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