[Artificial Intelligence and Statistics Logo] Artificial Intelligence and Statistics 2003

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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 Højbjerre

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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