http://www.cs.cmu.edu/Web/Groups/NIPS
Neural Information Processing Systems -- Natural and Synthetic
Monday November 29 - Saturday December 4, 1999
Denver, Colorado
Conference Program available at:
http://www.cs.cmu.edu/Groups/NIPS/NIPS99/program.txt
This is the thirteenth meeting of an interdisciplinary conference which brings
together cognitive scientists, computer scientists, engineers, neuroscientists,
physicists, 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 (November 29), and following it, there will be two days of focused
workshops on topical issues at a Breckenridge (December 3-4). Major categories
of accepted papers include the following topics:
Algorithms and Architectures: supervised and unsupervised learning algorithms,
model selection algorithms, active learning algorithms, feedforward and
recurrent network architectures, localized basis functions, mixture models,
belief networks, graphical models, Gaussian processes, factor analysis,
topographic maps, combinatorial optimization, hybrid symbolic-subsymbolic
systems.
Applications: handwriting recognition, sequence analysis, expert systems,
fault diagnosis, medical diagnosis, analysis of medical images, data analysis,
database mining, information retrieval, network traffic, music processing,
time-series prediction, financial analysis.
Cognitive Science/Artificial Intelligence: perception and psychophysics,
neuropsychology, cognitive neuroscience, development, conditioning, human
learning and memory, attention, language, natural language, reasoning, spatial
cognition, emotional cognition, conceptual representation, neurophilosophy,
problem solving and planning.
Implementations: analog and digital VLSI, optical neurocomputing systems, novel
neurodevices, computational sensors and actuators, simulation tools.
Neuroscience: neural encoding, spiking neurons, synchronicity, sensory
processing, systems neurophysiology, neuronal development, synaptic plasticity,
neuromodulation, dendritic computation, channel dynamics, experimental data
relevant to computational issues.
Reinforcement Learning and Control: exploration, planning, navigation,
Q-learning, TD-learning, state estimation, dynamic programming, robotic motor
control, process control, Markov decision processes.
Speech and Signal Processing: speech recognition, speech coding, speech
synthesis, auditory scene analysis, source separation, applications of hidden
Markov models to signal processing, models of human speech perception, auditory
modeling and psychoacoustics.
Theory: computational learning theory, statistical physics of learning,
information theory, prediction and generalization, regularization, Boltzmann
machines, Helmholtz machines, decision trees, support vector machines, online
learning, dynamics of learning algorithms, approximation and estimation theory,
learning of dynamical systems, complexity theory.
Visual Processing: image processing, image coding, object recognition, visual
psychophysics, stereopsis, motion detection and tracking.
INVITED SPEAKERS:
http://www.cs.cmu.edu/Groups/NIPS/NIPS99/Invited.html
Edward H. Adelson (banquet), Department of Brain and Cognitive
Sciences and Artificial Intelligence Laboratory, Massachusetts
Institute of Technology "Lightness Perception and Lightness Illusions"
Donald K. Eddington, Harvard Medical School and Cochlear Implant
Research Laboratory, Massachusetts Eye and Ear Infirmary "Sound
Processing for Cochlear Implants: Rationale, Implementation and
Patient Performance"
Bard Ermentrout, Department of Mathematics, University of Pittsburgh
"Spatio-temporal Computations in Biological Neural Nets"
Jessica Hodgins, College of Computing, Georgia Institute of Technology
"Animation of Human Motion"
Andrew W. Lo, Sloan School of Management and Laboratory for Financial
Engineering, Massachusetts Institute of Technology "How Anomalous Are
Financial Time Series Anomalies?"
J. Anthony Movshon, Howard Hughes Medical Institute, New York
University "Deconstructing Synchrony"
TUTORIALS: (November 30th)
http://www.cs.cmu.edu/Groups/NIPS/NIPS99/Tutorials.html
"Data Mining and Scalability to Large Databases", Usama Fayyad
and Heikki Mannila, Microsoft Research
"Probabilistic Models for Unsupervised Learning", Zoubin
Ghahramani and Sam Roweis, University College London
"Probabilistic Language Models: 100 Years and Counting", John
Lafferty, Carnegie Mellon University
"Neural Computation: from Software Simulation to Hardware
Emulation", Rodney Douglas, UNIZ/ETH Zurich
"WARNING: Data-Snooping May Be Dangerous To Your Wealth!", Andrew
Lo, MIT
"On-line Learning and Relative Loss Bounds", Manfred Warmuth,
University of California Santa Cruz
WORKSHOPS: (December 2-4)
http://www.cs.cmu.edu/Groups/NIPS/NIPS99/Workshops/
"Learning with Support Vectors: Theory and Applications"
"MCMC Methods for Machine Learning"
"Using Unlabeled Data for Supervised Learning"
"Complexity and Neural Computation: Average and Worst Case"
"Advanced Mean Field Methods"
"Overcomplete Representations and Nonlinear Approaches to ICA"
"Geometric Methods in Learning"
"Statistical Learning in High Dimensions"
"Learning Relational Data Representation"
"Visual Selection Mechanisms"
"Adaptive Computational Models and Short Time Perceptual Learning"
"Neural Mechanisms of Music Processing"
"Neuronal Response Variability - Curse or Blessing?"
"Computational Brain Imaging: Beyond Modern Phrenology"
"Spike Timing and Synaptic Plasticity"
"Neural Networks and Human Movement Simulation: New Frontiers"
For general inquiries or requests for registration material
E-mail: nipsinfo@salk.edu or Fax: (619) 587-0417
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