VisionScienceList: CALL FOR PAPERS -- NIPS*2001

From: Bill Freeman (
Date: Fri May 25 2001 - 03:20:09 PDT

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           Neural Information Processing Systems
                  Natural and Synthetic
           Monday, Dec. 3 -- Saturday, Dec. 8, 2001
           Vancouver, British Columbia, Canada
                  Whistler Ski Resort

    This is the fifteenth meeting of an interdisciplinary conference which
    brings together cognitive scientists, computer scientists, engineers,
    neuroscientists, physicists, statisticians, and mathematicians
    interested in all aspects of neural processing and computation. The
    conference will include invited talks as well as oral and poster
    presentations of refereed papers. The conference is single track and
    is highly selective. Preceding the main session, there will be one
    day of tutorial presentations (Dec. 3), and following it there will be
    two days of focused workshops on topical issues at Whistler Ski Resort
    (Dec. 7-8). Invited speakers this year will be:

    Barbara Finlay (Departments of Psychology, and Neurobiology and Behavior,
       Cornell University)
    Alison Gopnik (Department of Psychology, University of
       California at Berkeley)
    Jon M. Kleinberg (Department of Computer Science, Cornell University)
    Shihab Shamma (Department of Electrical Engineering University of Maryland)
    Judea Pearl (Department of Computer Science, UCLA)
    Tom Knight (Artificial Intelligence Laboratory, MIT)

    Major categories for paper submission, with example subcategories (by
    no means exhaustive), are listed below. (For this vision posting,
    visual processing is listed first, then alphabetically):

    Visual Processing: image processing, image coding, object recognition,
    face recognition, visual feature detection, visual psychophysics,
    stereopsis, optic flow algorithms, motion detection and tracking,
    spatial representations, spatial attention, scene analysis, visual
    search, visuo-spatial working memory.

    Algorithms and Architectures: supervised and unsupervised learning
    algorithms, feedforward and recurrent network architectures, kernel
    methods, committee models, graphical models, support vector machines,
    Gaussian processes, decision trees, factor analysis, independent
    component analysis, model selection algorithms, combinatorial
    optimization, hybrid symbolic-subsymbolic systems.

    Applications: innovative applications of neural computation including
    data mining, web and network applications, intrusion and fraud
    detection, bio-informatics, medical diagnosis, handwriting
    recognition, industrial monitoring and control, financial analysis,
    time-series prediction, consumer products, music and video
    applications, animation, virtual environments.

    Cognitive Science/Artificial Intelligence: perception and
    psychophysics, neuropsychology, cognitive neuroscience, development,
    human learning and memory, conditioning, categorization, attention,
    language, reasoning, spatial cognition, emotional cognition,
    neurophilosophy, problem solving and planning.

    Implementations: analog and digital VLSI, neuromorphic engineering,
    microelectromechanical systems, optical systems, vision chips,
    head-eye systems, cochlear implants, roving robots, computational
    sensors and actuators, molecular and quantum computing, novel
    neurodevices, simulation tools.

    Neuroscience: neural encoding, spiking neurons, synchronicity, sensory
    processing, systems neurophysiology, neuronal development, synaptic
    plasticity, neuromodulation, dendritic computation, channel dynamics,
    population codes, temporal codes, spike train analysis, and
    experimental data relevant to computational issues.

    Reinforcement Learning and Control: exploration, planning, navigation,
    computational models of classical and operant conditioning,
    Q-learning, TD-learning, state estimation, dynamic programming,
    robotic motor control, process control, game-playing, Markov decision
    processes, multi-agent cooperative algorithms.

    Speech and Signal Processing: speech recognition, speech coding,
    speech synthesis, speech signal enhancement, auditory scene analysis,
    source separation, applications of hidden Markov models to signal
    processing, models of human speech perception, auditory modeling and

    Theory: computational learning theory, statistical physics of
    learning, information theory, Bayesian methods, prediction and
    generalization, regularization, online learning (stochastic
    approximation), dynamics of learning, approximation and estimation
    theory, complexity theory.


    Review Criteria: All submitted papers will be thoroughly refereed on
    the basis of technical quality, significance, and clarity. Novelty of
    the work is also a strong consideration in paper selection, but to
    encourage interdisciplinary contributions, we will consider work which
    has been submitted or presented in part elsewhere, if it is unlikely
    to have been seen by the NIPS audience. Authors new to NIPS are
    strongly encouraged to submit their work, and will be given preference
    for oral presentations. Authors should not be dissuaded from
    submitting recent work, as there will be an opportunity after the
    meeting to revise accepted manuscripts before submitting a final
    camera-ready copy for the proceedings.

    Paper Format: Submitted papers may be up to seven pages in length,
    including figures and references, using a font no smaller than 10
    point. Text is to be confined within a 8.25in by 5in rectangle.
    Submissions failing to follow these guidelines will not be considered.
    Authors are required to use the NIPS LaTeX style files obtainable from
    the web page listed below. The style files are unchanged from

    Submission Instructions: NIPS accepts only electronic submissions.
    Full submission instructions will be available at the web site given
    below. You will be asked to enter paper title, names of all authors,
    category, oral/poster preference, and contact author data (name, full
    address, telephone, fax, and email). You will upload your manuscript from
    the same page. We will accept postscript and PDF documents, but
    we prefer postscript. The electronic submission page will be
    available on June 6, 2001

    Submission Deadline:

    PACIFIC DAYLIGHT TIME (08:00 GMT JUNE 21, 2001).

    The LaTeX style files for NIPS, the Electronic Submission Page, and
    other conference information are available on the World Wide Web at

    For general inquiries send e-mail to

    NIPS*2001 Organizing Committee:
    General Chair, Tom Dietterich, Oregon State University;
    Program Chair, Sue Becker, McMaster University;
    Publications Chair, Zoubin Ghahramani, University College London;
    Tutorial Chair, Yoshua Bengio, University of Montreal;
    Workshops Co-Chairs, Virginia de Sa, Sloan Center for Theoretical Neurobiology,
              Barak Pearlmutter, University of New Mexico;
    Publicity Chair, Richard Zemel, University of Toronto;
    Volunteer Coordinator, Sidney Fels, University of British Columbia;
    Treasurer, Bartlett Mel, University of Southern California;
    Web Masters, Alex Gray, Carnegie Mellon University,
                 Xin Wang, Oregon State University;
    Government Liaison, Gary Blasdel, Harvard Medical School;
    Contracts, Steve Hanson, Rutgers University,
    Scott Kirkpatrick, IBM, Gerry Tesauro, IBM.

    NIPS*2001 Program Committee:
    Sue Becker, McMaster University (chair);
    Gert Cauwenberghs, Johns Hopkins University;
    Bill Freeman, Mitsubishi Electric Research Lab;
    Thomas Hofmann, Brown University;
    Dan Lee, Bell Laboratories, Lucent Technologies;
    Sridhar Mahadevan, Michigan State University;
    Marina Meila-Predoviciu, University of Washington;
    Klaus Mueller, GMD First, Berlin;
    Klaus Obermayer, TU Berlin;
    Sam Roweis, Gatsby Computational Neuroscience Unit, UCL;
    John Shawe-Taylor, Royal Holloway, University of London;
    Josh Tenenbaum, Stanford University;
    Volker Tresp, Siemens, Munich;
    Richard Zemel, University of Toronto.


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