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---
title: Schedule
layout: default
---
<table>
<tr>
<td width="100%">
<p><b>Friday 3<sup>rd</sup> January 2003</b></p>
<p>Informal reception at 18:00</p>
<p><b>Saturday 4<sup>th</sup> January 2003</b></p>
<p>09:00 – 09:10 Welcome</p>
<p>09:10 – 10:00 <b>Invited talk: Geoffrey Hinton</b></p>
<p>10:00 – 10:25
<i><b>Fast Marginal Likelihood Maximisation for Sparse
Bayesian Models.</b></i> Michael Tipping, Anita Faul</p>
<p>10:25 – 10:50 Coffee</p>
<p>10:50 – 11:15 <i><b>Combining
Conjugate Direction Methods with Stochastic Approximation of Gradients.</b></i>
Nicol Schraudolph, Thore Graepel</p>
<p>11:15 – 11:40 <i><b>Expectation
Maximization of Forward Decoding Kernel Machines.</b></i> Shantanu
Chakrabartty, Gert Cauwenberghs</p>
<p>11:40 – 12:30
<b>Invited talk: </b>
<b>Zoubin Ghahramani</b></p>
<p>12:30 – 13:30 Lunch</p>
<p>13:30 – 19:00 Informal Discussion/Free Time for own activities</p>
<p>19:00 – 20:00 Dinner Break</p>
<p>20:00 – 20:50
<b>Invited talk: </b>
<b>Bill Freeman</b></p>
<p>20:50 – 21:15 <i><b>Generalized
belief propagation for approximate inference in hybrid Bayesian networks.</b></i>
Tom Heskes, Onno Zoeter</p>
<p>21:15 – 21:40 <i><b> </b></i><i><b>Tree-reweighted
belief propagation algorithms and approximate ML estimation by pseudo-moment
matching.</b></i> Martin Wainwright, Tommmi Jaakkola, Alan Willsky</p>
<p>21:40 – 22:05 <i><b>Model
Averaging with Bayesian Network Classifiers. </b></i>Denver Dash, Greg
Cooper</p>
<p><b>Sunday 5<sup>th</sup> January 2003</b></p>
<p>09:00 – 09:50
<b>Invited talk: </b>
<b>David Haussler</b></p>
<p>09:50 – 10:20 Coffee</p>
<p>10:20 – 10:45
<i><b>Fast Forward Selection to Speed Up Sparse
Gaussian Process Regression.</b></i> Matthias Seeger, Christopher K.I.
Williams</p>
<p>10:45 – 11:10 <i><b>On
Improving the Efficiency of the Iterative Proportional Fitting Procedure.
</b></i>Yee Whye Teh, Max Welling</p>
<p>11:10 – 11:35 <i><b>Rapid
Evaluation of Multiple Density Models. </b></i>Alexander Gray, Andrew Moore</p>
<p>11:35 – 12:00 <i><b>A
Bayesian Approach to Bergman's Minimal Model. </b></i>Kim E. Andersen,
Malene Højbjerre</p>
<p>12:00 – 12:25 <i><b>Bayesian
Inference in the Presence of Determinism. </b></i>David Larkin, Rina Dechter</p>
<p>12:25 – 13:30 Lunch</p>
<p>13:30 – 19:00 Informal
Discussion/Free Time/Poster Set-Up</p>
<p>19:00 – 20:30 <b>Conference
Dinner</b></p>
<p>20:30 – 22:30 <b> <i><a title="Go to poster presentation page" href="posters.html">Poster
Session</a></i></b></p>
<p><b>Monday 6<sup>th</sup> January 2003</b></p>
<p>09:00 – 09:50
<b>Invited talk: </b>
<b>Tommi Jaakkola </b>
</p>
<p>09:50 – 10:20 Coffee</p>
<p>10:20 – 10:45
<b><i>Convex Invariance Learning.</i></b> Tony Jebara</p>
<p>10:45 – 11:10
<i><b>On Boosting and the Exponential Loss.</b></i>
Abraham Wyner</p>
<p>11:10 – 12:00 <b>
Invited talk:
Lawrence Saul</b></p>
<p>12:00 – 13:00 Lunch</p>
<p>13:00 – 19:00 Informal Discussion/Free Time for own activities</p>
<p>19:00 – 20:00 Dinner Break</p>
<p>20:00 – 20:25
<i><b>Solving Markov Random Fields using Semi Definite
Programming.</b></i> Philip Torr</p>
<p>20:25 – 20:50
<i><b>The Sound of an Album Cover: A Probabilistic
Approach to Multimedia.</b></i> Eric Brochu,
Nando de Freitas, Kejie Bao</p>
<p>20:50 – 21:15
<b><i>A Generalized Linear Model for Principal
Component Analysis of Binary Data</i>.</b>
Andrew Schein, Lawrence Saul, Lyle Ungar</p>
<p>21:15 – 22:05
<b>Invited talk: </b>
<b>Andrew Blake </b></p>
<p><b>Tuesday 7<sup>th</sup> January 2003</b></p>
<p>Breakfast and depart</p>
</td>
</tr>
</table>