UAI 2005

21st Conference on Uncertainty in Artificial Intelligence
Program Schedule

July 26th-July 29th 2005

University of Edinburgh
Edinburgh, Scotland

Program Schedule

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


    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

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


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




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


Lunch (Chairs Lunch Meeting)


Invited Talk: A Walk on Mars: Managing Uncertainty Through Model-based Programming  
Brian C. Williams, MIT


Poster Highlights


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


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




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


Invited Talk: Uncertainty and Algorithms in Structural Molecular Biology and Proteomics
Bruce R. Donald, Dartmouth




Invited Talk: Models and Games for All the World's Information
Peter Norvig, Google


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.