UAI 2005

Program Schedule
 

• Tuesday July 26th. (Tutorials and Collocated 3rd Bayesian Modeling Applications Workshop)

  9:00	Tutorial I: Large-Margin Learning of Structured Prediction Models Ben Taskar, University of California at Berkeley
  10:30	Break
  11:00	Tutorial II: Non-parametric Bayesian methods Zoubin Ghahramani, Gatsby Computational Neuroscience Unit, University College London
  12:30	Lunch
  2:00	Tutorial III: Sensor Networks: Opportunities for UAI Carlos Guestrin, Carnegie Mellon University
  3:30	Break
  4:00	Tutorial IV: Computational Mechanism Design Satinder Singh, University of Michigan
  7:00	Opening Reception

• Wednesday July 27th. (Main conference commences)

8:45	Welcome
9:00	Session I: Preferences and Economic Models Chair: Satinder Singh Local Utility Elicitation in GAI Models Darius Braziunas and Craig Boutilier Unstructuring User Preferences: Efficient Non-parametric Utility Revelation Carmel Domshlak and Thorsten Joachims Common Voting Rules as Maximum Likelihood Estimators Vincent Conitzer and Tuomas Sandholm An Algorithm for Computing Stochastically Stable Distributions with Applications to Multiagent Learning in Repeated Games Amy Greenwald and John R. Wicks
10:40	Break
11:10	Session II: POMDPS Chair: Carmel Domshlak Near-Optimal Nonmyopic Value of Information in Graphical Models Andreas Krause and Carlos Guestrin Representation Policy Iteration Sridhar Mahadevan Point-based POMDP Algorithms: Improved Analysis and Implementation Trey Smith and Reid Simmons
12:25	Lunch
2:00	Invited Talk: Decision Theory Without "Acts" Larry Blume, Cornell University
3:00	Poster Highlights
3:30	Poster Session I

• Thursday July 28th

9:00	Session III: Extended Models Chair: Ronen Brafman Evidence with Uncertain Likelihoods Joseph Y. Halpern and Riccardo Pucella 'Say EM' for Selecting Probabilistic Models for Logical Sequences Kristian Kersting and Tapani Raiko Belief Updating and Learning in Semi-Qualitative Probabilistic Networks Cassio P. de Campos and Fabio G. Cozman Expectation Maximization and Complex Duration Distributions for Continuous Time Bayesian Networks Uri Nodelman, Christian R. Shelton and Daphne Koller
10:40	Break
11:10	Session IV: Message Passing Methods Chair: Daphne Koller On the Optimality of Tree-reweighted Max-product Message-passing Vladimir Kolmogorov and Martin J. Wainwright Sufficient Conditions for Convergence of Loopy Belief Propagation Joris M. Mooij and Hilbert J. Kappen Structured Region Graphs: Morphing EP into GBP M. Welling, T. Minka and Y.W. Teh
12:25	Lunch (Chairs Lunch Meeting)
2:00	Invited Talk: A Walk on Mars: Managing Uncertainty Through Model-based Programming   Brian C. Williams, MIT
3:00	Poster Highlights
3:30	Poster Session II
5:30	AUAI Business Meeting
7:00	Conference Banquet Banquet Talk: Hands-free writing David MacKay, University of Cambridge

• Friday July 29th

9:00	Session V: Applications Chair: Linda van Der Gaag Robotic Mapping with Polygonal Random Fields Mark A. Paskin and Sebastian Thrun Efficient Test Selection in Active Diagnosis via Entropy Approximation Alice X. Zheng, Irina Rish and Alina Beygelzimer Bayes' Bluff: Opponent Modelling in Poker Finnegan Southey, Michael Bowling, Bryce Larson, Carmelo Piccione, Neil Burch, Darse Billings, and Chris Rayner Prediction, Expectation, and Surprise: Methods, Designs, and Study of a Deployed Traffic Forecasting Service Eric Horvitz, Johnson Apacible, Raman Sarin and Lin Liao
10:40	Break
11:10	Session VI: Approximate Inference Chair: Avi Pfeffer The DLR Hierarchy of Approximate Inference Michal Rosen-Zvi, Michael I. Jordan and Alan L. Yuille Toward Practical N2 Monte Carlo: the Marginal Particle Filter Mike Klaas, Nando de Freitas, Arnaud Doucet
12:00	Invited Talk: Uncertainty and Algorithms in Structural Molecular Biology and Proteomics Bruce R. Donald, Dartmouth
1:00	Lunch
2:30	Invited Talk: Models and Games for All the World's Information Peter Norvig, Google
3:30	Session VII: Learning Chair: Nir Friedman Learning to map Sentences to Logical Form: Structured Classification with Probabilistic Categorial Grammars Luke Zettlemoyer and Michael Collins A Conditional Random Field For Discriminatively-Trained Finite-State String Edit Distance Andrew McCallum, Kedar Bellare and Fernando Pereira Discovery of Non-Gaussian Linear Causal Models Using ICA Shohei Shimizu, Aapo Hyvärinen, Yutaka Kano, and Patrik O. Hoyer
4:45	Conference ends.