22. UAI 2006: Cambridge, MA, USA

• Manfred K. Warmuth:
  A Bayesian Probability Calculus for Density Matrices.
  
• Manfred K. Warmuth, Dima Kuzmin:
  A Bayesian Probability Calculus for Density Matrices.
  
• Bhaskara Marthi, Stuart J. Russell, David Andre:
  A Compact, Hierarchical Q-function Decomposition.
  
• Sanjoy Dasgupta, Daniel Hsu, Nakul Verma:
  A Concentration Theorem for Projections.
  
• Phan Hong Giang:
  A New Axiomatization for Likelihood Gambles.
  
• Frank Wood, Thomas L. Griffiths, Zoubin Ghahramani:
  A Non-Parametric Bayesian Method for Inferring Hidden Causes.
  
• David Stavens, Sebastian Thrun:
  A Self-Supervised Terrain Roughness Estimator for Off-Road Autonomous Driving.
  
• Tomi Silander, Petri Myllymäki:
  A Simple Approach for Finding the Globally Optimal Bayesian Network Structure.
  
• Subramani Mani, Gregory F. Cooper, Peter Spirtes:
  A Theoretical Study of Y Structures for Causal Discovery.
  
• Arthur Choi, Adnan Darwiche:
  A Variational Approach for Approximating Bayesian Networks by Edge Deletion.
  
• Joseph Ramsey, Jiji Zhang, Peter Spirtes:
  Adjacency-Faithfulness and Conservative Causal Inference.
  
• Mikko Koivisto:
  Advances in Exact Bayesian Structure Discovery in Bayesian Networks.
  
• Michael L. Littman, Nishkam Ravi, Arjun Talwar, Martin Zinkevich:
  An Efficient Optimal-Equilibrium Algorithm for Two-player Game Trees.
  
• Yaxin Bi, Jiwen Guan:
  An Efficient Triplet-based Algorithm for Evidential Reasoning.
  
• Varsha Dani, Omid Madani, David M. Pennock, Sumit K. Sanghai, Brian Galebach:
  An Empirical Comparison of Algorithms for Aggregating Expert Predictions.
  
• Avi Pfeffer:
  Approximate Separability for Weak Interaction in Dynamic Systems.
  
• Vanessa Didelez:
  Asymmetric Separation for Local Independence Graphs.
  
• Paul Weng:
  Axiomatic Foundations for a Class of Generalized Expected Utility: Algebraic Expected Utility.
  
• Ricardo Silva, Zoubin Ghahramani:
  Bayesian Inference for Gaussian Mixed Graph Models.
  
• Zhihua Zhang, Michael I. Jordan:
  Bayesian Multicategory Support Vector Machines.
  
• Max Welling, Sridevi Parise:
  Bayesian Random Fields: The Bethe-Laplace Approximation.
  
• Andres Madsen:
  Belief Update in CLG Bayesian Networks With Lazy Propagation.
  
• Thomas Degris, Olivier Sigaud, Pierre-Henri Wuillemin:
  Chi-square Tests Driven Method for Learning the Structure of Factored MDPs.
  
• Tal El-Hay, Nir Friedman, Daphne Koller, Raz Kupferman:
  Continuous Time Markov Networks.
  
• Yuhong Guo, Dale Schuurmans:
  Convex Structure Learning for Bayesian Networks: Polynomial Feature Selection and Approximate Ordering.
  
• Bozhena Bidyuk, Rina Dechter:
  Cutset Sampling with Likelihood Weighting.
  
• Nir Friedman, Raz Kupferman:
  Dimension Reduction in Singularly Perturbed Continuous-Time Bayesian Networks.
  
• Vanessa Didelez, A. Philip Dawid, Sara Geneletti:
  Direct and Indirect Effects of Sequential Treatments.
  
• Koby Crammer, Amir Globerson:
  Discriminative Learning via Semidefinite Probabilistic Models.
  
• Monika Schaeffer, Ronald Parr:
  Efficient Selection of Disambiguating Actions for Stereo Vision.
  
• Dongryeol Lee, Alexander G. Gray:
  Faster Gaussian Summation: Theory and Experiment.
  
• Michael Eichler:
  Fitting Graphical Interaction Models to Multivariate Time Series.
  
• Cédric Pralet, Thomas Schiex, Gérard Verfaillie:
  From Influence Diagrams to Multi-operator Cluster DAGs.
  
• Matthew J. Beal, Praveen Krishnamurthy:
  Gene Expression Time Course Clustering with Countably Infinite Hidden Markov Models.
  
• Brian Milch, Stuart J. Russell:
  General-Purpose MCMC Inference over Relational Structures.
  
• Ian Porteous, Alex Ihter, Padhraic Smyth, Max Welling:
  Gibbs Sampling for (Coupled) Infinite Mixture Models in the Stick Breaking Representation.
  
• Carlos Brito, Judea Pearl:
  Graphical Condition for Identification in recursive SEM.
  
• Ilya Shpitser, Judea Pearl:
  Identification of Conditional Interventional Distributions.
  
• José M. Peña, Roland Nilsson, Johan Björkegren, Jesper Tegnér:
  Identifying the Relevant Nodes Without Learning the Model.
  
• Alexander L. Strehl, Lihong Li, Michael L. Littman:
  Incremental Model-based Learners With Formal Learning-Time Guarantees.
  
• Changsung Kang, Jin Tian:
  Inequality Constraints in Causal Models with Hidden Variables.
  
• Prakash P. Shenoy:
  Inference in Hybrid Bayesian Networks Using Mixtures of Gaussians.
  
• Zhao Xu, Volker Tresp, Kai Yu, Hans-Peter Kriegel:
  Infinite Hidden Relational Models.
  
• Chalee Asavathiratham:
  Linear Algebra Approach to Separable Bayesian Networks.
  
• Robert G. Cowell, Steffen L. Lauritzen, Julia Mortera:
  MAIES: A Tool for DNA Mixture Analysis.
  
• Inmar E. Givoni, Vincent Cheung, Brendan J. Frey:
  Matrix Tile Analysis.
  
• Iain Murray, Zoubin Ghahramani, David J. C. MacKay:
  MCMC for Doubly-intractable Distributions.
  
• Norm Ferns, Pablo Samuel Castro, Doina Precup, Prakash Panangaden:
  Methods for Computing State Similarity in Markov Decision Processes.
  
• Chris D. Bartels, Jeff A. Bilmes:
  Non-Minimal Triangulations for Mixed Stochastic/Deterministic Graphical Models.
  
• Or Zuk, Shiri Margel, Eytan Domany:
  On the Number of Samples Needed to Learn the Correct Structure of a Bayesian Network.
  
• Hei Chan, Adnan Darwiche:
  On the Robustness of Most Probable Explanations.
  
• Ruggiero Cavallo, David C. Parkes, Satinder P. Singh:
  Optimal Coordinated Planning Amongst Self-Interested Agents with Private State.
  
• Yimin Huang, Marco Valtorta:
  Pearl's Calculus of Intervention Is Complete.
  
• Scott Sanner, Craig Boutilier:
  Practical Linear Value-approximation Techniques for First-order MDPs.
  
• John Langford, Roberto Oliveira, Bianca Zadrozny:
  Predicting Conditional Quantiles via Reduction to Classification.
  
• Kathryn B. Laskey, Ning Xu, Chun-Hung Chen:
  Propagation of Delays in the National Airspace System.
  
• Harald Steck:
  Ranking by Dependence - A Fair Criteria.
  
• Seunghwan Lee:
  Reasoning about Uncertainty in Metric Spaces.
  
• Amar Subramanya, Alvin Raj, Jeff A. Bilmes, Dieter Fox:
  Recognizing Activities and Spatial Context Using Wearable Sensors.
  
• Gal Elidan, Ian McGraw, Daphne Koller:
  Residual Belief Propagation: Informed Scheduling for Asynchronous Message Passing.
  
• Itai Ashlagi, Moshe Tennenholtz, Dov Monderer:
  Robust Learning Equilibrium.
  
• Theodore Charitos, Linda C. van der Gaag:
  Sensitivity Analysis for Threshold Decision Making with Dynamic Networks.
  
• Guy Lebanon:
  Sequential Document Representations and Simplicial Curves.
  
• Wim Wiegerinck, Bart van den Broek, Bert Kappen:
  Stochastic Optimal Control in Continuous Space-Time Multi-Agent Systems.
  
• Manabu Kuroki, Zhihong Cai:
  Stratified Analysis of 'Probabilities of Causation'.
  
• Vikash K. Mansinghka, Charles Kemp, Thomas L. Griffiths, Joshua B. Tenenbaum:
  Structured Priors for Structure Learning.
  
• Manfred Jaeger:
  The AI&M Procedure for Learning from Incomplete Data.
  
• Edward Snelson, Zoubin Ghahramani:
  Variable Noise and Dimensionality Reduction for Sparse Gaussian processes.
  
• Guobiao Mei, Peter Russo:
  Visualization of Collaborative Data.
  

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