Thursday, July 13th - Tutorials
9:00 - 10:30 Tutorial 1: Compiling Graphical Models
Adnan Darwiche, University of California, Los Angeles
10:30 - 11:00 Break
11:00 - 12:30 Tutorial 2: Uncertainty with Logical, Procedural and Relational Languages
David Poole, University of British Columbia
12:30 - 14:00 Lunch
14:00 - 15:30 Tutorial 3: Causal Inference and Graphical Models - I
Peter Spirtes, Carnegie Mellon University
15:30 - 16:00 Break
16:00 - 17:30 Tutorial 4: Causal Inference and Graphical Models - II
Jin Tian, Iowa State University
19:00 Opening Reception
Friday, July 14th
8:45 - 9:00 Welcome
9:00 - 10:40 Session I: Probabilistic Inference
Chair: Adnan Darwiche

Asymmetric Separation For Local Independence Graphs
Vanessa Didelez Inference in Hybrid Bayesian Networks Using Mixtures of Gaussians
Prakash Shenoy Non-Minimal Triangulations for Mixed Stochastic/Deterministic Graphical Models
Chris Bartels and Jeff Bilmes General-Purpose MCMC Inference over Relational Structures
Brian Milch and Stuart Russell

10:40 - 11:10 Break
11:10 - 12:25 Session II: Structure Learning
Chair: Avi Pfeffer

Advances in exact Bayesian structure discovery in Bayesian networks
Mikko Koivisto A Variational Approach for Approximating Bayesian Networks by Edge Deletion
Arthur Choi and Adnan Darwiche On the Number of Samples Needed to Learn the Correct Structure of a Bayesian Network
Or Zuk, Shiri Margel and Eytan Domany

12:25 - 14:00 Lunch (Chairs Lunch Meeting)
14:00 - 15:00 Invited talk: Anticipatory Algorithms for Online Stochastic Combinatorial Optimization
Pascal Van Hentenryck, Brown University
15:00 - 16:00 Software Evaluation Report
Jeff Bilmes
16:00 - 16:30 Poster Highlights
16:30 - 18:30 Poster Session I
Saturday, July 15th
9:00 - 10:40 Session III: Causality
Chair: Jin Tian

Pearl's Calculus of Intervention Is Complete
Yimin Huang and Marco Valtorta Identification of Conditional Interventional Distributions
Ilya Shpitser and Judea Pearl Structured Priors for Structure Learning
Vikash Mansinghka, Charles Kemp, Thomas Griffiths and Joshua Tenenbaum Adjacency-Faithfulness and Conservative Causal Inference
Joseph Ramsey, Jiji Zhang and Peter Spirtes

10:40 - 11:10 Break
11:10 - 12:25 Session IV: Multi-agents
Chair: TBD

An Efficient Optimal-Equilibrium Algorithm for Two-player Game Trees
Michael Littman, Nishkam Ravi, Arjun Talwar and Martin Zinkevich Optimal Coordinated Planning Amongst Self-Interested Agents with Private State
Ruggiero Cavallo, David Parkes and Satinder Singh An Empirical Comparison of Algorithms for Aggregating Expert Predictions
Varsha Dani, Omid Madani, David Pennock, Sumit Sanghai and Brian Galebach

12:25 - 14:00 Lunch
14:00 - 15:00 Invited talk: Marginal Science: Facing the Task of Inference about an Unobserved Margin from an Insufficient Set of Observed Margins
Sander Greenland, University of California, Los Angeles
15:00 - 15:30 Poster Highlights
15:30 - 17:30 Poster Session II
17:30 AUAI Business Meeting
19:00 Conference Banquet
Banquet talk: Does the Turing Test Demonstrate Intelligence or Not?
Stuart M. Shieber, Harvard University
Sunday, July 16th
9:00 - 10:40 Session V: Dynamic Models
Chair: Jeff Bilmes

Continuous Time Markov Networks
Tal El-Hay, Nir Friedman, Daphne Koller and Raz Kupferman Incremental Model-based Learners With Formal Learning-Time Guarantees
Alexander L. Strehl, Lihong Li and Michael L. Littman Methods for computing state similarity in Markov Decision Processes
Norman Francis Ferns, Pablo Samuel Castro, Doina Precup and Prakash Panangaden Practical Linear Value-approximation Techniques for First-order MDPs
Scott Sanner and Craig Boutilier

10:40 - 11:10 Break
11:10 - 12:25 Session VI: Parameter Learning
Chair: Nir Friedman

Bayesian Inference for Gaussian Mixed Graph Models
Ricardo Silva and Zoubin Ghahramani Bayesian Random Fields: The Bethe-Laplace Approximation
Max Welling and Sridevi Parise A Bayesian Probability Calculus for Density Matrices
Manfred Warmuth and Dima Kuzmin

12:25 - 14:00 Lunch
14:00 - 15:00 Invited talk: Statistical Models for Population Genetic Data
Matthew Stephens, University of Washington
15:00 - 17:05 Session VII: Applications
Chair: Eric Horvitz

A Self-Supervised Terrain Roughness Estimator for Off-Road Autonomous Driving
David Stavens and Sebastian Thrun Propagation of Delays in the National Airspace System
Kathryn Laskey, Ning Xu and Chun-Hung Chen MAIES: A Tool for DNA Mixture Analysis
Robert Cowell, Steffen Lauritzen and Julia Mortera Efficient Selection of Disambiguating Actions for Stereo Vision
Monika Schaeffer and Ronald Parr Recognizing Activities and Spatial Context Using Wearable Sensors
Amarnag Subramanya, Alvin Raj, Jeff Bilmes and Dieter Fox

17:30 Conference ends