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                  CALL FOR PAPERS
Neural Information Processing Systems, Natural and Synthetic
      Monday, December 8 - Saturday December 13, 2003
            Vancouver, British Columbia, Canada
                    www.nips.cc
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Submissions are solicited for the seventeenth meeting of an
interdisciplinary conference which brings together
researchers interested in all aspects of neural and
statistical computation.  The conference will include invited
talks as well as oral and poster presentations of refereed
papers.  It is single track and highly selective.  Preceding
the main conference will be one day of tutorials (December
8), and following it will be two days of workshops at
Whistler/Blackcomb ski resort (December 12-13).

INVITED SPEAKERS: Anders Dale, Harvard University: Relating
Brain Imaging Signals to Biophysical Models of Neuronal
Circuits; Paul Ekman, UC San Francisco: About Face: What We
Have Learned Through Measuring Facial Movements; Michale Fee,
Bell Labs, Lucent Technologies: Time and Sequence in the
Brain: Insights from a Songbird; Marc Mezard, Universite de
Paris Sud: Analytic and Algorithmic Solutions of Random
Satisfiability Problems; Elissa Newport, University of
Rochester, Statistical Language Learning in Human Infants and
Adults; David Salesin, University of Washington and Microsoft
Research: The Need for Machine Learning in Computer Graphics.

TUTORIAL SPEAKERS: Stephen Boyd, Stanford University: Convex
Optimization and Applications; David Karger, MIT: Algorithmic
Tools Applied to Learning and Inference Problems; Daniel
Lee, University of Pennsylvania: Learning in Sensorimotor
Systems; David Lowe, University of British Columbia:
Real-time Object Recognition using Invariant Local Image
Features; Klaus-Robert Mueller, Fraunhofer FIRST: Towards
Brain Computer Interfacing; Zach Mainen, Cold Spring Harbor
Laboratory: Neural Coding and the Olfactory System;

SUBMISSIONS: Papers are solicited in all areas of neural and
statistical computation, including (but not limited to) the
following:

 o Algorithms and Architectures: statistical learning
   algorithms, neural networks, kernel methods, graphical
   models, Gaussian processes, independent component
   analysis, model selection, combinatorial optimization.

 o Applications: innovative applications or fielded systems
   that use machine learning, including systems for time
   series prediction, bioinformatics, text/web analysis,
   multimedia processing, and robotics.

 o Brain Imaging: neuroimaging, cognitive neuroscience, EEG
   (electroencephalogram), ERP (event related potentials),
   MEG (magnetoencephalogram), fMRI (functional magnetic
   resonance imaging), brain mapping, brain segmentation.

 o Cognitive Science and Artificial Intelligence:
   theoretical, computational, or experimental studies of
   perception, psychophysics, human or animal learning,
   memory, reasoning, problem solving, language, and
   neuropsychology.

 o Control and Reinforcement Learning: decision and control,
   exploration, planning, navigation, Markov decision
   processes, game-playing, multi-agent coordination,
   computational models of classical and operant
   conditioning.

 o Emerging Technologies: analog and digital VLSI,
   neuromorphic engineering, computational sensors and
   actuators, microrobotics, bioMEMS, neural prostheses,
   photonics, molecular and quantum computing.

 o Learning Theory: generalization and regularization,
   information theory, statistical physics of learning,
   Bayesian methods, approximation bounds, online learning
   and dynamics.

 o Neuroscience: theoretical and experimental studies of
   processing and transmission of information in biological
   neurons and networks, including spike train generation,
   synaptic modulation, plasticity and adaptation.

 o Speech and Signal Processing: recognition, coding,
   synthesis, denoising, segmentation, source separation,
   auditory perception, psychoacoustics, dynamical systems,
   recurrent networks, Markov models.

 o Visual Processing: image processing and coding,
   segmentation, object detection and recognition, motion
   detection and tracking, visual psychophysics, visual scene
   analysis and interpretation.

 o Demonstrations: Authors wishing to submit to the
   demonstration track should consult the conference web
   site.

REVIEW CRITERIA: Submissions will be refereed on the basis of
technical quality, novelty, significance, and clarity.
Authors new to NIPS are particularly encouraged to
submit. There will be an opportunity after the meeting to
revise accepted manuscripts.

PAPER FORMAT: Submissions may be up to eight 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 violating these guidelines will not
be considered.  Templates will be posted at the NIPS Website
nips.cc.

SUBMISSION INSTRUCTIONS: NIPS accepts only electronic
submissions in postscript and PDF format.  The conference web
site will accept electronic submissions from May 19, 2003
until midnight, June 6, 2003, Pacific daylight time.

ORGANIZING COMMITTEE: General Chair, Sebastian Thrun,
Carnegie Mellon University; Program Chair, Lawrence Saul,
University of Pennsylvania; Tutorials Chair, Sam Roweis,
University of Toronto; Workshops Co-chairs, Robert Jacobs,
University of Rochester, Satinder Singh Baveja, University of
Michigan; Demonstrations Chairs, Shih-Chii Liu,
ETH/University of Zurich, Tobi Delbruck, ETH/University of
Zurich; Publications Chair, Bernhard Schoelkopf, Max Planck
Gesellschaft Tuebingen; Publicity Chair, Klaus Robert
Mueller, Fraunhofer FIRST; Online Proceedings Chair, Andrew
McCallum, University of Massachusetts Amherst; Volunteers
Chair, Dale Schuurmans, University of Waterloo.

PROGRAM COMMITTEE: Lawrence Saul (Chair), University of
Pennsylvania; Peter Bartlett, UC Berkeley; Samy Bengio,
IDIAP; Chris Burges, Microsoft Research; Rich Caruana,
Cornell University; Ralph Etienne-Cummings, Johns Hopkins
University and University of Maryland, College Park; Geoff
Hinton, University of Toronto; John Lafferty, Carnegie Mellon
University; Mike Lewicki, Carnegie Mellon University; Michael
Littman, Rutgers University; Andrew McCallum, University of
Massachusetts Amherst; Rajesh Rao, University of Washington;
Jianbo Shi, University of Pennsylvania; Richard Shiffrin,
Indiana University; Yoram Singer, Hebrew University;
Alexander Smola, Australian National University; Martin
Wainwright, UC Berkeley.

      PAPERS MUST BE RECEIVED BY JUNE 6, 2003
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