| 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 |