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Special issue of the Journal of Mathematical Neuroscience
by Olivier Faugeras 24 Apr '14

24 Apr '14

Dear all, I am pleased to announce that a Special Issue of the Journal of Mathematical Neuroscience on Uncertainty and the Brain has just appeared in Open Access at: http://www.mathematical-neuroscience.com/series/UB Uncertainty and the Brain Edited by: Dr Olivier Faugeras, Prof Michele Thieullen Theoretical and applied neuroscientists are in great need of stochastic models to account for sources of uncertainty in neural tissues in a mathematically rigorous framework allowing for quantitative descriptions and predictions. Collection published: 17 April 2014 Editorial ** *Editorial for the Special Issue on Uncertainty in the Brain <http://www.mathematical-neuroscience.com/content/4/1/7>* Olivier Faugeras, Michèle Thieullen /The Journal of Mathematical Neuroscience/ 2014, *4*:7 (17 April 2014) ** *Measuring Edge Importance: A Quantitative Analysis of the Stochastic Shielding Approximation for Random Processes on Graphs <http://www.mathematical-neuroscience.com/content/4/1/6>* Deena R Schmidt, Peter J Thomas /The Journal of Mathematical Neuroscience/ 2014, *4*:6 (17 April 2014) Research ** *How Uncertainty Bounds the Shape Index of Simple Cells <http://www.mathematical-neuroscience.com/content/4/1/5>* D Barbieri, G Citti, A Sarti /The Journal of Mathematical Neuroscience/ 2014, *4*:5 (17 April 2014) ** *Fokker--Planck and Fortet Equation-Based Parameter Estimation for a Leaky Integrate-and-Fire Model with Sinusoidal and Stochastic Forcing <http://www.mathematical-neuroscience.com/content/4/1/4>* Alexandre Iolov, Susanne Ditlevsen, André Longtin /The Journal of Mathematical Neuroscience/ 2014, *4*:4 (17 April 2014) ** *Goodness-of-Fit Tests and Nonparametric Adaptive Estimation for Spike Train Analysis <http://www.mathematical-neuroscience.com/content/4/1/3>* Patricia Reynaud-Bouret, Vincent Rivoirard, Franck Grammont, Christine Tuleau-Malot /The Journal of Mathematical Neuroscience/ 2014, *4*:3 (17 April 2014) ** *Large Deviations for Nonlocal Stochastic Neural Fields <http://www.mathematical-neuroscience.com/content/4/1/1>* Christian Kuehn, Martin G Riedler /The Journal of Mathematical Neuroscience/ 2014, *4*:1 (17 April 2014) ** *A Density Model for a Population of Theta Neurons <http://www.mathematical-neuroscience.com/content/4/1/2>* Grégory Dumont, Jacques Henry, Carmen Tarniceriu /Journal of Mathematical Neuroscience/ 2014, *4*:2 (17 April 2014) --------------------------------------------------------------------------------------- : Olivier Faugeras : Professor : Equipe INRIA NeuroMathComp Team : co-editor in chief, Journal of Mathematical Neuroscience : http://www-sop.inria.fr/members/Olivier.Faugeras/index.en.html : Email: olivier.faugeras(a)inria.fr : Tel: +334 92 38 78 31 : Sec: +334 92 38 78 30 : ---------------------------------------------------------------------------------------

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[RSS2014] CfP: First Workshop on Affordances: Affordances in "Vision for Cognitive Robotics" (in conjunction with RSS 2014)
by Karthik Mahesh Varadarajan 23 Apr '14

23 Apr '14

====================================================================== *Call for Papers- First Workshop on Affordances: Affordances in Vision for Cognitive Robotics* (in conjunction with RSS 2014), July 13, 2014, Berkeley, USA http://affordances.info/workshops/RSS.html ====================================================================== Based on the Gibsonian principle of defining objects by their function, "affordances" have been studied extensively by psychologists and visual perception researchers, resulting in the creation of numerous cognitive models. These models are being increasingly revisited and adapted by computer vision and robotics researchers to build cognitive models of visual perception and behavioral algorithms in recent years. This workshop attempts to explore this nascent, yet rapidly emerging field of affordance based cognitive robotics while integrating the efforts and language of affordance communities not just in computer vision and robotics, but also psychophysics and neurobiology by creating an open affordance research forum, feature framework and ontology called AfNet (theaffordances.net) In particular, the workshop will focus on emerging trends in affordances and other human-centered function/action features that can be used to build computer vision and robotic applications. The workshop also features contributions from researchers involved in traditional theories to affordances, especially from the point of view of psychophysics and neuro-biology. Avenues to aiding research in these fields using techniques from computer vision and cognitive robotics will also be explored. Primary topics addressed by the workshop include the following among others - Affordances in visual perception models - Affordances as visual primitives, common coding features and symbolic cognitive systems - Affordances for object recognition, search, attention modulation, functional scene understanding/ classification - Object functionality analysis - Affordances from appearance and touch based cues - Haptic adjectives - Functional-visual categories for transfer learning - Actions and functions in object perception - Human-object interactions and modeling - Motion-capture data analysis for object categorization - Affordances in human and robot grasping - Robot behavior for affordance learning - Execution of affordances on robots - Affordances to address cognitive and domestic robot applications - Affordance ontologies - Psychophysics of affordances - Neurobiological and cognitive models for affordances The workshop also seeks to address key challenges in robotics with regard to functional form descriptions. While affordances describe the function that each object or entity affords, these in turn define the manipulation schema and interaction modes that robots need to use to work with objects. These functional features, ascertained through vision, haptics and other sensory information also help in categorizing objects, task planning, grasp planning, scene understanding and a number of other robotic tasks. Understanding various challenges in the field and building a common language and framework for communication across varied communities in are the key goals of the proposed workshop. Through the course of the workshop, we also envisage the establishment of a working group for AfNet. An initial version is available online at www.theaffordances.net. We hope the workshop will serve to foster greater collaboration between the affordance communities in various fields. *Paper Submissions* Paper contributions to the workshop are solicited in four different formats - *Conceptual papers* (1 page): Authors are invited to submit original ideas on approaches to address specific problems in the targeted areas of the workshop. While a clear presentation of the proposed approach and the expected results are essential, specifics of implementation and evaluations are outside the scope of this format. This format is intended at exchange and evaluation of ideas prior to implementation/ experimental work as well as to open up collaboration avenues. - *Design papers* (3 pages): Authors submitting design papers are required to address key issues regarding the problem considered with detailed algorithms and preliminary or proof-of-concept results. Detailed evaluations and analyses are outside the scope of this format. This format is intended at addressing late-breaking and work in progress results as well as fostering collaboration between research and engineering groups. - *Experimental papers* (3 pages): Experimental papers are required to present results of experiments and evaluation of previously published algorithms or design frameworks. Details of implementation and exhaustive test case analyses are key to this format. These papers are geared at benchmarking and standardizing previously known approaches. - *Full papers* (5 pages): Full papers must be self-inclusive contributions with a detailed treatment of the problem statement, related work, design methodology, algorithm, test-bed, evaluation, comparative analysis, results and future scope of work. Submission of original and unpublished work is highly encouraged. Since the goal of this workshop is to bring together the various affordance communities, extended versions/ summary reports of recent research published elsewhere, as adapted to the goals of the workshop, will also be accepted. These papers are required to clearly state the relevance to the workshop and the necessary adaptation. The program will be composed of oral as well as Pecha-Kucha style presentations. Each contribution will be reviewed by three reviewers through a single-blind review process. The paper formatting should follow the RSS formatting guidelines (Templates: Word<http://www.roboticsconference.org/paper-template-word.zip> andLaTeX <http://www.roboticsconference.org/paper-template-latex.tar.gz>). All contributions are to be submitted via Microsoft Conference Management Tool <https://cmt.research.microsoft.com/A2014/Default.aspx> in PDF format. Appendices and supplementary text can be submitted as a second PDF, while other materials such as videos (though, preferably as links on vimeo or youtube) as a zipped file. All papers are expected to be self-inclusive and supplementary materials are not guaranteed to be reviewed. Please adhere to the following strict deadlines. In addition to direct acceptance, early submissions may be conditionally accepted, in which case submission of a revised version of the paper based on reviewer comments, prior to the late submission deadline is necessary. The final decision on acceptance of such conditionally accepted papers will be announced along with the decisions for the late submissions. *Important Dates* - Initial submissions (Early): 23:59:59 PDT May 5, 2014 - Notification of acceptance (Early submissions): May 15, 2014 - Initial submissions (Late): 23:59:59 PDT May 27, 2014 - Notification of acceptance (Late submissions): June 5, 2014 - Submission of publication-ready version: June 10, 2014 - Workshop date: July 13, 2014 *Organizers* Karthik Mahesh Varadarajan <http://www.karthikmahesh.com/> (varadarajan(at) acin.tuwien.ac.at), TU Wien Markus Vincze <http://www.acin.tuwien.ac.at/index.php?id=231&L=1> (vincze(at)tuwien.ac.at), TU Wien Trevor Darrell <http://www.eecs.berkeley.edu/~trevor/> (trevor(at) eecs.berkeley.edu) UC. Berkeley Juergen Gall <http://www.vision.ee.ethz.ch/~gallju/>(gall(at)iai.uni-bonn.de), Univ. Bonn *Speakers and Participants* (To be updated) Abhinav Gupta (Affordances in Computer Vision), Carnegie Mellon University Ashutosh Saxena (Affordances in Cognitive Robotics), Cornell University Lisa Oakes (Psychophysics of affordances)*, UC. Davis TBA (Neurobiology of affordances)* *Program Committee* Irving Biederman (USC) Aude Olivia (MIT) Fei-Fei Li (Stanford University) Martha Teghtsoonian (Smith College) Derek Hoiem (UIUC) Barbara Caputo (Univ. of Rome, IDIAP) Song-Chun Zhu (UCLA) Antonis Argyros (FORTH) Tamim Asfour (KIT) Michael Beetz (TUM) Norbert Krueger (Univ. of Southern Denmark) Sven Dickinson (Univ. of Toronto) Diane Pecher (Erasmus Univ. Rotterdam) Aaron Bobick (GeorgiaTech) Jason Carso (UB New York) Juan Carlos Niebles (Universidad del Norte) Tamara Berg (UNC Chapel Hill) Moritz Tenorth (Univ. Bremen) Dejan Pangercic (Robert Bosch) Roozbeh Mottaghi (Stanford) Alireza Fathi (Stanford) Xiaofeng Ren (Amazon) David Fouhey (CMU) Tucker Hermans (Georgia Tech) Tian Lan (Stanford) Amir Roshan Zamir (UCF) Hamed Pirsiavash (MIT) Walterio Mayol-Cuevas (Univ. of Bristol)

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new MATLAB toolbox for Granger causality analysis
by Anil Seth 23 Apr '14

23 Apr '14

Dear all, Lionel Barnett and I are pleased to announce the availability of our wholly new MATLAB toolbox for implementing Granger causality analysis. This new free software is a wholesale revision of my previous ‘GCCA’ toolbox which has been available since 2010 (http://www.ncbi.nlm.nih.gov/pubmed/19961876) and which has enjoyed a wide uptake within the neuroscience community and beyond. Granger causality is a powerful analysis method which can be used to detect directed functional connectivity in stationary time-series data, of the sort often (but not always) found in neuroscience datasets. The new ‘multivariate Granger causality’ ‘MVGC’ toolbox offers a range of enhancements. It easily handles conditional spectral analyses. It requires only estimation of the ‘full’ regression model, avoiding biases inherent in estimation of both full and reduced models. It is accompanied by a fully functional help system integrated into the online MATLAB documentation. And much else besides. The toolbox can be downloaded here: http://www.sussex.ac.uk/sackler/mvgc/ A paper describing the toolbox and the basic concepts and maths underlying Granger causality has been recently published in Journal of Neuroscience Methods: http://www.sciencedirect.com/science/article/pii/S0165027013003701 … which is the appropriate citation for any published work utilizing the software. Preparation of the toolbox was supported by the Sackler Centre for Consciousness Science, which is funded by the Dr. Mortimer and Dame Theresa Sackler Foundation. We hope you find it useful! Best regards Anil Seth and Lionel Barnett ------------------------------------------- Anil K. Seth, D.Phil. Professor of Cognitive and Computational Neuroscience Co-Director, Sackler Centre for Consciousness Science University of Sussex www.anilseth.com<http://www.anilseth.com> a.k.seth(a)sussex.ac.uk<mailto:a.k.seth@sussex.ac.uk>

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DecMeg2014 data analysis competition
by Emanuele Olivetti 22 Apr '14

22 Apr '14

DecMeg2014 data analysis competition Biomag 2014 Decoding Challenge - Brain Decoding Across Subjects https://www.kaggle.com/c/decoding-the-human-brain Decoding mental states from functional neuroimaging data is a data analysis paradigm adopted both in neuroscience studies and in brain-computer interface applications. Decoding means determining, from the recorded brain activity, what stimulus was provided to a subject. In this competition, a large number of trials, from a face vs. scrambled face visual task, are available from multiple subjects. The brain activity was recorded by means of magnetoencephalography (MEG). MEG recordings from various subjects and the category of the associated visual stimuli are given to the participants of the competition in order to train their prediction algorithms. With their algorithms, the participants will have to predict the category of the stimulus of a different set of MEG recordings, from other subjects. Each submission to the competition will be scored according to the accuracy of prediction. Decoding across subjects is a difficult task because of the variability in head shape, cortical folding and functional organisation. For MEG data, the literature on decoding across subjects is still in early stages and this competition aims at raising the awareness about this complex scientific problem. This competition is associated with the the 19th International Conference on Biomagnetism, Biomag 2014, Halifax (Canada), August 24-28, 2014. The competition begins: April 21st, 2014. The competition ends: July 27th, 2014. Prizes: 1st 3,000 USD, 2nd 1,500 USD, 3rd 500 USD. Organizers: Emanuele Olivetti, Seyed Mostafa Kia and Paolo Avesani (NeuroInformatics Lab, Bruno Kessler Foundation and University of Trento, IT), e-mail: decmeg2014(a)list.fbk.eu . Scientific steering committee: Ole Jensen (Donders Institute, NL), Nathan Weisz (University of Trento, IT), Richard Henson (MRC/CBU, UK) and Alexandre Gramfort (Telecom ParisTech, CNRS, CEA / Neurospin). We would also like to thank Daniel Wakeman (Martinos Center, MGH, USA). The awards for this competition are funded by Elekta Oy, MEG International Services Ltd (MISL), Fondazione Bruno Kessler and Besa Gmbh. Relevant links: - competition website: https://www.kaggle.com/c/decoding-the-human-brain - Biomag 2014: http://www.biomag2014.org - NeuroInformatics Lab: http://nilab.fbk.eu - Elekta Oy: http://www.elekta.com - MISL (CTF MEG): http://www.ctfmeg.com - Fondazione Bruno Kessler: http://www.fbk.eu - Besa GmbH: http://www.besa.de Please feel free to forward this message to your colleagues or contacts who might be interested in this competition.

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NEURON Summer Course deadline approaching
by Ted Carnevale 22 Apr '14

22 Apr '14

The early registration deadline for the NEURON Summer Course is Friday, May 9, less than three weeks from today. Applicants who sign up by that date are eligible for reduced registration fees. NEURON Fundamentals June 21-24 This course shows how to model individual neurons and networks of neurons, and introduces parallel simulation. The early registration fee is $1050, but after May 9 registration goes up to $1200. Parallel Simulation with NEURON June 25-26 This is for users who are already familiar with NEURON and now need to parallelize an existing model or create a new model that will run on parallel hardware. The early registration fee is $650, but after May 9 it goes up to $750. Sign up for both courses by May 9 and pay only $1600, or wait until May 10 or later and pay $1800. Registration is limited, and the final registration deadline is Friday, May 30, 2014. For more information about these courses see http://www.neuron.yale.edu/neuron/courses or contact Ted Carnevale ted dot carnevale at yale edu 203-494-7381

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CoSMo 2014: application deadline approaching!
by Gunnar Blohm 22 Apr '14

22 Apr '14

Just a quick reminder that the application deadline for the summer school on Computational Sensory-Motor Neuroscience (CoSMo 2014) is approaching fast: Apr 28, 2014!!! http://www.compneurosci.com/CoSMo/ Best Gunnar Blohm, Konrad Körding, Paul Schrater -- ------------------------------------------------------- Dr. Gunnar BLOHM Assistant Professor in Computational Neuroscience Centre for Neuroscience Studies, Departments of Biomedical and Molecular Sciences, Mathematics & Statistics, and Psychology, School of Computing, and Canadian Action and Perception Network (CAPnet) Queen’s University 18, Stuart Street Kingston, Ontario, Canada, K7L 3N6 Tel: (613) 533-3385 Fax: (613) 533-6840 Email: Gunnar.Blohm(a)QueensU.ca Web: http://www.compneurosci.com/

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Advanced Statistics and Data Mining Summer School (Madrid) - Early registration deadline
by asdm＠fi.upm.es 22 Apr '14

22 Apr '14

Dear colleagues, We would like to remind you that the early registration period for the Advanced Statistics and Data Mining Summer School will finish on June 2nd. The summer school will be held in Madrid, from June 23rd to July 4th. This year's programme comprises 12 courses and runs for 2 weeks. Attendees may register in each course independently. Extended information on course programmes, price, venue, accommodation and transport is available at the school's website: http://www.dia.fi.upm.es/ASDM Please, send this information to your colleagues, students, and whoever you think may find it interesting. Best regards, Pedro Larranaga, Concha Bielza, Bojan Mihaljevic and Laura Anton-Sanchez. -- School coordinators. *** List of courses and brief description *** * Week 1 (June 23rd - June 27th, 2014) * 1st session: 9:30 - 12:30 Course 1: Bayesian Networks (15 h) Basics of Bayesian networks. Inference in Bayesian networks. Learning Bayesian networks from data. Real applications. Course 2: Time Series(15 h) Basic concepts in time series. Descriptive methods for time series. Linear models for time series. Extensions. 2nd session: 13:30 - 16:30 Course 3: Supervised Pattern Recognition (15 h) Introduction. Assessing the performance of supervised classification algorithms. Preprocessing. Classification techniques. Combining multiple classifiers. Comparing supervised classification algorithms. Course 4: Bayesian Inference (15 h) Introduction: Bayesian basics. Conjugate models. MCMC and other simulation methods. Regression and Hierarchical models. Model selection. 3rd session: 17:00 - 20:00 Course 5: Neural Networks and Deep Learning (15 h) Introduction. Training algorithms. Learning and Optimization. MLPs in practice. Deep Networks. Course 6: Feature Subset Selection (15 h) Introduction. Filter approaches. Wrapper methods. Embedded methods. Advanced topics. Practical session. * Week 2 (June 30th - July 4th, 2014) * 1st session: 9:30 - 12:30 Course 7: Statistical Inference(15 h) Introduction. Some basic statistical test. Multiple testing. Introduction to bootstrap methods. Introduction to Robust Statistics. Course 8: Bayesian Classifiers (15 h) Discrete predictors. Gaussian Bayesian networks-based classifiers. Other Bayesian classifiers. Bayesian classifiers for: positive and unlabeled data, semi-supervised learning, data streams, temporal data. 2nd session: 13:30 - 16:30 Course 9: Text Mining (15 h) Introduction. Fundamentals. Language Modeling. Text Classification. Information Extraction. Course 10: Unsupervised Pattern Recognition (15 h) Introduction to clustering. Data exploration and preparation. Prototype-based clustering. Density-based clustering. Graph-based clustering. Cluster evaluation. Miscellanea. Conclusions and final advise. 3rd session: 17:00 - 20:00 Course 11: Support Vector Machines and Convex Optimization (15 h) Introduction. SVM models. SVM learning algorithms. Convex non differentiable optimization. Course 12: Hidden Markov Models (15 h) Introduction. Discrete Hidden Markov Models. Basic algorithms for Hidden Markov Models. Semicontinuous Hidden Markov Models. Continuous Hidden Markov Models. Unit selection and clustering. Speaker and Environment Adaptation for HMMs. Other applications of HMMs.

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2nd call for papers - 2014 IEEE International Workshop on Machine Learning for Signal Processing (MLSP)
by 2014 IEEE International Workshop on Machine Learning fo Signal Processing 22 Apr '14

22 Apr '14

2014 IEEE International Workshop on Machine Learning for Signal Processing (MLSP) September 21-24, 2014 Reims, France http://mlsp2014.conwiz.dk CALL FOR PAPERS The 24th MLSP workshop in the series of workshops organized by the IEEE Signal Processing Society MLSP Technical Committee will present the most recent and exciting advances in machine learning for signal processing through keynote talks, tutorials as well as special and regular single-track sessions. Prospective authors are invited to submit papers on relevant algorithms and applications including, but not limited to: - Learning theory and techniques - Graphical models and kernel methods - Data-driven adaptive systems and models - Pattern recognition and classification - Distributed, Bayesian, subspace/manifold and sparsity-aware learning - Multiset data analysis and multimodal data fusion - Perceptual signal processing in audio, image and video - Cognitive information processing - Multichannel adaptive and nonlinear signal processing - Applications, including: speech and audio, image and video, music, biomedical signals and images; communications; bioinformatics; biometrics, computational intelligence, genomic signals and sequences; social networks; games, and smart grid. DATA ANALYSIS AND SIGNAL PROCESSING COMPETITION Data Analysis and Signal Processing Competition is being organized in conjunction with the workshop. The goal of the competition is to advance the current state-of-the-art in theoretical and practical aspects of signal processing domains. The problems are selected to reflect current trends, evaluate existing approaches on common benchmarks, and identify critical new areas of research. Winners will be announced and awards given at the workshop. BEST STUDENT AWARD The MLSP Best Student Paper Award will be granted to the best overall paper for which a student is the principal author and presenter. This author must be a registered student at the time of paper submission to be eligible for this award. The award will be presented during the conference and consists of a honorarium (to be divided equally between all student authors of the paper), and a certificate for each such author. The award will be selected by a subcommittee of the program committee. The selection is based on the quality, originality, and clarity of the submission. PAPER SUBMISSION Prospective authors are invited to submit a double column paper of up to six pages using the electronic submission procedure at http://mlsp2014.conwiz.dk/paper_submission.htm Accepted papers will be published on memory sticks to be distributed at the workshop. The presented papers will be published in and indexed by IEEE Xplore. SCHEDULE: - Submission of full paper: May 5, 2014 - Notification of acceptance: June 27, 2014 - Advance registration before: July 25, 2014 - Camera-ready paper: July 25, 2014 ORGANIZING COMMITTEE: General Chair Mamadou Mboup Contact general chair at mlsp2014-chair(a)conwiz.dk Program Chairs Tülay Adali Eric Moreau Contact program chairs at mlsp2014-programchairs(a)conwiz.dk Data Competition Chair Vince Calhoun Special Session Chair Jean-Yves Tourneret Publicity Chair Marc Van Hulle Web and Publication Chair Jan Larsen Kevin Guelton Local Arrangement Chairs Valeriu Vrabie Hassan Fenniri

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Endeavour Scholarships and Fellowships
by Naotsugu Tsuchiya 22 Apr '14

22 Apr '14

Dear all, The Australian government is offering Endeavour Scholarships and Fellowships https://aei.gov.au/scholarships-and-fellowships/international-applicants/pa… to those competitive international students and postdocs to visit and conduct short-term research in Australia. Please see the web site if you are interested. In my lab, we are looking for students/postdocs who are proficient in Matlab (and preferably signal processing and/or information theory as well) and interested in 1) application of the integrated information theory of consciosness to the real neuronal data, 2) analysis of intracranial recording data (using decoding, cross-frequency coupling etc) to understand the neuronal basis of consciousness. Please send me <naotsugu.tsuchiya(a)monash.edu> your CV if you are interested. Endeavour Awards will be closing 30 June 2013. Regards Nao Tsuchiya -- ------------------------------------------------------------------------- Nao (Naotsugu) Tsuchiya, Ph.D. 1. Associate Professor School of Psychological Sciences Faculty of Medicine, Nursing and Health Sciences, Monash University 2. ARC Future Fellow homepage: http://users.monash.edu.au/~naotsugt/Tsuchiya_Labs_Homepage/Main.html

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NIPS 2014 Call for Papers
by Chris Hiestand 22 Apr '14

22 Apr '14

Neural Information Processing Systems Conference and Workshops December 8-13, 2014 Montreal Convention Center, Montreal, Canada Deadline for Paper Submissions: Friday, June 6, 2014, 11 pm Universal Time (4 pm Pacific Daylight Time). Submit at: https://cmt.research.microsoft.com/NIPS2014/ Submissions are solicited for the Twenty-Eigth Annual Conference on Neural Information Processing Systems, an interdisciplinary conference that brings together researchers in all aspects of neural and statistical information processing and computation, and their applications. The conference is a highly selective, single track meeting that includes oral and poster presentations of refereed papers as well as invited talks. The 2014 conference will be held on December 8-11 at Montreal Convention Center, Montreal, Canada. One day of tutorials (December 8) will precede the main conference, and two days of workshops (December 12-13) will follow it at the same location. Complete details: http://nips.cc/Conferences/2014/CallForPapers

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