59 PST, sharp) and with the subject line "NIPS 2008 Workshop Submission". The notification of acceptance will be sent out on 6. November, 2008. All accepted submissions will have the opportunity for oral presentation, and ample opportunity for discussion is integrated in the workship. Prospective Audience -------------------- Researchers interested in the general picture of the perception-action cycle, both in biology and general AI, robotics, learning in embodied agents, bio-inspired AI. Organizers ---------- Daniel Polani, University of Hertfordshire, UK Naftali Tishby, The Hebrew University Jerusalem, Israel From terry at salk.edu Mon Oct 6 18:23:12 2008 From: terry at salk.edu (Terry Sejnowski) Date: Mon, 06 Oct 2008 15:23:12 -0700 Subject: Connectionists: NIPS 08 Workshop - Dec 13 - Cortical Microcircuits - Whistler In-Reply-To: Message-ID: NIPS 2008 Workshop - Whistler Canada - http://nips.cc/Conferences/2008/Program/ Cortical Microcircuits and their Computational Functions Saturday 13th December 2008 Organizers: Terry Sejnowski, Salk Institute, Tomaso Poggio, MIT Workshop Description: There are around 100,000 neurons under a mm^2 of cerebral cortex and about one billion synapses. Thalamic inputs to the cortex carry information that is transformed by local microcircuits of excitatory and inhibitory neurons. In recent years there has been an explosion of discoveries about the anatomical organization of the micrcircuits and the physiolgical properties of the neurons and synapses that compose them. The goal of this workshop is to explore the funcitonal implications of these new findings and in particualr to attempt to characterize the elementary computational operations that are performed in different layers of cortex. Some of the issues that speakers will address include: - How is the input from the thalamus able to dominate the cortex when the vast majority of the synapses in cortex are from cortical neurons and the thalamic inputs constitute less than 5% of the synapses on the first layer of cells in layer 4. - Is there a canonical microcircuit? How does it differ between sensory areas and motor areas, between the early and late stages in the cortical hierarchy, and in cortical areas that support working memory? - How is the gain of the microcircuit affected by top down inputs from higher cortical areas through attentional control? How are microcircuit with positive feedback stabilized? - What do the intrinsic properties of dendrites contribute to the computation performed by neurons? - What is the relation between proposed operations for canonical microcircuits such as gain control, normalization, tuning, soft-max? Can one compare the ventral stream to the dorsal stream? - What is the consequence of short-term synaptic plasticity on transient and tonic cortical processing? Workshop Format: There will be a series of 8 brief 20 minute talks with 20 minutes of discussion following each talk. Speakers: Rodney Douglas, (INI, Zurich) - Canonical cortical microcircuit Paul Tiesinga (UNC, Chapel Hill) - Microcircuits for gain control Attila Losonczy (Janelia Farm) - Dendritic computation Terry Sejnowski (Salk/UCSD) - Thalamocoritical inputs to cortex Tomaso Poggio (MIT) - Functions of microcircuits Bernie Widrow (Stanford) - Mechanisms for cognitive memory Sebastian Seung (MIT) - Connectomics David Heeger (NYU) - Microcircuits for normalization ----- From david.c.sterratt at ed.ac.uk Tue Oct 7 08:26:34 2008 From: david.c.sterratt at ed.ac.uk (David Sterratt) Date: Tue, 07 Oct 2008 13:26:34 +0100 Subject: Connectionists: Call for participation in a workshop on Computational Developmental Neuroscience in Edinburgh Message-ID: <1223382394.16315.28.camel@canongate.inf.ed.ac.uk> An embedded and charset-unspecified text was scrubbed... Name: not available Url: https://mailman.srv.cs.cmu.edu/mailman/private/connectionists/attachments/20081007/6c318a95/attachment.ksh From g.goodhill at uq.edu.au Tue Oct 7 21:42:43 2008 From: g.goodhill at uq.edu.au (Geoffrey Goodhill) Date: Wed, 8 Oct 2008 11:42:43 +1000 Subject: Connectionists: Faculty position available Message-ID: FACULTY APPOINTMENT IN COMPUTATIONAL NEUROSCIENCE at the Queensland Brain Institute, University of Queensland, Australia QBI (www.qbi.uq.edu.au) seeks a creative, accomplished Group Leader with an internationally recognized research program in the computational analysis of the nervous system. The appointment is for 5 years initially, with renewal beyond that dependent on performance. Applicants should hold a Ph.D. degree and have postdoctoral experience. Applications from more senior candidates will also be considered. The level of appointment will be commensurate with the candidate?s level of experience, and a competitive start-up package will be provided. QBI is focused on the following 7 main research themes, all of which will be expanded in terms of infrastructure and research capacity over the next five years: Computational Neuroscience, Cognitive and Behavioural Neuroscience, Synaptic Plasticity, Visual and Sensory Neuroscience , Mental and Neurological Disorders, Neurogenesis, and Axonal Guidance. The Institute is housed in a $63 million facility fitted with state-of-the-art research equipment. The Institute currently accommodates some 250 scientists, students and support staff. QBI has access to a range of world-class technologies, including a16.4T small animal MRI and a 3T human research MRI. It also has extensive capabilities in animal and human behavioural testing, and has developed strong interdisciplinary teams in the area of applying nanotechnology to neuroscience. The University of Queensland has a student population of over 35,000 and also has strong programs in Mathematics, Physics, Computer Science and Engineering. QBI is developing a collaborative network in the Asia-Pacific region and has recently signed affiliation agreements with leading neuroscience institutes in Japan and China. To apply please send a cover letter, a CV, a three-page statement of research interests, and arrange to have 3 letters of recommendation sent to the Search Committee. Applications should be sent either by email to h.weir at uq.edu.au, or by regular mail to Ms Helen Weir, Queensland Brain Institute, The University of Queensland, St Lucia, QLD 4072, Australia. Applications should be received by November 10th to assure full consideration. Informal enquiries are welcome, and should be directed to me: Geoffrey J Goodhill, PhD Associate Professor Queensland Brain Institute & School of Physical Sciences University of Queensland St Lucia, QLD 4072, Australia Phone: +61 7 3346 6431 Fax: +61 7 3346 6301 Email: g.goodhill at uq.edu.au http://www.uq.edu.au/qbi/index.html?page=26835 Editor-in-Chief, Network: Computation in Neural Systems http://www.informaworld.com/smpp/title~content=t713663148~db=all From ica2009 at dmo.fee.unicamp.br Wed Oct 8 18:05:52 2008 From: ica2009 at dmo.fee.unicamp.br (ICA2009) Date: Wed, 8 Oct 2008 19:05:52 -0300 (BRT) Subject: Connectionists: CFP - DEADLINE EXTENSION - ICA2009 Message-ID: Dear member of the connectionists list, The submission deadline of the ICA2009 conference has been extended. Please find below the new call for papers, which is also available in the conference website: http://www.dspcom.fee.unicamp.br/ica2009 Best regards, Allan Kardec Barros and Joao Marcos T. Romano. General Chairs, ICA2009 Tulay Adali and Christian Jutten Technical Chairs, ICA2009 ----------------------------------- 8th International Conference on Independent Component Analysis and Signal Separation Paraty, Brazil 15-18 March 2009 http://www.dspcom.fee.unicamp.br/ica2009 The 8th International Conference on Independent Component Analysis and Signal Separation, ICA 2009, will be held in Paraty, Brazil, March 15-18, 2009. The meeting will feature keynote addresses by leading researchers, as well as invited and contributed papers. Prospective authors are invited to submit papers in the following areas (but not limited to): * Algorithms and Architectures: non-linear ICA, probabilistic models, sparse coding, linear & nonlinear models, convolutive & noisy models; * Theory: optimization, complex methods, time-frequency representations; * Applications: audio, bio-informatics, biomedical engineering, communications, finance, text, image processing, psychology; * Emerging Technologies: analogue and digital VLSI implementations, photonics; * Functional Neuroimaging: EEG, MEG, fMRI analysis, applications in neuroscience; * Speech and Musical Audio: source separation, denoising, dereverberation, temporal models, computational auditory scene analysis (CASA), beamforming; * Visual and Sensory Processing: image processing and coding, image separation. SPECIAL SESSION ON EVALUATION ICA 2009 will feature a special session on the first community-based Signal Separation Evaluation Campaign (http://sisec.wiki.irisa.fr/). Researchers entering the campaign are encouraged to submit a paper to this session describing their approach. Papers discussing new algorithms or application strategies for existing algorithms (e.g. signal representation, parameter settings) are both welcome. Accepted papers will be published in the proceedings of ICA 2009, after review by the evaluation chairs and the program chairs. ADDITIONAL INFORMATION Proceedings will be published in Springer-Verlag's Lecture Notes in Computer Science Series (LNCS). LNCS is published, in parallel to the printed books, in full-text electronic form. All contributions must be original, and must not have been previously published, nor be under review for presentation elsewhere. Extended versions of a selection of papers presented at the conference will be considered for a special issue of a journal to appear in 2009. Detailed instructions for submission to ICA 2009 and further information will be available in the conference website. IMPORTANT DATES: * November 10, 2008 - Submission deadline * December 8, 2008 - Notification of acceptance * December 19, 2008 - Final paper due From cardoso at bcos.uni-freiburg.de Wed Oct 15 10:02:47 2008 From: cardoso at bcos.uni-freiburg.de (Simone Cardoso de Oliveira) Date: Wed, 15 Oct 2008 16:02:47 +0200 Subject: Connectionists: First Announcement Bernstein Award 2009 Message-ID: <48F5F807.9060203@bcos.uni-freiburg.de> Dear connectionists, the German Federal Ministry for Education and Research has announced a call for applications for the next Bernstein Award (to be awarded in 2009). Deadline for application is March 25, 2009. Since 2006 the German Federal Ministry of Education and Research (BMBF) annually awards excellent junior scientists with outstanding research ideas in the field of Computational Neuroscience. The ?Bernstein Award for Computational Neuroscience? is provided for a scientific project of a young research group headed by a postdoc regardless of nationality and is equipped with up to 1.25 Mio Euros in the form of a grant over a period of five years. Further information: http://www.gesundheitsforschung-bmbf.de/de/1834.php (in German) http://www.gesundheitsforschung-bmbf.de/en/1834.php (in English) Best regards, Simone Cardoso -- Dr. Simone Cardoso de Oliveira Bernstein Coordination Site of the National Network Computational Neuroscience Albert Ludwigs University Freiburg Hansastr. 9A 79104 Freiburg, Germany phone: +49-761-203-9583 fax: +49-761-203-9585 cardoso at bcos.uni-freiburg.de www.nncn.de From anderson at titan.cog.brown.edu Mon Oct 6 15:10:16 2008 From: anderson at titan.cog.brown.edu (Jim Anderson) Date: Mon, 6 Oct 2008 15:10:16 -0400 (EDT) Subject: Connectionists: Computational Modeling of Human Cognitive Systems Message-ID: COMPUTATIONAL MODELING, BROWN UNIVERSITY: The Department of Cognitive and Linguistic Sciences and the Department of Psychology invite applications for a tenure-track joint position as Assistant Professor in the computational modeling of human cognitive systems, beginning July 1, 2009. Applicants must have a strong computational or theoretical research program, modeling any aspect of human cognitive or language processing. Collaboration or experience in related experimental research is desirable. Candidates should also have a broad teaching ability in the cognitive sciences at both the undergraduate and graduate levels and an interest in contributing to interdisciplinary research and education. Brown has a highly interdisciplinary research environment in the study of mind, brain, behavior, and language, and is in the process of establishing an integrated Department of Cognitive, Linguistic, and Psychological Sciences. Plans to house the new department (together with the multi-departmental Institute for Brain Science) in a new building adjacent to the MRI Research Facility are well under way. Curriculum vitae, reprints and preprints of publications, one-page statements of research and teaching interests, and three letters of reference should be submitted by December 15, 2008. Applicants are encouraged to submit materials on-line at www.cog.brown.edu/jobs, or else by mail to Computational Search Committee, Dept. of Cognitive and Linguistic Sciences, Box 1978, Brown University, Providence, R.I. 02912 USA. All Ph.D. requirements must be completed before July 1, 2009. Women and minorities are especially encouraged to apply. Brown University is an Equal Opportunity/Affirmative Action Employer. From Eugene.Izhikevich at nsi.edu Thu Oct 9 12:34:12 2008 From: Eugene.Izhikevich at nsi.edu (Eugene M. Izhikevich) Date: Thu, 09 Oct 2008 09:34:12 -0700 Subject: Connectionists: Polychronization: MATLAB and C programs to explore polychronous dynamics Message-ID: <48EE3284.8070500@nsi.edu> MATLAB and C programs to analyze polychronous dynamics in spiking networks with conduction delays and STDP are available at http://www.nsi.edu/users/izhikevich/publications/spnet.htm The quickest way to start is to download polychron.m, polygroup.m, and 18000.mat into the same folder. Then, run polychron.m and enjoy the show. See Izhikevich (2006) for more details http://www.nsi.edu/users/izhikevich/publications/spnet.pdf -- Eugene M. Izhikevich, Senior Fellow in Theoretical Neurobiology PhD, Mathematics, http://www.nsi.edu/users/izhikevich The Neurosciences Institute, Editor-in-Chief at scholarpedia.org 10640 John J. Hopkins Drive tel:(858) 626-2063 San Diego, CA, 92121, USA fax:(858) 626-2099 From esann at dice.ucl.ac.be Sun Oct 12 09:57:15 2008 From: esann at dice.ucl.ac.be (esann@dice.ucl.ac.be) Date: Sun, 12 Oct 2008 15:57:15 +0200 Subject: Connectionists: ESANN'2009 special sessions: CFP Message-ID: <7CFF78B2880F48ADA40C67C0B762B2CC@maxwell.local> ESANN'2009 17th European Symposium on Artificial Neural Networks Advances in Computational Intelligence and Learning Bruges (Belgium) - April 22-23-24, 2009 Special sessions ============================================= The following message contains a summary of all special sessions that will be organized during the ESANN'2009 conference. Authors are invited to submit their contributions to one of these sessions or to a regular session, according to the guidelines found on the web pages of the conference http://www.dice.ucl.ac.be/esann/. Deadline for submissions: November 21, 2008. According to our policy to limit the number of unsolicited e-mails, we gathered all special session descriptions in a single message, and try to avoid sending it to overlapping distribution lists. We apologize if you receive multiple copies of this e-mail despite our precautions. Special sessions that will be organized during the ESANN'2009 conference ========================================================= 1. Semi-supervised learning Ant?nio de P?dua Braga (Federal Univ. Minas Gerais, Brazil) 2. Learning (with) Preferences Fabio Aiolli, Alessandro Sperduti (Univ. degli Studi di Padova, Italy) 3. Brain Computer Interfaces: from theory to practice Luc Boullart (Ghent University), Patrick Santens (Ghent University Hospital), George Otte (Dr. Guislain Institute), Bart Wyns (Ghent University, Belgium) 4. Efficient learning in recurrent networks Benjamin Schrauwen (Ghent University, Belgium), Jochen J. Steil (Bielefeld University, Germany), Barbara Hammer (Clausthal University of Technology, Germany) 5. Weightless Neural Systems Massimo De Gregorio (Istituto di Cibernetica-CNR, Italy), Priscila M. V. Lima, Felipe M. G. Fran?a (Universidade Federal do Rio de Janeiro, Brazil) 6. Neural Maps and Learning Vector Quantization - Theory and Applications Thomas Villmann, Frank-Michael Schleif (Univ. Leipzig, Germany) Short descriptions ================== 1. Semi-supervised learning ----------------------------------------------------------------------- Organized by: Ant?nio de P?dua Braga (Federal Univ. Minas Gerais, Brazil) Semi-Supervised learning falls in-between the Supervised and Unsupervised Learning paradigms, by considering both labeled and unlabeled data for training. From the Supervised Learning perspective, structural information, particularly related to the separation margin, is usually added to the Optimization problem resulted from the labeled data. From the Unsupervised Learning perspective, Semi-Supervised Clustering is accomplished by considering the labeled data as constraints to the clustering task. Despite of having different goals, the basic elements of training in both perspectives are the labels plus structural information obtained from the unlabeled data set. In this special session, we seek for contributions from both perspectives above, not limited to Artificial Neural Networks design. Topics of interest include (but are not limited to): - Semi-supervised learning - Semi-supervised clustering - Transductive learning - Co-training - Partial supervision 2. Learning (with) Preferences ----------------------------------------------------------------------- Organized by: Fabio Aiolli, Alessandro Sperduti (Univ. degli Studi di Padova, Italy) Preferences give a declarative way for specifying desires and are very important in many applications which include reccomender systems for e-commerce and social networks, ranking systems for information retrieval, and player modelling for games. In all these contexts, people find easier to indicate which objects they prefer to which other with respect to make absolute judgments about the relevance they give to each of them. Recently, preference learning models and preference based predictions have gained popularity in the machine learning and knowledge discovery communities. Many supervised learning tasks can in fact be modeled as sets of preferences over a parameterized relevance function. This kind of preferences are given in the form of partial or full orders over the relevance function. Preferences can be given between objects (instance rankings) and/or between classes (label rankings). Other interesting topics concern how to mine or elicitate preferences from user behaviours and how to aggregate preferences obtained from multiple sources. We invite papers on learning preferences and/or learning with preferences. In particular topics of interest include, but are not limited to: - theory about any aspect of preference learning - preference based models to cope with structured (complex) predictions - preference mining and preference elicitation - preference/ranking aggregation - semi-supervised preference learning - scalability and efficiency of preference based learning algorithms - evaluation measures for preference learning - applications of preference learning: information retrieval, e-commerce, games, ecc. Submitted papers will be reviewed according to the ESANN reviewing process and will be evaluated on their scientific significance, originality, correctness, and writing style. 3. Brain Computer Interfaces: from theory to practice ----------------------------------------------------------------------- Organized by: Luc Boullart (Ghent University), Patrick Santens (Ghent University Hospital), George Otte (Dr. Guislain Institute), Bart Wyns (Ghent University, Belgium) Brain-Computer Interfaces (BCI) are a new kind of human-machine interfaces and represents a burgeoning field of research. Brain signals are measured using EEG and translated directly into control commands. A typical application of BCI is found in people with severe motor disabilities allowing them to manipulate their environment in an alternative way. However there?s still a lot of work to be done to make it usable in daily life. This special session aims at presenting novel ideas of brain signal analysis, artefact removal algorithms (for example blind source separation), feature selection strategies and BCI classification algorithms or interesting applications of BCI for robot control. Keywords: (brain) signal processing and modelling, brain-computer interfaces, intelligent ?brain? controlled computers, EEG signal analysis 4. Efficient learning in recurrent networks ----------------------------------------------------------------------- Organized by: Benjamin Schrauwen (Ghent University, Belgium), Jochen J. Steil (Bielefeld University, Germany), Barbara Hammer (Clausthal University of Technology, Germany) Recurrent neural networks carry the promise of efficient biologically plausible signal processing models optimally suited for a wide area of applications, especially when dealing with spatio-temporal data or causalities. On the other hand, they can form the basis for an explanation for neurophysiological processes and cognitive phenomena of the human brain. Recently, a number of fundamental paradigms connected to RNNs have been developed which allow new insights into potential supervised and unsupervised information processing with RNNs and open the way to new efficient training algorithms which overcome the well-known problems of long-term dependencies. The aim of the session is to further the understanding and development of efficient, biologically plausible recurrent information processing, both in theory and in applications. Submissions are encouraged within the following non-exhaustive list of keywords: - reservoir computing: echo state machine, liquid state machine - recurrent SOM - LSTM - unsupervised and semi-supervised adaptation of RNNs - evolutionary models for RNNs - connection of RNNs and brain phenomena - connection of RNNs and symbolic reasoning - theory of RNN dynamics, learning, and generalization - applications 5. Weightless Neural Systems ----------------------------------------------------------------------- Organized by: Massimo De Gregorio (Istituto di Cibernetica-CNR, Italy), Priscila M. V. Lima, Felipe M. G. Fran?a (Universidade Federal do Rio de Janeiro, Brazil) Mimicking biological neurons by focusing on the decoding performed by the dendritic trees is a different and attractive alternative to the integrate-and-fire McCullogh-Pitts neuron stylisation. RAM-based or Boolean neurons and systems have been studied and applied in a wide spectrum of situations. This session invites original contributions on theoretical and practical aspects of weightless neural systems, at all levels of abstraction (pattern recognition, consciousness, artificial emotions, reasoning etc). 6. Neural Maps and Learning Vector Quantization - Theory and Applications ----------------------------------------------------------------------- Organized by: Thomas Villmann, Frank-Michael Schleif (Univ. Leipzig, Germany) Neural maps and learning vector quantization constitute important neural paradigms in unsupervised and supervised vector quantization. Prominent methods are the self-organizing map (SOM), neural gas (NG) and the family of LVQ-algorithms or generalizations thereof. Although most of the approaches are well-known, there are still open theroretical questions like magnification for Heskes-SOM or non-euclidean NG, the dynamics of LVQ, to name just a few. Recent investigations and extensions are in the field of non-standard metrics, structured data processing, time series, batch and patch-variants etc. All these interesting new developments lead to a broader range of applications of the algorithms compared to their standard variants. The proposed session invite researchers to submit contribution about new approaches, extensions and modifications as well as ideas in this outlined direction. Thereby, new theoretical investigations as well as outstanding applications demonstrating the abilities of new extensions/modifications of the standard algorithm are in the focus. For the latter aspect a strong connection between the specific aspects of SOM/NG/LVQ to the application should be explicitely given and highlighted. Submissions are encouraged within the following non-exhaustive list of topics: - theory of SOM/NG/LVQ and variants thereof - magnification and magnification control - non-standard metrics - new extensions of existing approaches - semi-supervised learning - fuzzy methods for neural maps - statistical interpretations - learning theory - outstanding applications ======================================================== ESANN - European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning http://www.dice.ucl.ac.be/esann * For submissions of papers, reviews, registrations: Michel Verleysen Univ. Cath. de Louvain - Machine Learning Group 3, pl. du Levant - B-1348 Louvain-la-Neuve - Belgium tel: +32 10 47 25 51 - fax: + 32 10 47 25 98 mailto:esann at uclouvain.be * Conference secretariat d-side conference services 24 av. L. Mommaerts - B-1140 Evere - Belgium tel: + 32 2 730 06 11 - fax: + 32 2 730 06 00 mailto:esann at uclouvain.be ======================================================== From dominik.janzing at tuebingen.mpg.de Thu Oct 16 02:41:26 2008 From: dominik.janzing at tuebingen.mpg.de (Dominik Janzing) Date: Thu, 16 Oct 2008 08:41:26 +0200 Subject: Connectionists: CFP NIPS 2008 workshop causality Message-ID: Dear member of the connectionists list, We would like to announce the NIPS 2008 Workshop on Causality Friday December 12, 2008 Whistler Resort & Spa and Westin Hilton, BC, CANADA Organizers: Isabelle Guyon, Dominik Janzing, Bernhard Schoelkopf CALL FOR PAPERS The goal of this workshop is to discuss new approaches to causal discovery from empirical data, their applications and methods to evaluate their success. Emphasis will be put on the definition of objectives to be attained and on assessment methods to evaluate proposed solutions. The participants are encouraged to participate to a "competition pot-luck" in which datasets and problems are exchanged and solutions proposed. Full 6-page papers should be submitted by ** November 21, 2008 ** to causality at clopinet.com. Accepted papers will be published in the proceedings of JMLR and as an edited book. See http://clopinet.com/isabelle/Projects/NIPS2008/ for a list of topics and formatting instructions. **VIRTUAL CONTRIBUTIONS** Submission of a paper on the topics of the workshop is not conditioned on participating in the competition nor being physically present at the workshop. All authors of selected papers will be requested to submit before the conference a set of slides or a poster in PDF format, which will be made available on the web site of the workshop. Speakers not present at the workshop will be invited to present their work in a recorded audio teleconference following the workshop. Best Regards, Dominik Janzing From olivier.buffet at loria.fr Fri Oct 10 03:42:43 2008 From: olivier.buffet at loria.fr (Olivier Buffet) Date: Fri, 10 Oct 2008 09:42:43 +0200 Subject: Connectionists: PhD position on active sensing, POMDPs Message-ID: <48EF0773.5010500@loria.fr> PhD position on active sensing, POMDPs at INRIA (Nancy, France): Title: Optimal Control of Active Sensors Summary: One of the main objectives of artificial intelligence is to make artificial agents capable of suggesting optimal decisions to a human - or even to act in completely autonomous manner ? by reasoning about the effects of the sequence of actions it envisions. The POMDP formalism [1,2] (Partially Observable Markov Decision Processes) allows in particular to model settings where an agent is in an environment whose evolution is uncertain, and whose perception is limited. This PhD position will focus more precisely on information gathering problems involving active sensors [3], the decisions being made so as to acquire observations bringing the most complementary pieces of information about a given situation. The candidate will first look for algorithms which are efficient despite the large size of the search space (size linked to the uncertainty inherent to the problem), then he will extend these approaches to the joint use of multiple -more or less independent- active sensors. This work will be applied -in the context of an industrial project- to the low cost identification of defaults in aeronautics parts made of composite materials by selecting the observations to perform (which sensor, where, at which resolution). But case studies will also cover classical problems such as searching for a mobile intruder in a complex environment. Bibliographic references: [1] D.P. Bertsekas and J.N. Tsitsiklis. Neurodynamic Programming. Athena Scientific, 1996. [2] Kevin Murphy. A Survey of POMDP Solution Techniques. Technical report, Department of Computer Science, University of California, 2000. [3] Matthijs T. J. Spaan. Cooperative Active Perception using POMDPs. In Proceedings of the AAAI 2008 Workshop on Advancements in POMDP Solvers, July 2008. Required skills and background: Partially observable Markov devision processes (POMDP) are at the heart of this PhD position. The candidate will have to be familiar with this field or related fields (algorithmic, operations research, probabilities). Software development will be conducted in Java or C++. Applicants are required to hold a Master's degree in ComputerScience / Applied Maths (or an equivalent diploma). Contact (phone and e-mail) : Vincent Thomas 03 54 95 85 08 vincent.thomas at loria.fr Fran?ois Charpillet 03 83 59 20 81 francois.charpillet at loria.fr Olivier Buffet 03 54 95 85 02 olivier.buffet at loria.fr APPLICATION PROCESS To apply, please send the following documents to olivier.buffet at loria.fr before 31/10/2008: - detailed CV - motivation letter - references (master's supervisor) - master's thesis - possibly recent transcripts of records About INRIA PhD opportunities: http://www.inria.fr/travailler/opportunites/doc.en.html From pascal.fua at epfl.ch Thu Oct 9 03:21:14 2008 From: pascal.fua at epfl.ch (Pascal Fua) Date: Thu, 09 Oct 2008 09:21:14 +0200 Subject: Connectionists: Open Faculty Positions at EPFL Message-ID: <48EDB0EA.3080405@epfl.ch> The School of Computer and Communication Sciences at EPFL invites applications for faculty positions in computer science. We are primarily seeking candidates for tenure-track assistant professor positions, but suitably qualified candidates for senior positions will also be considered. Successful candidates will develop an independent and creative research program, participate in both undergraduate and graduate teaching, and supervise PhD students. Candidates from all areas of computer science will be considered, but preference will be given to candidates with interests in algorithms, bioinformatics, graphics, machine learning, and design methodologies for integrated systems. Significant start-up resources and research infrastructure will be available. Internationally competitive salaries and benefits are offered. To apply, please follow the application procedure at http://icrecruiting.epfl.ch. The following documents are requested in PDF format: curriculum vitae, including publication list, brief statements of research and teaching interests, names and addresses (including e-mail) of 3 references for junior positions, and 6 for senior positions. Screening will start on January 1, 2009. Further questions can be addressed to : Professor Willy Zwaenepoel Dean School of Computer and Communication Sciences EPFL CH-1015 Lausanne, Switzerland recruiting.ic at epfl.ch For additional information on EPFL, please consult: http://www.epfl.ch or http://ic.epfl.ch From aude.billard at epfl.ch Mon Oct 13 11:35:00 2008 From: aude.billard at epfl.ch (Aude Billard) Date: Mon, 13 Oct 2008 17:35:00 +0200 Subject: Connectionists: Postdoctoral researcher in the field of computer vision and machine learning Message-ID: <03fa01c92d49$4106b170$1d53b280@lasalap0> Postdoctoral researcher in the field of computer vision and machine learning The Learning Algorithm and Systems Laboratory at the EPFL (Swiss Federal Institute of Technology, Lausanne) seeks immediately one qualified postdoctoral researcher in the field of computer vision and machine learning. The postdoc will work in the framework of the IM2 and TACT projects, that develop algorithms for multimodal analysis of video and audio data recorded by the WearCam, a wearable hat designed for children with disabilities, see http://lasa.epfl.ch/research/toys/wearcam/index.php The successful candidate will have a PhD and experience in at least 1 of the following fields: - computer vision or image processing - machine learning, pattern recognition or statistical techniques In addition, the candidate should have a strong background in C++ programming and matlab. The applicant should be fluent in English. The initial Postdoctoral position is for one year, with a possibility of 1 year extension. The position is open immediately. Application: Interested candidates should send a letter of motivation, along with their detailed CV, electronic transcripts of B.S. and M.S. degrees and names of 3 references to Prof. Aude Billard (aude.billard at epfl.ch.) ----------------------------- References: - website LASA: http://lasa.epfl.ch - website WearCam Project: http://lasa.epfl.ch/research/toys/wearcam/index.php -------------- next part -------------- An HTML attachment was scrubbed... URL: https://mailman.srv.cs.cmu.edu/mailman/private/connectionists/attachments/20081013/167a8a6c/attachment.html From wjma at cpu.bcm.edu Wed Oct 22 15:32:07 2008 From: wjma at cpu.bcm.edu (Wei Ji Ma) Date: Wed, 22 Oct 2008 14:32:07 -0500 Subject: Connectionists: PhD Program in Neuroscience at Baylor College of Medicine Message-ID: <48071F74CBAD5B46973B3D2B90179BCBEC3B@stan.hou-ad.hnl.bcm.tmc.edu> The following announcement may be of particular interests to students of math, physics, computer science, engineering, and related disciplines. PhD Program in Neuroscience at Baylor College of Medicine, Houston, TX Neuroscientists increasingly recognize that theory and computational approaches are essential to understanding how the human brain works. Baylor College of Medicine is at the forefront of this development, with a core group of researchers working to incorporate theoretical and quantitative methods into studies of cognition in health and psychiatric disease. The Graduate Program in Neuroscience offers students with a strong quantitative and analytical background the opportunity to apply their skills to challenging problems in cognition research, while receiving world-class training across the breadth of neuroscience. Physics, mathematics, computer science, and engineering are not traditionally associated with investigating human cognition. Yet students from these and related disciplines often possess the skills and mindset that are necessary to create theoretical frameworks for experimental data. In the Department of Neuroscience at BCM, this can take on many forms, such as advanced analysis of neuroimaging data, investigating the neural mechanisms of time perception, modeling anomalies of reward processing in psychiatric patients, studying the dynamics of decision-making in groups, or developing probabilistic theories of human perception. Each of the computationally oriented neuroscience laboratories at BCM also conducts human behavioral or neuroimaging studies, thereby allowing for a direct and fruitful interplay between theory and experiment. This is aided by state-of-the-art imaging and computing facilities, as well as active collaborations with neurophysiological laboratories and clinical divisions. Students of this new approach will acquire the tools and training that will position them uniquely for groundbreaking interdisciplinary research after the completion of their program, as well as for many other career paths. The graduate program leading to a Ph.D. in neuroscience is designed as a five-year program. In the first year, students complete a series of courses that provide them with a strong background in all facets of neuroscience. Concurrently, they familiarize themselves with ongoing research through 3 to 5 rotations in the laboratories of Neuroscience faculty of their choice. At the end of the first year, students choose an advisor, enter into the lab full-time, and develop suitable thesis research projects. For more information about the neuroscience laboratories at BCM with a theoretical/computational focus, please visit the website of the Computational Psychiatry Unit at http://cpu.bcm.edu/labs.html. For more information about the Graduate Program, visit http://neuro.bcm.edu/think or contact Dr. Mariella De Biasi, Director of Graduate Studies, at debiasi at bcm.edu. P.S. There is no application fee and our Program offers free tuition and a very competitive stipend! -------------- next part -------------- An HTML attachment was scrubbed... URL: https://mailman.srv.cs.cmu.edu/mailman/private/connectionists/attachments/20081022/7dfb7dd9/attachment.html From mcclelland at stanford.edu Sun Oct 26 15:58:56 2008 From: mcclelland at stanford.edu (Jay McClelland) Date: Sun, 26 Oct 2008 12:58:56 -0700 Subject: Connectionists: Graduate Training in Mind, Brain, and Computation at Stanford Message-ID: <4904CC00.2020303@stanford.edu> Graduate Training in Mind, Brain, and Computation at Stanford The Center for Mind, Brain and Computation (MBC) at Stanford University announces its new Graduate Training Program. The program is supported by an NSF IGERT graduate training grant. The goal of the Center is to encourage research on the emergent functions of the brain, exploiting a synergistic combination of experimental and computational methods. Topics of investigation include plasticity, learning, and memory; decision making; vision, attention, and reading; executive function and motor control; cortical microcircuit function and dysfunction, and many others. Faculty affiliated with the program (see list below) work at all levels of analysis of brain function, using a range of computational, statistical, mathematical, and experimental methods. The graduate training program is designed to enhance the training of students in participating Ph.D. Programs at Stanford who wish to make integrated use of computational/mathematical and experimental approaches in research related to the themes of the Center. The program is affiliated with the Ph.D. programs in Computer Science, Electrical Engineering, Neuroscience, and Psychology. Students in any of these programs are eligible to become affiliates of the MBC program; affiliates may become trainees after developing a specialized training program in consultation with MBC faculty. These training programs are intended to allow the trainee to stretch beyond the coursework and research training they would ordinarily receive in their home discipline, under the joint supervision of a primary and secondary mentor. The secondary mentor should represent an approach or discipline that complements that of the primary mentor in ways relevant to the trainees goals. Trainees who are US nationals may be considered for support from the NSF IGERT Grant. If you are not yet a Ph.D. student at Stanford, and are interested in MBC, you should apply to one or more of the affiliated Ph.D. programs. Concurrently, you may apply for MBC affiliate status by requesting the application form from the MBC program administrator, lehope at stanford.edu. If you are already a Ph.D. student at Stanford and would like to join the program, you may contact the program administrator at any time to begin the process. For more information or to contact MBC, visit http://www.stanford.edu/group/mbc For information about each allied Ph.D. program, replace xx in xx.stanford.edu with cs, ee, neuroscience, or psychology. MBC Program Director: Jay McClelland, Psychology Co-Director: Krishna Shenoy, Electrical Engineering Steering Committee: John Huguenard, Neurology Daphne Koller, Computer Science William Newsome, Neurobiology Andrew Ng, Computer Science Terry Sanger, Neurology Brian Wandell, Psychology Other Training Faculty: Stephen Baccus, Neurobiology Kwabena Boahen, Bioengineering Lera Boroditsky, Psychology Karl Deisseroth, Bioengineering and Psychiatry Scott Delp, Mechanical Engineering Gary Glover, Radiology Kalanit Grill-Spector, Psychology Trevor Hastie, Statistics Eric Knudsen, Neurobiology Brian Knutson, Psychology Robert Malenka, Psychiatry Samuel McClure, Psychology Vinod Menon, Psychiatry Teresa Meng, EE & CS Tirin Moore, Neurobiology Josef Parvizi, Neurology Jennifer Raymond, Neurobiology Mark Schnitzer, Biological Sciences Carla Shatz, Biological Sciences and Neurobiology Stephen Smith, Molecular & Cellular Physiology Richard Tsien, Molecular & Cellular Physiology Sebastian Thrun, CS & EE Anthony Wagner, Psychology Bernard Widrow, Electrical Engineering From Dave_Touretzky at cs.cmu.edu Fri Oct 24 05:58:28 2008 From: Dave_Touretzky at cs.cmu.edu (Dave_Touretzky@cs.cmu.edu) Date: Fri, 24 Oct 2008 05:58:28 -0400 Subject: Connectionists: PhD program in Neural Computation Message-ID: <5319.1224842308@ammon.boltz.cs.cmu.edu> The Ph.D. Program in Neural Computation (PNC) at Carnegie Mellon University and the University of Pittsburgh is now accepting applications. Carnegie Mellon University, in collaboration with the University of Pittsburgh, recently created a new Ph.D. program in computational neuroscience called the Program in Neural Computation (PNC). This program, which is in its third year, is seeking qualified applicants to begin their graduate training in the Fall of 2009. The PNC is supported in part by an NIH training grant, and emerged as an outgrowth of the highly successful certificate program that has been administered by the CNBC for about the last ten years. Students in the program can train with a wide array of faculty from both Carnegie-Mellon and the University of PIttsburgh. The PNC seeks to attract students with strong quantitative backgrounds who are interested in graduate work in the area of computational neuroscience, and for whom other graduate programs are often not the best fit. Details about program curriculum, training faculty and contact information are available at: http://www.cnbc.cmu.edu/pnc The online application is available at: https://applyweb.cs.cmu.edu/apply/index.php?domain=11 The deadline for applications is January 1, 2009. For further information, contact: Nathan Urban, Ph.D. Associate Professor Department of Biological Sciences and Center for the Neural Basis of Cognition Carnegie Mellon University 4400 Fifth Ave Pittsburgh PA 15213 ph. 412-268-5122 fax 412-268-8423 http://www.andrew.cmu.edu/user/nurban/Lab_pages/ From mcclelland at stanford.edu Sun Oct 26 16:23:12 2008 From: mcclelland at stanford.edu (Jay McClelland) Date: Sun, 26 Oct 2008 13:23:12 -0700 Subject: Connectionists: Cognitive Faculty Position at Stanford: Computational Applicants Sought Message-ID: <4904D1B0.5080808@stanford.edu> STANFORD UNIVERSITY PSYCHOLOGY DEPARTMENT plans to make a tenure-track appointment in Cognitive Psychology to begin in the 2009-10 academic year. Rank is open. Applicants using computational/mathematical models and/or cognitive neuroscience approaches are encouraged. All areas will be considered, including memory, thinking, language, perception, and decision making. The appointee will be expected to teach courses at both the graduate and undergraduate levels. Applicants should apply through AcademicJobsOnline.org by December 1, 2008. Applications should include a curriculum vitae (including bibliography), a brief statement of research and teaching interests, and copies of representative scholarly papers. Assistant Professor candidates should also arrange for three letters of reference. Stanford University is an equal opportunity employer and is committed to increasing the diversity of its faculty. It welcomes nominations of, and applications from, women and minority groups, as well as others who would bring additional dimensions to the university's research and teaching missions. From jeedward at yahoo.com Sat Oct 18 10:18:14 2008 From: jeedward at yahoo.com (Ed) Date: Sat, 18 Oct 2008 07:18:14 -0700 (PDT) Subject: Connectionists: Special track on neural computation at IICAI-09 Message-ID: <206329.29965.qm@web45902.mail.sp1.yahoo.com> A special track on neural computation will be organized at the 4th Indian International Conference on Artificial Intelligence (IICAI-09). The goal of this session is to enhance interactions between the people working in the area of neural computation ?with other relevant areas such as computerscience, bioinformaticians, cognitive science, etc. The conference and the track will be held in Tumkur (near Bangalore), India during December 16-18 2009. The conference consists of paper presentations, special workshops, sessions, invited talks and local tours, etc.? and it is one of the biggest AI events in the world. We invite draft paper submissions. Please see the website: www.iiconference.org ?for more details of the conference. ? Edward Publicity Committee __________________________________________________ Do You Yahoo!? Tired of spam? Yahoo! Mail has the best spam protection around http://mail.yahoo.com -------------- next part -------------- An HTML attachment was scrubbed... URL: https://mailman.srv.cs.cmu.edu/mailman/private/connectionists/attachments/20081018/d30d8f9b/attachment-0001.html From kenji at ieee.org Sun Oct 19 18:59:57 2008 From: kenji at ieee.org (Kenji Suzuki) Date: Mon, 20 Oct 2008 07:59:57 +0900 Subject: Connectionists: Postdoctoral Positions in Cybernics (up to three positions) Message-ID: <48FBBBED.2020805@ieee.org> * We apologize if you receive multiple copies of this announcement. Job announcement Postdoctoral Positions in Cybernics (up to three positions) Cybernics Program, University of Tsukuba, Japan Ref: CYB04/P0810 http://www.cybernics.tsukuba.ac.jp/ Review of applications: from 1 November, 2008 Applications are invited for three (3) postdoctoral positions in the area of Cybernics: fusion of human, machine and information systems, or relevant subjects. Cybernics is a new domain of interdisciplinary academic field of human-assistive technology to enhance, strengthen, and support human cognitive and physical functions, which challenges to integrate and harmonize humans and robots (RT: robotics technology) with the basis of information technology (IT). We provide a stimulating environment for enthusiastic and creative postdocs, and the research teams allows them to pursue research in close collaboration with School of Medicine, Philosophy and Laws. The topics including - but not limited to - Robot suits (exoskeleton) - Assistive and Rehabilitation robotics - Humanoid robotics - Physical and cognitive human-robot interaction - Vital data sensing, Medical interface and Medical robotics - Brain-machine interface - Other fields in Cybernics (see the faculty members) These positions are for duration of three years, and will be available immediately. The review of applications will proceed after November 1st 2008 on their arrival and will continue until the position is filled. The Cybernics program (Leader, Prof. Yoshiyuki Sankai) is supported by the grant-in-aid science research under the Global COE program, and also is a strategic initiative of the University of Tsukuba. For more details on research areas, see the program website. Candidates are expected to have earned a Ph.D. degree or equivalent in a relevant subject area and to have demonstrated achievement in their fields. Candidates recently graduated Ph.D., or expected to obtain their Ph.D. degrees or equivalent before the appointment begins are also encouraged to apply. Applications should include full curriculum vitae, a list of publications, 5 reprints or preprints of relevant papers, an outline of past researches, future research plans, and possible contribution to this project (about A4 2-pages), and the names and addresses of at least two referees. Applicants are requested, if possible, to list publications under the following main headings: Authored or Edited books, Refereed Journal papers, Review articles, Refereed conference proceedings, Non-refereed conference proceedings, Patents, Awards, External funding and grants, Others. Please return your application by email, preferably in PDF format, to jobs.pd at cybernics.tsukuba.ac.jp. You should include the ref. number you are applying for in the header of your e-mail, or standard mail envelope. For informal inquiries please contact the Leader of the Cybernics Program, Professor Yoshiyuki Sankai on email sankai at cybernics.tsukuba.ac.jp. Tsukuba is a university and science city, located about 60 kilometers, about 45 min by train northeast of central Tokyo. Over 50 national and independently administered research organizations are concentrated in the Tsukuba Science City district, which is centered on the university. Yoshiyuki Sankai Professor, Leader of Cybernics Program University of Tsukuba Review of applications: from 1 November, 2008 (will continue until the positions are filled.) * http://www.cybernics.tsukuba.ac.jp/jobs/CYB04P0810.html --- Kenji Suzuki kenji at ieee.org University of Tsukuba, Japan http://www.iit.tsukuba.ac.jp/~kenji/ From rjolivet at pharma.uzh.ch Wed Oct 22 04:07:56 2008 From: rjolivet at pharma.uzh.ch (Renaud Jolivet) Date: Wed, 22 Oct 2008 10:07:56 +0200 Subject: Connectionists: Fully funded 3 years PhD position at the University of Zurich Message-ID: <48FEDF5C.9020300@pharma.uzh.ch> Modeling neuron-astrocyte metabolic interactions and their impact on neural activity We are looking for a talented and motivated PhD student for a computational neuroscience project aimed at understanding the energetic constraints of neuronal activity. The brain uses glucose as its primary energy substrate. Surprisingly however, neurons can also use lactate ? a glucose derivative ? rather than glucose as their main energy fuel. Lactate is being produced in astrocytes from blood-borne glucose and is then shuttled to neurons instantiating a metabolic connection between astrocytes and neurons. Since this mechanism was originally postulated in 1994, its existence has been the subject of a much heated controversy. Our recent work using mathematical analysis suggests that this lactate shuttle does take place in vivo, is of significant importance and is regulated by the activity of excitatory neurons as originally postulated. This leaves open the question as to why brain energetic is organized in this fashion. This question is being addressed in the group at the moment using a combination of in vivo experiments and computational modeling. With this project, we wish to open a new line of research focusing on the role of this lactate shuttle in the regulation of neuronal activity, a mechanism recently described in vitro. The project will consist of developing, simulating and analyzing a network model containing different neuronal and astrocytic subpopulations. Energetic constraints and regulatory mechanisms will be integrated in the network by progressively increasing the complexity of astrocyte?neuron metabolic interactions. Combining modeling with experiments is possible if the candidate wishes to do so. Requirements ? Strong theoretical background (mathematics, physics or equivalent). ? Knowledge of the Python programming language and MATLAB an asset. ? Basic knowledge of biology and neuroscience. ? Interested in combining theoretical tools with in vivo experiments to address key questions in neuroscience. ? Fluent in English. Contact ? Please contact Renaud Jolivet by e-mail at rjolivet at pharma.uzh.ch. ? Further information about the group can be found at http://www.pharma.uzh.ch/research/functionalimaging.html ? University of Zurich website http://www.uzh.ch/index_en.html ? Neurosciences in Zurich http://www.neuroscience.ethz.ch/ ? Living in Zurich http://www.zuerich.com/en/welcome.cfm From luecke at fias.uni-frankfurt.de Thu Oct 23 13:32:25 2008 From: luecke at fias.uni-frankfurt.de (=?iso-8859-1?q?J=F6rg_L=FCcke?=) Date: Thu, 23 Oct 2008 19:32:25 +0200 Subject: Connectionists: Open PhD and Post-doc Positions at the New Computational Vision Center in Frankfurt Message-ID: <200810231932.25420.luecke@fias.uni-frankfurt.de> We offer a range of PhD and post-doc positions for theoretical and experimental work in the new 'Bernstein Focus Neurotechnology' in Frankfurt. Research in the center is part of the Bernstein Network of Computational Neuroscience funded by the German Federal Ministry of Education and Research (BMBF). The offered PhD and post-doc positions are fully funded research positions covering the the fields of: * computational neuroscience * computer vision * machine learning * visual robotics Our focus on Neurotechnology will combine basic research in these fields to develop an integrated and autonomously learning vision system. For information about the individual projects, see the project descriptions further below. We are looking for highly qualified post-graduate students and post-docs who have graduated in any of the subjects above or in related fields such as physics, mathematics, computer science, engineering, etc. In general, candidates are required to have a strong analytical background and good programming skills. Good communication skills in English (oral and written) are essential. Research is carried out in international groups located at the Frankfurt Institute for Advanced Studies (FIAS), the Computer Science Dept of the University of Frankfurt, the Honda Research Institute Europe, the Max Planck Institute for Brain Research, and other associated research centers. All collaborating institutions are located in and around the cosmopolitan city of Frankfurt in the heart of Europe. ====================================================================== APPLICATION PROCEDURE The review of applications will begin immediately. Required application materials: * complete scientific curriculum vitae * copy of Masters or Diploma certificate * copy of PhD certificate, if applicable * statement of research interests and achievements * at least two letters of reference * proof of proficiency in English (e.g., TOEFL or similar) Please send electronic files and scanned-in versions of documents (all in PDF format if possible). Files should be compiled into a ZIP archive. Applicants are asked to apply directly to up to three of the projects listed below. Write a single application and address it to the principal investigator(s) named as contact for the corresponding project(s). As subject line, please use "Bernstein: Application for PhD Position" or "Bernstein: Application for Post-doc Position". ======================================================================= DESCRIPTION OF PROJECTS ----------------------------------------------------------------------- Development of an Integrated System for Visual Recognition (Core project) In the core project we will integrate algorithms for visual perception and learning. Research will profit from the fact that many existing systems of perception and learning in vision solve complementary problems. The combination of different such systems will enable the development of a vision system with far-reaching capabilities. The essential challenge in the core project is to design, implement and evaluate a common software architecture that allows for the integration of very diverse visual sub-functions and their learning-based cooperation in order to solve complex vision tasks. For further information see: http://fias.uni-frankfurt.de/bernstein PIs: Rudolf Mester, Christoph von der Malsburg, Jochen Triesch, Cornelius Weber, Jorg Lucke Contact: for this project, contact _all_ three addresses: mester at vsi.cs.uni-frankfurt.de, malsburg at fias.uni-frankfurt.de, triesch at fias.uni-frankfurt.de ----------------------------------------------------------------------- Autonomous Learning in an Infant-Like Active Vision System We will develop an active vision system that autonomously learns to perceive the world around it. An existing anthropomorphic robot head capable of fast saccade-like eye movements will be used. In close collaboration with some of the other projects, the robot will be given learning capabilities including attentional mechanisms and curiosity drives. The robot will learn to control its gaze and learn both low-level (stereo, motion) and high-level (shapes, objects, people) representations and predictive models in an autonomous fashion. PIs: Jochen Triesch, Cornelius Weber, Christoph von der Malsburg Contact: triesch at fias.uni-frankfurt.de ----------------------------------------------------------------------- A Learning Visual Sensor System for a Mobile Platform This project addresses the demonstration of learnt and continuously improving visual perception used on a mobile robot which shall safely navigate in an unknown indoor environment, detect and identify obstacles and moving objects in the scene. The emphasis is not on the navigation capabilities but on perception: the project emphasizes the autonomous learning of motion and near-field environment perception capabilities under egomotion, considering the conjunction of perception (vision) and action (motor signals). PIs: Rudolf Mester, Hanno Scharr Contact: mester at vsi.cs.uni-frankfurt.de ----------------------------------------------------------------------- Cooperative Neural Learning Approaches in a Multi-Camera Visual Surveillance Scenario We plan to develop a system which exhibits autonomous learning of convergent cooperative processing of visual information in a large multi-camera setup which is arranged over an extended area. The demonstrator will show prototypically that a complex network of visual sensors can learn about the geometric and photometric interrelation between shared cameras, learn about the appearance and behavior of people, and ultimately learn about usual and unusual events in an autonomous fashion. This will be achieved by combining statistical methods and neural control and communication strategies. PIs: Rudolf Mester, Jochen Triesch Contact: mester at vsi.cs.uni-frankfurt.de ----------------------------------------------------------------------- Cue-Integration in Large-Scale Multi-Modal Sensory Systems Integrating various sensory modalities or submodalities is a fundamental activity of the brain. Often, the brain seems to integrate sensory signals in a close-to-optimal fashion. But how does it learn to do so? In this project we will develop computational models to explain how the brain forms efficient representations for sensory signals from different (sub-)modalities and how it learns to integrate them in an optimal fashion at the same time. PIs: Tobias Rodemann, Jochen Triesch Contact: triesch at fias.uni-frankfurt.de ----------------------------------------------------------------------- Hierarchical Memory Models In this project we will develop and investigate hierarchical memory structures for visual objects. We aim to develop explicit object representations that can serve as a basis for visual recognition. The studied systems learn from examples with no or little supervision. Probabilistic generative methods and dynamical systems approaches will be used. A background in mathematical modelling is desirable. PIs: Jorg Lucke, Christoph von der Malsburg Contact: luecke at fias.uni-frankfurt.de ----------------------------------------------------------------------- Analysis of Non-linear Dynamical Systems In this project we will develop methodologies to analyze large dynamical systems, to serve as a theoretical foundation of the dynamical system construction of the core vision system. Methods in nonlinear system analysis will be used, and extended with the assistance of numerical calculation to deal with general systems with less symmetry. PIs: Junmei Zhu, Christoph von der Malsburg Contact: jzhu at fias.uni-frankfurt.de ----------------------------------------------------------------------- Generative Models for Learning and Recognition in Vision Probabilistic generative models represent a state-of-the-art approach to component extraction. The vast majority of generative models used for this task assumes a linear superposition of components. For visual data this assumption is often violated. In this project we study a novel class of generative models which are not limited to linear component superposition and thus well-suited for applications to visual data. A background in mathematical modelling as provided by courses in mathematics, theoretical physics etc. is desirable. For further reading please see: fias.uni-frankfurt.de/~luecke PIs: Jorg Lucke, Julian Eggert Contact: luecke at fias.uni-frankfurt.de ----------------------------------------------------------------------- On-Camera Foveated Vision (FPGA Implementation) The early human visual system compresses data via high visual resolution at the fovea (gaze center) but low peripheral resolution. In this project we will implement such foveated vision, meeting high standards to foster its wider use, e.g. in other Bernstein projects. An on-camera implementation is desired, as via a programmable FPGA or via a "smart camera". The investigation of learning algorithms for low-level visual processing makes this project an ideal entry into computational neuroscience. Further reading: fias.uni-frankfurt.de/~cweber/08WeberTriesch_fovea.pdf PIs: Cornelius Weber, Volker Lindenstruth Contact: cweber at fias.uni-frankfurt.de ----------------------------------------------------------------------- Structural Learning of Motion and Depth Estimation This project aims at developing new processing structures for visual motion signals which take into consideration information from numerous different visual processing 'modules', such as stereo, optical flow, texture flow, higher-order covariance analysis etc. The developed algorithms will use stereo imagery together with motor signals, and egomotion data provided by an already available mobile robot platform. For further reading please visit: http://www.vsi.cs.uni-frankfurt.de/research/stellenhinweise.html PIs: Rudolf Mester, Hanno Scharr Contact: mester at vsi.cs.uni-frankfurt.de ----------------------------------------------------------------------- Neural Models of Development of Visual Processing and Memory in Human Infants The human visual system learns to perceive and understand the visual world in a largely autonomous fashion. But how do we develop an understanding of fundamental concepts of space, time, objects, or causality? How do we form memories and models of the physical and social world around us? In this project, we study selected questions from this area by a combination of experiments with human infants and the development of computational models. The models shall be rooted in biologically plausible learning processes and explain the improvement of infant competence as studied with methods from developmental psychology. PIs: Thorsten Kolling, Monika Knopf, Jochen Triesch Contact: triesch at fias.uni-frankfurt.de ----------------------------------------------------------------------- Modeling the Role of Feedback Signals in Visual Motion Processing Massive feedback from higher to lower processing areas are a hallmark of the cortical architecture. This project combines physiological, anatomical and computational modeling approaches to investigate the functional role of these feedback connections for motion processing. On the experimental side, we will use reversible cooling of the cortex to selectively deactivate higher processing areas and observe the impact of the (lack of) their feedback signals on processing in V1. On the modeling side, we will develop models that aim to explain the functional role of these connections (e.g. contributing to Bayesian inference) as well as the learning mechanisms that shape them. PIs: Ralf Galuske, Jochen Triesch Contact PI: triesch at fias.uni-frankfurt.de ====================================================================== For more information about the collaborating institutes please see: - Neuroscience, FIAS, Goethe-University Frankfurt http://fias.uni-frankfurt.de/neuro - VSI, Dept of Computer Science, Goethe-University Frankfurt http://www.vsi.cs.uni-frankfurt.de/research - MPI for Brain Research, Frankfurt http://www.mpih-frankfurt.mpg.de) - Honda Research Institute Europe http://www.honda-ri.de -- Dr. J?rg L?cke Frankfurt Institute for Advanced Studies (FIAS) Goethe-Universit?t Frankfurt Germany From opossumnano at gmail.com Wed Oct 22 05:04:23 2008 From: opossumnano at gmail.com (Tiziano Zito) Date: Wed, 22 Oct 2008 11:04:23 +0200 Subject: Connectionists: Modular toolkit for Data Processing 2.4 released! Message-ID: <20081022090423.GA18890@localhost> We are glad to announce release 2.4 of the Modular toolkit for Data Processing (MDP). MDP is a Python library of widely used data processing algorithms that can be combined according to a pipeline analogy to build more complex data processing software. The base of available algorithms includes, to name but the most common, Principal Component Analysis (PCA and NIPALS), several Independent Component Analysis algorithms (CuBICA, FastICA, TDSEP, and JADE), Slow Feature Analysis, Restricted Boltzmann Machine, and Locally Linear Embedding. What's new in version 2.4? -------------------------------------- - The new version introduces a new parallel package to execute the MDP algorithms on multiple processors or machines. The package also offers an interface to develop customized schedulers and parallel algorithms. Old MDP scripts can be turned into their parallelized equivalent with one simple command. - The number of available algorithms is increased with the Locally Linear Embedding and Hessian eigenmaps algorithms to perform dimensionality reduction and manifold learning (many thanks to Jake VanderPlas for his contribution!) - Some more bug fixes, useful features, and code migration towards Python 3.0 Resources --------- Download: http://sourceforge.net/project/showfiles.php?group_id=116959 Homepage: http://mdp-toolkit.sourceforge.net Mailing list: http://sourceforge.net/mail/?group_id=116959 -- Pietro Berkes Volen Center for Complex Systems Brandeis University Waltham, MA, USA Niko Wilbert Institute for Theoretical Biology Humboldt-University Berlin, Germany Tiziano Zito Bernstein Center for Computational Neuroscience Humboldt-University Berlin, Germany From pierre-yves.oudeyer at inria.fr Thu Oct 23 17:43:52 2008 From: pierre-yves.oudeyer at inria.fr (Pierre-Yves Oudeyer) Date: Thu, 23 Oct 2008 23:43:52 +0200 Subject: Connectionists: [publication and CFP] IEEE CIS Newsletter on Autonomous Mental Development Message-ID: <4900F018.8000009@inria.fr> Dear colleagues, It is my pleasure to announce you that the latest issue of the IEEE CIS Newsletter on Autonomous Mental Development, is available at: http://www.cse.msu.edu/amdtc/amdnl/AMDNL-V5-N2.pdf This issue announces the creation of a journal dedicated to developmental robotics and computational developmental systems, the IEEE Transactions on Autonomous Mental Development. The inaugural issue will appear early next year. I encourage all of you to submit papers for this issue. The deadline is 14^th December. In this issue, we also have two lively reports of IEEE ICDL 2008 and Epirob 2008 conferences, highlighting high selection standards as well as important research topics such as embryogenesis and the interaction between evolution and development. The dialog column, orchestrated by Paul Fitzpatrick, challenges us around the question of finding killer-applications for developmental systems, with answers from Charlie Kemp, Hideki Kozima, Matthew Schlesinger, Claus Von Hofsten, Juyang Weng, and Lola Canamero. Finally, Kerstin Dautenhahn's call for next issue's dialog questions the use of robots for investigating human developmental disorders such as autism, as well as potential tools for therapy. Answers shall be sent by the 15th February to k.dautenhahn at herts.ac.uk or pierre-yves.oudeyer at inria.fr. I wish you a stimulating reading! Best regards, Pierre-Yves Oudeyer, /Editor of the IEEE CIS Newsletter on Autonomous Mental Development INRIA Bordeaux Sud-Ouest 351, cours de la lib?ration, 33405 Talence, France http://www.pyoudeyer.com/ -------------- next part -------------- An HTML attachment was scrubbed... URL: https://mailman.srv.cs.cmu.edu/mailman/private/connectionists/attachments/20081023/db276ee9/attachment.html From reza at fmrib.ox.ac.uk Mon Oct 27 11:47:40 2008 From: reza at fmrib.ox.ac.uk (Reza Salimi) Date: Mon, 27 Oct 2008 15:47:40 +0000 Subject: Connectionists: Post-doctoral Research Assistant in Imaging Neuroscience (FMRIB Centre, University of Oxford) Message-ID: Department of Clinical Neurology Oxford University Centre for Functional MRI of the Brain (FMRIB) Post-doctoral research assistant in Imaging Neuroscience Salary: Grade 7, ?27,466? ?33,780 p.a. The Centre for Functional Magnetic Resonance Imaging of the Brain seeks a post doctoral scientist to carry out research in imaging of neurodegenerative disorders using in vivo and ex vivo MRI imaging. The project is a collaboration between Imperial College London and the FMRIB centre. The successful candidate will be working under supervision of Dr. Mojtaba Zarei and Prof. Paul Matthews. S/he will be liaising between two Centres for data acquisition and analysis. The post is funded by the Department of Health. The successful candidate should have a PhD or equivalent in a relevant discipline with experience in MRI data acquisition and analysis. An excellent academic track record, together with a good understanding of MRI physics, as well as programming skills are desirable. The post is available immediately until 31st October 2009, with the possibility of extension, subject to funding availability. For an outline of the lab's research interests and links to further information see http://www.fmrib.ox.ac.uk/fmrib-research/neurodegeneration. Applicants should send their CV and research statement to: mojtaba @fmrib.ox.ac.uk -- G. Salimi-Khorshidi, D.Phil. Student, Dept. of Clinical Neurology, University of Oxford. reza at fmrib.ox.ac.uk http://www.fmrib.ox.ac.uk/~reza FMRIB Centre, John Radcliffe Hospital, Headington, Oxford, OX3 9DU Tel: +44 (0) 1865 222466 Fax: +44 (0)1865 222717 -------------- next part -------------- An HTML attachment was scrubbed... URL: https://mailman.srv.cs.cmu.edu/mailman/private/connectionists/attachments/20081027/96afeb1d/attachment-0001.html From NikolayV.Manyakov at med.kuleuven.be Tue Oct 28 05:36:14 2008 From: NikolayV.Manyakov at med.kuleuven.be (Nikolay Manyakov) Date: Tue, 28 Oct 2008 10:36:14 +0100 Subject: Connectionists: Call for papers for the IJNS special issue "Advances in the neurodynamics of cortical interactions" Message-ID: <4906DD0E.6090204@med.kuleuven.be> ---- Apologies for cross-posting ---- Call for papers for the special issue: "Advances in the neurodynamics of cortical interactions" International Journal of Neural Systems http://www.worldscinet.com/ijns/ijns.shtml Editor-in-Chief: Hojjat Adeli, Ohio State University, USA, Adeli.1 at osu.edu Special Issue editors: Marc M. Van Hulle, K.U.Leuven, Belgium, marc.vanhulle at med.kuleuven.be Milan Palus, Academy of Sciences, Czech Republic Dennis J McFarland, Wadsworth Laboratories, USA Deadline: December 31, 2008 The special issue invites original contributions in either theory, algorithms or methods for estimating causality, synchrony and other forms of interactions obtained invasively through chronically implanted multi-electrode arrays, and non-invasively through fMRI, EEG or MEG. Not only within modality interactions are targeted, such as synchrony between spike trains, but also across modalities, such as interactions between spike trains and local field potentials (LFPs) and between LFPs and fMRI, or EEG and fMRI. The recorded signals can be linear and stationary or not, and their interactions requiring the bridging of different temporal and spatial resolutions. Neural engineering applications of cortical interaction modeling to brain-machine interfacing and neuroprosthetic devices are encouraged. Following the success of the special issue on Synchronization in Neural Systems published as issue 17:2, April 2007, the International Journal of Neural Systems http://www.worldscinet.com/ijns/ijns.shtml is devoting a special issue on neurodynamics of cortical interactions. The main objective of this special issue is to increase the visibility of the techniques and methods of cortical interaction modeling, and to foster the exchange between different disciplines, hence, the contributions should be made accessible not only to the neural engineering audience. Prospective authors are invited to submit their full-length articles of maximally 30 double spaced pages following the submission guidelines of IJNS. Each submission will be peer-reviewed by at least three reviewers. Submission of a manuscript implies that it is original unpublished work that has not been submitted for possible publication elsewhere previously. Please inform the guest editors and the Editor-in-Chief about your intention to submit a manuscript for possible publication in the special issue as soon as possible. Please email your original contribution as a pdf file to the first Guest Editor with a copy to the Editor-in-Chief by December 31, 2008. Disclaimer: http://www.kuleuven.be/cwis/email_disclaimer.htm From A.Garay-Arevalo at statslab.cam.ac.uk Tue Oct 28 09:46:18 2008 From: A.Garay-Arevalo at statslab.cam.ac.uk (A.Garay-Arevalo@statslab.cam.ac.uk) Date: 28 Oct 2008 13:46:18 +0000 Subject: Connectionists: Vacancies, University of Cambridge - Lectureship, PDRAs, PhD Studentships Message-ID: Dear All, The Cambridge Statistics Initiative, based out of the Statistical Laboratory of the Department of Pure Mathematics and Mathematical Statistics, has several new positions available. Please apply to the below-mentioned contacts for each position. **** University of Cambridge University Lectureship in Statistics Salary: ?34,793- ?44,074 Vacancy Reference: LF04213 Applications are invited for a University Lectureship in Statistics, to be held in the Statistical Laboratory and filled by 1 September 2009, or by negotiation. Information about the Laboratory can be found at www.statslab.cam.ac.uk . Appointment will be made at an appropriate point on the scale for University Lecturers and will be until the retiring age, but will be subject to an initial probationary period of five years. Applications should be sent in hard copy or by email to Professor R. R. Weber, Director, Statistical Laboratory, Department of Pure Mathematics & Mathematical Statistics, Wilberforce Road, Cambridge CB3 0WB (fax: (01223) 337956; email: vacancies at statslab.cam.ac.uk), and should include a full curriculum vitae, email address, list of publications and the names and email addresses of three academic referees, and should be accompanied by a completed form PD18 Parts I and III (downloadable from here ). Applicants should ask their referees to email/post letters directly to the Director, to reach him by the closing date. Further particulars are available at www.statslab.cam.ac.uk/Vacancies/. Closing date: 28 November 2008. -------------------------------------------------------------------------------- University of Cambridge Postdoctoral Research Associates Salary: ?25,888-?33,780 pa Vacancy Reference LF04215 Limit of Tenure applies* Applications are invited for Postdoctoral Research Associate positions in Statistics, to be held in the Statistical Laboratory and to commence on a date to be negotiated. Information about the Laboratory can be found at www.statslab.cam.ac.uk . These research posts, which are available for between two and three years, are associated with a major expansion of personnel and activities in core statistical methodology and its applications. Appointment will be made at an appropriate point on the scale for Research Associates. Applications should be sent in hard copy or by email to Professor R. R. Weber, Director, Statistical Laboratory, Wilberforce Road, Cambridge CB3 0WB (fax (01223) 337956; email vacancies at statslab.cam.ac.uk), and should include full curriculum vitae, email address, list of publications and the names and email addresses of two academic referees, and should be accompanied by a completed PD18 Part I and III (downloadable from here ). Applicants should ask their referees to email/post letters directly to the Director, to reach him by the closing date. Further particulars are available at www.statslab.cam.ac.uk/Vacancies . *Limit of tenure: 2-3 years Closing Date: 28 November 2008 -------------------------------------------------------------------------------- University of Cambridge PhD Studentships in Statistics Vacancy Reference No: LF04227 Limit of tenure applies* Applications are invited for PhD studentships in Statistics, to be held in the Statistical Laboratory. The Studentships are associated with the Cambridge Statistics Initiative which is targeted at the development of novel statistical methodology, both generic and in specific application areas. Information about the Laboratory can be found at www.statslab.cam.ac.uk . The studentships will provide funding to cover fees at the home/EU rate. Additional funding for fees for those paying the overseas arts rate could be available and will be assessed competitively. A stipend will be paid of at least the equivalent to the national minimum (?13290 for the academic year 2009/10) for a minimum period of 3 years. Supervision, along with research training tailored to the needs of the student, will be provided by the Laboratory. Research interests of academic staff can be found here . Applicants must qualify for admission to the PhD course at the University of Cambridge. They should normally hold (or expect to be awarded) a first class UK honours degree or equivalent and a postgraduate qualification in Mathematics or Statistics. Initial enquiries, which should include a curriculum vitae and an indication of possible research topics, should be directed to Professor A.P. Dawid. * Limit of tenure: 3 years Closing date: 31 January 2009. ------------ -------------- next part -------------- A non-text attachment was scrubbed... Name: Lecturer advert public-1.doc Type: application/msword Size: 30720 bytes Desc: Lecturer advert public-1.doc Url : https://mailman.srv.cs.cmu.edu/mailman/private/connectionists/attachments/20081028/5c967f2c/Lectureradvertpublic-1-0001.doc -------------- next part -------------- A non-text attachment was scrubbed... Name: PDRA advert public-1.doc Type: application/msword Size: 31232 bytes Desc: PDRA advert public-1.doc Url : https://mailman.srv.cs.cmu.edu/mailman/private/connectionists/attachments/20081028/5c967f2c/PDRAadvertpublic-1-0001.doc From d.mandic at imperial.ac.uk Fri Oct 24 14:09:20 2008 From: d.mandic at imperial.ac.uk (Danilo P. Mandic) Date: Fri, 24 Oct 2008 19:09:20 +0100 Subject: Connectionists: A DVV toolbox for detecting the degree of nonlinearity and uncertainty in time series Message-ID: <49020F50.9030901@imperial.ac.uk> Dear All, The "Delay Vector Variance" toolbox is available at http://www.commsp.ee.ic.ac.uk/~mandic/dvv.htm It characterizes the modality (linear, nonlinear, deterministic, stochastic) of a time series and is very useful for the analysis of biomedical time series (fMRI, EEG, HRV) and also provides 'nonlinear' features in data fusion applications (sleep psychology, fatigue in car drivers). Enjoy Danilo =================== Dr Danilo Mandic Department of Electrical and Electronic Engineering Imperial College London, United Kingdom From btuller at nsf.gov Fri Oct 31 10:18:57 2008 From: btuller at nsf.gov (Tuller, Betty K.) Date: Fri, 31 Oct 2008 10:18:57 -0400 Subject: Connectionists: Program Officer position in Cognitive Neuroscience at NSF Message-ID: <1D6FC73B2F5DFD4CAD5F54416E5DA2C201393765@NSF-BE-02.ad.nsf.gov> The National Science Foundation is seeking candidates for a Program Director position in the Cognitive Neuroscience Program within the Division of Behavioral and Cognitive Sciences (BCS), Directorate for Social, Behavioral, and Economic (SBE) Sciences, located in Arlington, VA. The Cognitive Neuroscience Program is focused on advancing a rigorous understanding of how the human brain supports thought, perception, affect, action social processes, language, and other aspects of cognition and behavior, including how such processes develop and change in the brain over time. Major duties of the Program Director include implementing the proposal review and evaluation process for the program and recommending awards or declinations based on merit, resource availability, and program goals. Applicants must have a Ph.D. or equivalent experience directly related to the neuroscience of human cognition, language, social behavior or culture sciences; plus six or more years of successful research, research administration, and/or managerial experience pertinent to the program. For additional information, please see: http://jobsearch.usajobs.opm.gov/getjob.asp?JobId=76724952&AVSDM=2008%2D 10%2D16+14%3A00%3A40 For people unfamiliar with the NSF Rotator Program, it allows a mid- to senior-level academic to come to Washington for a year or two and assume the role and responsibilities of a program officer. They are both Program and Review, run the review meetings ("Panels" at NSF), and make funding decisions. One year is probably a bit too short to do anything truly innovative, such as start a new program, but with a two-year stint you can have a permanent effect in shaping the field. Important note: You don't have to 'waste' a sabbatical to do this, as most institutions will allow you to take a leave of absence. The NSF pays your full (12-month equivalent) salary, with a cost of living adjustment to DC, either through your university or as a temporary federal employee. You will learn a lot about how the grants process works and get to enjoy all that Washington has to offer. Please forward this announcement to anyone you think might be interested. For more detailed information, look at the ad on USAjobs, referenced above, or call Stacia Friedman-Hill (currently a Program Officer for Cognitive Neuroscience) at 703.292.8121. Betty Tuller, Ph.D. Director, Program in Perception, Action, and Cognition National Science Foundation 4201 Wilson Blvd Arlington, VA 22230 Tel: 703.292.7238 Fax: 703.292.9068 New proposal guidelines will be effective in January 2009; see http://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf091 -------------- next part -------------- An HTML attachment was scrubbed... URL: https://mailman.srv.cs.cmu.edu/mailman/private/connectionists/attachments/20081031/5a5ae54e/attachment-0001.html From terry at salk.edu Mon Oct 27 18:13:17 2008 From: terry at salk.edu (Terry Sejnowski) Date: Mon, 27 Oct 2008 15:13:17 -0700 Subject: Connectionists: UCSD Computational Neurobiolology Gradaute Training Program Message-ID: DEADLINE: DECEMBER 1, 2008 UCSD COMPUTATIONAL NEUROBIOLOGY Neurosciences Graduate Training Program - University of California, San Diego http://neurograd.ucsd.edu/doctoral/cnspec.html http://compneuro.salk.edu/ The goal of the Computational Neurobiology Graduate Program at UCSD is to train researchers who are equally at home measuring large-scale brain activity, analyzing the data with advanced computational techniques, and developing new models for brain development and function. Candidates from a wide range of backgrounds are invited to apply, including Biology, Psychology, Computer Science, Physics and Mathematics. The three major themes in the training program are: 1. Neurobiology of Neural Systems: Anatomy, physiology and behavior of systems of neurons. Using modern neuroanatomical, behavioral, neuropharmacological and electrophysiological techniques. Lectures, wet laboratories and computer simulations, as well as research rotations. Major new imaging and recording techniques also will be taught, including two-photon laser scanning microscopy and functional magnetic resonance imaging (fMRI). 2. Algorithms and Realizations for the Analysis of Neuronal Data: New algorithms and techniques for analyzing data obtained from physiological recording, with an emphasis on recordings from large populations of neurons with imaging and multielectrode recording techniques. New methods for the study of co-ordinated activity, such as multi-taper spectral analysis and Independent Component Analysis (ICA). 3. Neuroinformatics, Dynamics and Control of Systems of Neurons: Theoretical aspects of single cell function and emergent properties as many neurons interact among themselves and react to sensory inputs. A synthesis of approaches from mathematics and physical sciences as well as biology will be used to explore the collective properties and nonlinear dynamics of neuronal systems, as well as issues of sensory coding and motor control. Participating Faculty include: * Henry Abarbanel (Physics): Nonlinear and oscillatory dynamics; modeling central pattern generators in the lobster stomatogastric ganglion. Director, Institute for Nonlinear Systems at UCSD * Thomas Albright (Salk Institute): Motion processing in primate visual cortex; linking single neurons to perception; fMRI in awake, behaving monkeys. Director, Sloan Center for Theoretical Neurobiology * Darwin Berg (Neurobiology): Regulation synaptic components, assembly and localization, function and long-term stability. * Ed Callaway (Salk Institute): Neural circuits, visual perception, visual cortex Genetic tools for tracing neural pathways. * Gert Cauwenberghs (Biology): Neuromorphic Engineering; analog VLSI chips; wireless recording and nanoscale instrumentation for neural systems; large-scale cortical modeling. * EJ Chichilnisky (Salk Institute): Retinal multielectrode recording; neural coding, visual perception. * Garrison Cottrell (Computer Science and Engineering): Dynamical neural network models and learning algorithms * Virginia De Sa (Cognitive Science): Computational basis of perception and learning (both human and machine); multi-sensory integration and contextual influences * Mark Ellisman (Neurosciences, School of Medicine): High resolution electron and light microscopy; anatomical reconstructions. Director, National Center for Microscopy and Imaging Research * Fred Gage (Salk Institute): Neurogenesis and models of the hippocampus; neuronal diversity, neural stem cells. * Robert Hecht-Nielsen (Electrical and Computer Engineering): Neural computation and the functional organization of the cerebral cortex. Founder of Hecht-Nielsen Corporation * Harvey Karten (Neurosciences, School of Medicine): Anatomical, physiological and computational studies of the retina and optic tectum of birds and squirrels * David Kleinfeld (Physics): Active sensation in rats; properties of neuronal assemblies; optical imaging of large-scale activity. * William Kristan (Neurobiology): Computational Neuroethology; functional and developmental studies of the leech nervous system, including studies of the bending reflex and locomotion. Director, Neurosciences Graduate Program at UCSD * Herbert Levine (Physics): Nonlinear dynamics and pattern formation in physical and biological systems, including cardiac dynamics and the growth and form of bacterial colonies * Scott Makeig (Institute for Neural Computation): Analysis of cognitive event-related brain dynamics and fMRI using time-frequency and Independent Component Analysis * Javier Movellan (Institute for Neural Computation): Sensory fusion and learning algorithms for continuous stochastic systems * Mikhael Rabinovich (Institute for Nonlinear Science): Dynamical systems analysis of the stomatogastric ganglion of the lobster and the antenna lobe of insects * Pamela Reinagel (Biology): Sensory and neural coding; natural scene statistics; recordings from the visual system of cats and rodents. * Massimo Scanziani (Biology): Neural circuits in the somotosensory cortex; physiology of synaptic transmission; inhibitory mechanisms. * Terrence Sejnowski (Salk Institute/Neurobiology): Computational neurobiology; physiological studies of neuronal reliability and synaptic mechanisms. Director, Institute for Neural Computation * Tanya Sharpee (Salk): Statistical physics and information theory approach to understanding sensory processing. Statistical properties of natural auditory and visual environments. * Nicholas Spitzer (Neurobiology): Regulation of ionic channels and neurotransmitters in neurons; effects of electrical activity in developing neurons on neural function. Chair of Neurobiology * Charles Stevens (Salk Institute): Synaptic physiology; theoretical models of neuroanatomical scaling. * Roger Tsien (Chemistry): Second messenger systems in neurons; development of new optical and MRI probes of neuron function, including calcium indicators and caged neurotransmitters * Ruth Williams (Mathematics): Probabilistic analysis of stochastic systems and continuous learning algorithms On-line applications: http://neurograd.ucsd.edu/admissions/index.html The deadline for completed application materials, including letters of recommendation, is December 1, 2008. From terry at salk.edu Thu Oct 30 21:28:56 2008 From: terry at salk.edu (Terry Sejnowski) Date: Thu, 30 Oct 2008 18:28:56 -0700 Subject: Connectionists: NEURAL COMPUTATION - December, 2008 In-Reply-To: Message-ID: Neural Computation - Contents - Volume 20, Number 12 - December 1, 2008 ARTICLES Optimization of decision making in multilayer networks: The role of Locus Coeruleus Eric Shea-Brown, Mark Gilzenrat, and Jonathan Cohen Indices for Testing Neural Codes Jonathan Victor and Sheila Nirenberg A Mathematical Analysis of the Effects of Hebbian Learning Rules on the Dynamics and Structure of Discrete-time Random Recurrent Neural Networks Benoit Siri, Hugues Berry, Bruno Cessac, Bruno Delord, and Mathias Quoy NOTE A Fast, Streaming SIMD Extensions 2, Logistic Squashing Function Jonathan Milner and Angus Grandison LETTERS Gamma Oscillations in a Non-linear Regime: a Minimal Model Approach Using Heterogeneous Integrate and Fire Networks Brice Bathellier, Alan Carleton, and Wulfram Gerstner Analytical and Simulation Results for the Stochastic Spatial Fitzhugh-Nagumo Model Neuron Henry Tuckwell Representation and the Timing of Reward-Prediction Errors in Models of the Dopamine System Elliot Ludvig, Richard Sutton, and E. James Kehoe An Ongoing Subthreshold Neuronal State Established Through Dynamic Co-Assembling of Cortical Cells Osamu Hoshino Optimal Approximation of Signal Priors Aapo Hyvarinen Sleeping Our Way to Weight Normalization and Stable Learning Thomas Sullivan and Virginia de Sa ----- ON-LINE - http://neco.mitpress.org/ SUBSCRIPTIONS - 2009 - VOLUME 21 - 12 ISSUES USA/Canada Others Electronic only Student/Retired $60 $123 $54 Individual $110 $173 $99 Institution $849 $912 $756 MIT Press Journals, 238 Main Street, Suite 500, Cambridge, MA 02142-9902. Tel: (617) 253-2889 FAX: (617) 577-1545 journals-orders at mit.edu http://mitpressjournals.org/neuralcomp ----- From maass at igi.tugraz.at Fri Oct 31 13:27:13 2008 From: maass at igi.tugraz.at (Wolfgang Maass) Date: Fri, 31 Oct 2008 18:27:13 +0100 Subject: Connectionists: positions for research on computation and learning in networks of spiking neurons Message-ID: <490B3FF1.2010107@igi.tugraz.at> In the research group of Wolfgang Maass at the Graz University of Technology in Austria ( http://www.igi.tugraz.at/maass/ ) there are openings for a Postdoc and a Phd student for research on computation and learning in networks of spiking neurons, with application to models for biological visual processing and related technological devices (e.g. the spike-based Dynamic Vision Sensor http://siliconretina.ini.uzh.ch/wiki/index.php). Interest in understanding brain function as well as knowledge in machine learning, computer vision, computation theory, and programming skills are expected. Applicants should send their CV and pdf's of relevant publications by Nov. 12 to Angelika Zehetner angelika at igi.tugraz.at -- Prof. Dr. Wolfgang Maass Institut fuer Grundlagen der Informationsverarbeitung Technische Universitaet Graz Inffeldgasse 16b , A-8010 Graz, Austria Tel.: ++43/316/873-5811 Fax ++43/316/873-5805 http://www.igi.tugraz.at/maass/Welcome.html From dominik.janzing at tuebingen.mpg.de Fri Oct 31 04:01:08 2008 From: dominik.janzing at tuebingen.mpg.de (Dominik Janzing) Date: Fri, 31 Oct 2008 09:01:08 +0100 Subject: Connectionists: NIPS2008 causality workshop: deadline extensions Message-ID: Dear causality enthusiasts, Two more tasks have been added to the Pot-luck challenge and the deadline was extended to ** November 19 **. Win one of four prizes! See http://clopinet.com/causality . Regardless of your participation to the challenge, you may submit an abstract until ** November 21 ** for the NIPS workshop http://clopinet.com/isabelle/Projects/NIPS2008/ to present a poster or submit a 6-page paper to apply for an oral presentation and/or be published in the proceedings. Confirmed invited speakers: Phil Dawid (University of Cambridge), Patrik Hoyer (University of Helsinki), Kevin Murphy (University of British Columbia), Judea Pearl (UCLA), Thomas Richardson (University of Washington), Donald Rubin (Harvard University), and Richard Scheines, (Carnegie Mellon University). We hope to see you then! Isabelle Guyon, Dominik Janzing and Bernhard Schoelkopf From d.mandic at imperial.ac.uk Fri Oct 31 10:21:55 2008 From: d.mandic at imperial.ac.uk (Danilo Mandic) Date: Fri, 31 Oct 2008 14:21:55 +0000 Subject: Connectionists: Three Lectureship posts in Neurotechnology at Imperial College London - deadline 9 JAnuary 2009 Message-ID: <490B1483.6010300@imperial.ac.uk> Dear All, Imperial College is seeking to make three appointments at the interface between neuroscience and engineering. Two of these appointments will be joint lectureships between the Departments of Bioengineering and Electrical and Electronic Engineering (EEE). The third appointment will be a joint lectureship between the Departments of Bioengineering and Computing. Applicants should have a strong record of academic achievement and be able to direct an exciting and independent research programme in an area that synergises with our current activities. For more detail and information how to apply, go to http://www3.imperial.ac.uk/employment/academic/en20080235 Imperial College London is ranked in the top five universities of the world, according to the 2007 Times Higher Education Supplement league tables. From dejan at igi.tugraz.at Wed Oct 29 11:21:58 2008 From: dejan at igi.tugraz.at (Pecevski Dejan) Date: Wed, 29 Oct 2008 16:21:58 +0100 Subject: Connectionists: New paper about reward-modulated spike-timing-dependent plasticity Message-ID: <49087F96.9060706@igi.tugraz.at> Dear all, A new paper that provides a theoretical analysis of the functional properties of reward-modulated spike-timing-dependent plasticity is available online at: http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000180 (http://www.igi.tugraz.at/maass/psfiles/183_legenstein_etal_2008.pdf ) The paper also discusses the possible role of spontaneous activity and trial to trial variability in cortical networks as an exploration strategy during learning with reward-modulated STDP. Abstract: Reward-modulated spike-timing-dependent plasticity (STDP) has recently emerged as a candidate for a learning rule that could explain how behaviorally relevant adaptive changes in complex networks of spiking neurons could be achieved in a self-organizing manner through local synaptic plasticity. However, the capabilities and limitations of this learning rule could so far only be tested through computer simulations. This article provides tools for an analytic treatment of reward-modulated STDP, which allows us to predict under which conditions reward-modulated STDP will achieve a desired learning effect. These analytical results imply that neurons can learn through reward-modulated STDP to classify not only spatial but also temporal firing patterns of presynaptic neurons. They also can learn to respond to specific presynaptic firing patterns with particular spike patterns. Finally, the resulting learning theory predicts that even difficult credit-assignment problems, where it is very hard to tell which synaptic weights should be modified in order to increase the global reward for the system, can be solved in a self-organizing manner through reward-modulated STDP. This yields an explanation for a fundamental experimental result on biofeedback in monkeys by Fetz and Baker. In this experiment monkeys were rewarded for increasing the firing rate of a particular neuron in the cortex and were able to solve this extremely difficult credit assignment problem. Our model for this experiment relies on a combination of reward-modulated STDP with variable spontaneous firing activity. Hence it also provides a possible functional explanation for trial-to-trial variability, which is characteristic for cortical networks of neurons but has no analogue in currently existing artificial computing systems. In addition our model demonstrates that reward-modulated STDP can be applied to all synapses in a large recurrent neural network without endangering the stability of the network dynamics. -- Dejan Pecevski, Dipl.-Ing. Institute for Theoretical Computer Science Graz University of Technology A-8010 Graz, Austria From Dominique.Martinez at loria.fr Thu Oct 30 12:02:12 2008 From: Dominique.Martinez at loria.fr (Dominique Martinez) Date: Thu, 30 Oct 2008 17:02:12 +0100 Subject: Connectionists: Post-doctoral position in computational olfaction at INRA Versailles or LORIA Nancy, France Message-ID: <20081030170212.kzn14r1sqlco0wwo@webmail.loria.fr> A full-time postdoctoral position in computational neuroscience is available for studying the role of oscillatory synchronization in olfactory systems. The aim of the project is to understand the mechanisms of odour coding by means of a multidisciplinary approach combining models and experiments. The candidate will have to interact with other researchers in a mixed team of modellers using mathematical and computational methods and experimentalists performing electrophysiological recordings of neurons. The project also includes collaboration with the CNRS in Lyon, France. The successful candidate will be responsible for the statistical analysis of experimental data and for designing network models based on experimental findings. The work will be performed either at LORIA, a computer science laboratory from the National Institute for Computer Science (INRIA) in Nancy, or at the National Institute for Agricultural Research (INRA) in Versailles, at half an hour train from down-town Paris. The position is for 18 months, starting on Jan. 2009 with a possible extension up to three years. Candidates should hold a PhD degree in a relevant discipline (Computer Science, Mathematics or Physics). The candidate should have expertise in programming (Python, MySQL, C/C++, Matlab), and should demonstrate a strong interest in biophysics, systems neuroscience, or cognitive neuroscience. Knowledge in statistics would also be appreciated. Applications including a CV, a motivation letter and the names of two references must be sent electronically to Dominique Martinez (Dominique.Martinez at loria.fr) and Jean-Pierre Rospars (Rospars at versailles.inra.fr). From YOMTOV at il.ibm.com Tue Oct 28 20:27:34 2008 From: YOMTOV at il.ibm.com (Elad Yom-Tov) Date: Tue, 28 Oct 2008 16:27:34 -0800 Subject: Connectionists: CFP: Journal of Machine Learning Research - Special Topic on Large Scale Learning Message-ID: An HTML attachment was scrubbed... URL: https://mailman.srv.cs.cmu.edu/mailman/private/connectionists/attachments/20081028/544287b3/attachment.html