Snowbird, Utah, April 4-7, 2000


TUESDAY April 4th
4:00 Registration - outside Ballroom 1
5:30 Dinner - Golden Cliff
7:00 Oral Session 1 - Ballroom 1
7:00 David Cohn and Huan Chang, (Just Research and CMU)
Learning the Structure in Document Bases
7:20 Andrew McCallum, Dayne Frietag, Fernando Pereira, (CMU and AT&T)
Maximum Entropy Markov Models for Information Extraction and Segmentation
7:40 Volker Tresp (Siemens )
The Generalized Bayesian Committee Machine
8:20 Sam Roweis and Geoff Hinton (Gatsby Unit, University College London)
One Microphone Source Separation
8:40 David Heckerman, Eric Horvitz, John Platt, Robert Rounthwaite, Christopher Meek, Susan Dumais, David Maxwell Chickering, and Andy Jacobs (Microsoft Research )
Adaptive Filtering of Junk Email

7:00 Breakfast - Golden Cliff
8:00 Oral Session 1 - Ballroom 1
* 8:00 Craig Boutillier (University of British Columbia)
Factored POMDPs and Belief State Approximation
8:40 Uri Lerner, Daphne Koller, Ronald Parr (Stanford University )
Tracking in hybrid dynamic Bayesian networks
9:00 Yair Weiss, William Freeman (UC Berkeley, and Mitsubishi Electric Research Lab)
On the fixed points of the max-product algorithm
9:20 Break
* 9:40 Geoffrey Hinton (Gatsby Unit, University College London)
Training Products of Experts by Maximizing Contrastive Likelihood
10:20 Daniel Lee and Sebastian Seung (Bell Labs and MIT)
Hidden nonnegative Variable Models for Dynamic Data
10:40 Sanjoy Dasgupta (UC Berkeley )
Random Projection as a tool for learning high-dimensional mixture models
11:00 Sebastian Thrun (Carnegie Mellon University )
Particle Filters for Mobile Robot Navigation
11:20Lunch - Golden Cliff
5:30Dinner - Golden Cliff
7:00Poster Session A
8:00Poster Session B

THURSDAY April 6th
7:00 Breakfast - Golden Cliff
8:00 Oral Session 1 - Ballroom 1
* 8:00 John Lafferty (Carnegie Mellon University )
Learning Language Models for Information Retrieval
8:40 Dale Schuurmans and Finnegan Southey (University of Waterloo )
An adaptive regularization method for supervised learning
9:00 Leon Bottou, Yann LeCun, Vladimir Vapnik (AT&T Labs - Research)
Predicting Learning Curves without the Ground Truth Hypothesis
9:20 Break
* 9:40 Shun-Ichi Amari (U. of Tokyo - Riken)
Information Geometry of Multilayer Perceptrons
10:20 Lyle H. Ungar, Greg Grudic (University of Pennsylvania, )
Boundary Localized Reinforcement Learning for Robotics
10:40 Eric B. Baum (NEC Research Institute)
Toward Powerful Reinforcement Learning
11:00 Satinder Singh, Michael Kearns, Marilyn Walker, and Diane Litman (AT&T Labs - Research)
Automatic Optimization of Dialogue Policy via Reinforcement Learning
11:20Lunch - Golden Cliff
5:30Dinner - Golden Cliff
7:00Poster Session C
8:00Poster Session D

FRIDAY April 7th
7:00 Breakfast - Golden Cliff
8:00 Oral Session 1 - Ballroom 1
* 8:00 Trevor Hastie (Stanford University )
Gene Shaving: a new class of clustering methods for expression arrays
8:40 Rich Caruana, David Cohn, Andrew McCallurn (Just Research and CMU)
Semi-supervised Clustering with User Feedback
9:00 Eric Brill (Microsoft Research )
Regular Expression Learning for Natural Language Processing
9:20 Break
* 9:40 Ehud Kalai (Northwestern University)
Rational Interactive Learning
10:20 Vladimir Pavlovic and James M. Rehg (Compaq)
Learning Switching Linear System Models of Figure Motion from Image Sequences
10:40 Lars Schwabe, Peter Adorjan, and Klaus Obermayer (Technische Universitat Berlin, )
The Principle of 'Dynamic Coding'
11:00 D. Ormoneit, H. Sidenbladh, M. J. Black, and T. Hastie (Stanford University, and Xerox Parc)
Stochastic Modeling and Tracking of Human Motion
11:20Lunch - Golden Cliff
5:30Banquet - Golden Cliff
7:40 Oral Session 1 - Ballroom 1
7:40 Peter N. Belhumeur Athinodoros S. Georghiades (Yale University )
A Photometric Method for Synthesizing Photorealistic Pictures Under Changes in Viewpoint and Lighting
8:00 Erik Winfree (Caltech )
Synthetic Transcriptional Networks and Neural Networks
8:20 Break
* 8:40 Deborah Gordon (Stanford)
The Organization of Work in Ant Colonies
9:00 Adjourn