Wednesday January 5: |
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6:30- |
Arrival and Evening Reception |
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Thursday
January 6: |
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9:15-9:30 |
Welcome |
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9:30-10:15 |
Invited Talk |
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Tom Minka |
Some Intuitions About Message Passing |
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10:15-11:05 |
Session |
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Semiparametric Latent Factor Models |
Yee Whye Teh, Matthias Seeger and Michael I. Jordan |
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Approximate Inference for Infinite Contingent Bayesian Networks |
Brian Milch, Bhaskara Marthi, David Sontag, Stuart Russell,
Daniel
L. Ong and Andrey Kolobov |
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11:05-11:30 |
Coffee Break |
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11:30-1:10 |
Session |
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A Graphical Model for Simultaneous Partitioning and Labeling |
Philip J. Cowans and Martin Szummer
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*Best
Student Paper Award* |
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Generative Model for Layers of Appearance and Deformation |
Anitha Kannan, Nebojsa Jojic and Brendan Frey |
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Loss Functions for Discriminative Training of Energy-Based
Models |
Yann LeCun and Fu Jie Huang |
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Learning Causally Linked Markov Random Fields |
Geoffrey Hinton, Simon Osindero and Kejie Bao |
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1:10-8:00 |
Break |
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8:00-8:45 |
Invited Talk |
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Steffen Lauritzen |
Identification and Separation of DNA Mixtures using
Peak Area Information |
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8:45-9:10 |
Session |
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Nonlinear Dimensionality Reduction by Semidefinite
Programming
and Kernel Matrix Factorization |
Kilian Weinberger, Benjamin Packer
and Lawrence Saul |
*Best
Student Paper Award* |
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9:10-11:10 |
Poster Session 1 - (click for poster titles) |
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Friday January 7: |
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9:15-10:00 |
Invited Talk |
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Craig Boutilier |
Regret-based Methods
for Decision Making and Preference Elicitation |
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10:00-10:50 |
Session |
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Defensive Forecasting |
Vladimir Vovk, Akimichi Takemura and Glenn Shafer |
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Kernel Constrained Covariance for Dependence Measurement |
Arthur Gretton, Alex Smola,
Olivier Bousquet,
Ralf Herbrich,
Andrei Belitski, Mark Augath,
Yusuke Murayama,
Jon
Pauls,
Bernhard Schölkopf and Nikos Logothetis |
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10:50-11:15 |
Coffee Break |
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11:15-12:30 |
Session |
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Kernel Methods for Missing Variables |
Alex Smola, S. V. N. Vishwanathan
and Thomas Hofmann |
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Regularized Spectral Learning |
Marina Meila, Susan Shortreed and Liang Xu |
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Learning Spectral Graph
Segmentation |
Timothée Cour, Nicolas Gogin
and Jianbo Shi |
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12:30-5:00 |
Break |
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5:00-6:15 |
Session |
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Distributed Latent Variable Models of Lexical Co-occurrences |
John Blitzer |
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On the Path to an Ideal ROC Curve:
Considering Cost
Asymmetry in Learning Classifiers |
Francis Bach, Amir Globerson and Fernando Pereira |
*Best Student Paper Award* |
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Estimating Class Membership Probabilities using Classifier
Learners |
John Langford and Bianca Zadrozny |
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6:15-8:00 |
Poster Session 2 - (click
for poster titles) |
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8:00- |
Banquet |
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Saturday January 8: |
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9:15-10:00 |
Invited Talk |
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Tommi Jaakkola |
Information, transfer,
and semi-supervised learning |
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10:00-10:50 |
Session |
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Robust Higher Order Statistics |
Max Welling |
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Fast Non-Parametric Bayesian Inference on Infinite
Trees |
Marcus Hutter |
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10:50-11:15 |
Coffee Break |
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11:15-12:30 |
Session |
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Poisson-Networks: A Model for Structured Poisson Processes |
Shyamsundar Rajaram, Graepel Thore and Ralf Herbrich |
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Autonomy Identification for Bayesian Network Structure
Learning |
Raanan Yehezkel and Boaz Lerner |
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Restructuring Dynamic Causal Systems in Equilibrium |
Denver Dash |
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12:30-8:00 |
Break |
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8:00-10:00 |
Poster Session 3 - (click
for poster titles) |
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10:00-10:25 |
Session |
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Probability and Statistics in the Law |
Philip Dawid |
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10:25-11:10 |
Invited Talk |
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Nir Friedman |
Probabilistic Models for Identifying Regulation Networks:
From Qualitative to Quantitative Models |
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11:10 |
Close of AISTATS 2005 |