Snowbird, Utah, April 1-4, 2003

PROGRAM

TUESDAY April 1st
4:00 Registration - outside Ballroom 1
5:30 Dinner - Golden Cliff
7:00 Oral Session 1 - Ballroom 1
7:00 T. Hofmann (Brown University), I. Tsochantaridis (Brown University), and Yasemin Altun (Brown University)
Learning Mappings to Discrete Output Spaces via Joint Feature Maps
7:20 H. Chipman (U. Waterloo), E. George (U. Pennsylvania), R. McCulloch (U. Chicago)
BART: Bayesian Additive Regression Trees
7:40 G. Harik, N. Shazeer
A Large Hierarchical Latent Variable Model For Text Generation
8:00 Break
8:20 Peter N.Yianilos
Metric Learning, Winnow, Virtual Variables, and the Record Linkage Problem
8:40 Michael Arnold, Terrence Sejnowski (Salk), Dan Hammertrom, and Marwan Jabri (OGI)
Intergrating an internal model into a system with dopamine-like reinforcement learning
9:00 Klaus Pawelzik, David Rotermund, and Udo Ernst (Univ. Bremen, Germany)
Building representations spike by spike
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WEDNESDAY April 2nd
7:00 Breakfast - Golden Cliff
8:00 Oral Session 2 - Ballroom 1
8:00 Adam Arkin [Patrick Flaherty, Guri Giaeve, Michael Jordan, and Adam Arkin (Berkeley)]
Graphical Model Based Yeast Haploinsufficiency Profiling for Determining Drug Mechanisms and Interactions
8:40 J.S. Yedidia (MERL)
Electronic Circuits that "Solve" Factor Graphs
9:00 Bar-Joseph, Z. (MIT) and Gerber, G. (MIT) and Gifford, D. (MIT) and Jaakkola, T. (MIT) and Simon, I. (Hebrew U.)
Principled Methods for Analyzing Time Series Gene Expression
9:20 Break
9:40 H. Attias (Microsoft Research)
A New Approach to Planning under Uncertainty
10:00 K. Fukumizu (Institute of Statistical Mathematics), F. Bach (U. California, Berkeley), and M. Jordan (U. California, Berkeley)
Kernel Dimension Reduction for Regression
10:20 Y. Bengio (Montreal), P. Vincent (Montreal), and J-F. Paiement (Montreal)
Learning Eigen-Functions: Links with Spectral Clustering and Kernel PCA
10:40 M. Alex O. Vasilescu (University of Toronto) and Demetri Terzopoulos (New York University)
Learning Multilinear Models of Image Ensembles
11:00 J. R. Movellan, G. Littlewort, I. Fasel, M. Stewart Bartlett
Development, Evaluation and Application of a System for Real Time Fully Automatic Face Finding and Expression Recognition in Video Seequences
11:20 Lunch - Golden Cliff
5:30 Dinner - Golden Cliff
7:00-9:30 Poster Session A
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THURSDAY April 3nd
7:00 Breakfast - Golden Cliff
8:00 Oral Session 3 - Ballroom 1
8:00 Martin J. Wainwright (UC Berkeley) and Michael I. Jordan (UC Berkeley)
Semidefinite relaxations for approximate inference on graphs with cycles
8:20 Y. Qi (MIT) and T. Minka (CMU)
Expectation propagation for adaptive detection and decoding in flat-fading channels
8:40 D. Blei (Berkeley) and M. Jordan (Berkeley)
Modeling annotated data
9:00 Yann LeCun and Leon Bottou (NEC Labs)
Lagrangian Difference Learning
9:20 Break
9:40 Manuela Veloso (CMU)
Dynamic Multi-Robot Coordination in the Presence of Teammates and Adversaries
10:20 R. Grover and H. Durrant-Whyte (The University of Sydney)
Efficient Representations for Learning Unstructured Environments
10:40 J. Ham, D. D. Lee, L. K. Saul (U. Pennsylvania)
Learning high dimensional correspondences from low dimensional manifolds
11:00 S. Thrun (CMU), D. Haehnel (CMU), W. Burgard (U. freiburg)
Modeling Nonrigid Objects from Range Data
11:20 Lunch - Golden Cliff
5:30 Dinner - Golden Cliff
7:00-9:30 Poster Session B
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FRIDAY April 3nd
7:00 Breakfast - Golden Cliff
8:00 Oral Session 4 - Ballroom 1
8:00 Joshua Alspector & Aleksander Kolcz
Incremental Learning for Text Categorization with Non-Stationary Data
8:20 L. Zhang (Boston U), V. Pavlovic (Rutgers U), S. Kasif (Boston U)
Comparative Genomics, Evolution and Error Analysis in HMMs: How Learning Explained Biology
8:40 R. Collobert (Idiap) and S. Bengio (Idiap)
Efficient Gradient Descent: Hessian and Criterion
9:00 Leon Bottou and Yann LeCun (NEC Labs)
On-line learning for large problems
9:20 Break
9:40 Martial Hebert (CMU)
Approaches to Object Recognition in Images
10:20 S. Lazebnik (U. Illinois at Urbana-Champaign), C. Schmid (INRIA Rhone-Alpes), J. Ponce (U. Illinois at Urbana-Champaign)
Representing, Learning, and Recognizing Non-Rigid Textures and Texture Categories
10:40 G. Dorko (INRIA) and C. Schmid (INRIA)
Feature Selection for Object Class Detection
11:00 T. Breuel
A Bayesian Approach to Similarity with Applications to OCR and 3D Object Recognition
11:20 Lunch - Golden Cliff
5:30 Banquet - Golden Cliff
7:30 Oral Session 5
7:30 Jianbo Shi (U. Penn)
Finding Usual Events in Video
7:50 W. Burgard (U Freiburg), D. Haehnel (U Freiburg/CMU), R. Triebel (CMU), and S. Thrun (CMU)
Mapping with Mobile Robots in Dynamic Environments
8:10 Break
8:30 Eric Cosatto, Hans-Peter Graf, Volker Strom (AT&T Labs Research)
Recognizing Patterns of Prosodic Head Movements
8:50 M. Riedmiller (Univ. of Dortmund), A. Merke (Univ. of Dortmund)
Practical Aspects of Cooperative Reinforcement Learning in a Complex Domain
9:10 Closing Remarks (Yann LeCun
9:15 Adjourn