
Proceedings of the
Ninth International Workshop
on Artificial Intelligence and Statistics
January 3-6, 2003, Hyatt Hotel, Key West, Florida
Christopher M. Bishop and Brendan J. Frey (editors)
ISBN 0-9727358-0-1
Society for Artificial Intelligence and Statistics
| [ Introduction ] | [ Papers ] | [ Programme ] | [ Invited Speakers ] | [ Acknowledgments ] |
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Friday 3rd January 2003 Informal reception at 18:00 Saturday 4th January 2003 09:00 09:10 Welcome 09:10 10:00 Invited talk: Geoffrey Hinton 10:00 10:25 Fast Marginal Likelihood Maximisation for Sparse Bayesian Models. Michael Tipping, Anita Faul 10:25 10:50 Coffee 10:50 11:15 Combining Conjugate Direction Methods with Stochastic Approximation of Gradients. Nicol Schraudolph, Thore Graepel 11:15 11:40 Expectation Maximization of Forward Decoding Kernel Machines. Shantanu Chakrabartty, Gert Cauwenberghs 11:40 12:30 Invited talk: Zoubin Ghahramani 12:30 13:30 Lunch 13:30 19:00 Informal Discussion/Free Time for own activities 19:00 20:00 Dinner Break 20:00 20:50 Invited talk: Bill Freeman 20:50 21:15 Generalized belief propagation for approximate inference in hybrid Bayesian networks. Tom Heskes, Onno Zoeter 21:15 21:40 Tree-reweighted belief propagation algorithms and approximate ML estimation by pseudo-moment matching. Martin Wainwright, Tommmi Jaakkola, Alan Willsky 21:40 22:05 Model Averaging with Bayesian Network Classifiers. Denver Dash, Greg Cooper Sunday 5th January 2003 09:00 09:50 Invited talk: David Haussler 09:50 10:20 Coffee 10:20 10:45 Fast Forward Selection to Speed Up Sparse Gaussian Process Regression. Matthias Seeger, Christopher K.I. Williams 10:45 11:10 On Improving the Efficiency of the Iterative Proportional Fitting Procedure. Yee Whye Teh, Max Welling 11:10 11:35 Rapid Evaluation of Multiple Density Models. Alexander Gray, Andrew Moore 11:35 12:00 A Bayesian Approach to Bergman's Minimal Model. Kim E. Andersen, Malene Hψjbjerre 12:00 12:25 Bayesian Inference in the Presence of Determinism. David Larkin, Rina Dechter 12:25 13:30 Lunch 13:30 19:00 Informal Discussion/Free Time/Poster Set-Up 19:00 20:30 Conference Dinner 20:30 22:30 Poster Session Monday 6th January 2003 09:00 09:50 Invited talk: Tommi Jaakkola 09:50 10:20 Coffee 10:20 10:45 Convex Invariance Learning. Tony Jebara 10:45 11:10 On Boosting and the Exponential Loss. Abraham Wyner 11:10 12:00 Invited talk: Lawrence Saul 12:00 13:00 Lunch 13:00 19:00 Informal Discussion/Free Time for own activities 19:00 20:00 Dinner Break 20:00 20:25 Solving Markov Random Fields using Semi Definite Programming. Philip Torr 20:25 20:50 The Sound of an Album Cover: A Probabilistic Approach to Multimedia. Eric Brochu, Nando de Freitas, Kejie Bao 20:50 21:15 A Generalized Linear Model for Principal Component Analysis of Binary Data. Andrew Schein, Lawrence Saul, Lyle Ungar 21:15 22:05 Invited talk: Andrew Blake Tuesday 7th January 2003 Breakfast and depart
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