Table of Contents

• Optimizing Memory-Bounded Controllers for Decentralized POMDPsChristopher Amato, Daniel S. Bernstein, Shlomo Zilberstein. 1-8 [doi]
• Evaluating influence diagrams with decision circuitsDebarun Bhattacharjya, Ross D. Shachter. 9-16 [doi]
• Discovering Patterns in Biological Sequences by Optimal SegmentationJoseph Bockhorst, Nebojsa Jojic. 17-24 [doi]
• Minimax regret based elicitation of generalized additive utilitiesDarius Braziunas, Craig Boutilier. 25-32 [doi]
• Generalized Polya Urn for Time-varying Dirichlet Process MixturesFrancois Caron, Manuel Davy, Arnaud Doucet. 33-40 [doi]
• Reachability Under UncertaintyAllen Chang, Eyal Amir. 41-48 [doi]
• A Utility Framework for Bounded-Loss Market MakersYiling Chen, David M. Pennock. 49-56 [doi]
• Node Splitting: A Scheme for Generating Upper Bounds in Bayesian NetworksArthur Choi, Mark Chavira, Adnan Darwiche. 57-66 [doi]
• Bandit Algorithms for Tree SearchPierre-Arnaud Coquelin, Rémi Munos. 67-74 [doi]
• Probabilistic Models for Anomaly Detection in Remote Sensor Data StreamsEthan W. Dereszynski, Thomas G. Dietterich. 75-82 [doi]
• Learning Probabilistic Relational Dynamics for Multiple TasksAshwin Deshpande, Brian Milch, Luke S. Zettlemoyer, Leslie Pack Kaelbling. 83-92 [doi]
• Statistical Translation, Heat Kernels and Expected DistancesJoshua V. Dillon, Yi Mao, Guy Lebanon, Jian Zhang. 93-100 [doi]
• Bayesian structure learning using dynamic programming and MCMCDaniel Eaton, Kevin P. Murphy. 101-108 [doi]
• Causal Reasoning in Graphical Time Series ModelsMichael Eichler, Vanessa Didelez. 109-116 [doi]
• A new parameter Learning Method for Bayesian Networks with Qualitative InfluencesAd Feelders. 117-124 [doi]
• Search for Choquet-optimal paths under uncertaintyLucie Galand, Patrice Perny. 125-132 [doi]
• Convergent Propagation Algorithms via Oriented TreesAmir Globerson, Tommi Jaakkola. 133-140 [doi]
• Studies in Lower Bounding Probabilities of Evidence using the Markov InequalityVibhav Gogate, Bozhena Bidyuk, Rina Dechter. 141-148 [doi]
• Shift-Invariance Sparse Coding for Audio ClassificationRoger Grosse, Rajat Raina, Helen Kwong, Andrew Y. Ng. 149-158 [doi]
• Analysis of Semi-Supervised Learning with the Yarowsky AlgorithmGholamreza Haffari, Anoop Sarkar. 159-166 [doi]
• Large-Flip Importance SamplingFiras Hamze, Nando de Freitas. 167-174 [doi]
• Fast Nonparametric Conditional Density EstimationMichael P. Holmes, Alexander G. Gray, Charles L. Isbell. 175-182 [doi]
• Accuracy Bounds for Belief PropagationAlexander T. Ihler. 183-190 [doi]
• Template Based Inference in Symmetric Relational Markov Random FieldsAriel Jaimovich, Ofer Meshi, Nir Friedman. 191-199 [doi]
• Polynomial Constraints in Causal Bayesian NetworksChangsung Kang, Jin Tian. 200-208 [doi]
• On Discarding, Caching, and Recalling Samples in Active LearningAshish Kapoor, Eric Horvitz. 209-216 [doi]
• Survey Propagation RevisitedLukas Kroc, Ashish Sabharwal, Bart Selman. 217-226 [doi]
• Evaluation of the Causal Effect of Control Plans in Nonrecursive Structural Equation ModelsManabu Kuroki, Zhihong Cai. 227-234 [doi]
• Learning Bayesian Network Structure from Correlation-Immune DataEric Lantz, Soumya Ray, David Page. 235-242 [doi]
• Nonparametric Bayes Pachinko AllocationWei Li, David M. Blei, Andrew McCallum. 243-250 [doi]
• Determining the Number of Non-Spurious Arcs in a Learned DAG Model: Investigation of a Bayesian and a Frequentist ApproachJennifer Listgarten, David Heckerman. 251-258 [doi]
• Best-First AND/OR Search for Most Probable ExplanationsRadu Marinescu 0002, Rina Dechter. 259-266 [doi]
• Collaborative Filtering and the Missing at Random AssumptionBenjamin M. Marlin, Richard S. Zemel, Sam T. Roweis, Malcolm Slaney. 267-275 [doi]
• AND/OR Multi-Valued Decision Diagrams (AOMDDs) for Weighted Graphical ModelsRobert Mateescu, Rina Dechter. 276-284 [doi]
• Consensus ranking under the exponential modelMarina Meila, Kapil Phadnis, Arthur Patterson, Jeff A. Bilmes. 285-294 [doi]
• Apprenticeship Learning using Inverse Reinforcement Learning and Gradient MethodsGergely Neu, Csaba Szepesvári. 295-302 [doi]
• Reading Dependencies from Polytree-Like Bayesian NetworksJose M. Peña. 303-309 [doi]
• Causal Bounds and InstrumentsRoland Ramsahai. 310-317 [doi]
• Mixture-of-Parents Maximum Entropy Markov ModelsDavid S. Rosenberg, Dan Klein, Ben Taskar. 318-325 [doi]
• Reasoning at the Right Time GranularitySuchi Saria, Uri Nodelman, Daphne Koller. 326-334 [doi]
• A Tractable Approach to Finding Closest Truncated-commute-time Neighbors in Large GraphsPurnamrita Sarkar, Andrew W. Moore. 335-343 [doi]
• Improved Memory-Bounded Dynamic Programming for Decentralized POMDPsSven Seuken, Shlomo Zilberstein. 344-351 [doi]
• What Counterfactuals Can Be TestedIlya Shpitser, Judea Pearl. 352-359 [doi]
• On Sensitivity of the MAP Bayesian Network Structure to the Equivalent Sample Size ParameterTomi Silander, Petri Kontkanen, Petri Myllymäki. 360-367 [doi]
• Markov Logic in Infinite DomainsParag Singla, Pedro Domingos. 368-375 [doi]
• Improved Dynamic Schedules for Belief PropagationCharles A. Sutton, Andrew McCallum. 376-383 [doi]
• Imitation Learning with a Value-Based PriorUmar Syed, Robert E. Schapire. 384-391 [doi]
• A Criterion for Parameter Identification in Structural Equation ModelsJin Tian. 392-399 [doi]
• Constrained Automated Mechanism Design for Infinite Games of Incomplete InformationYevgeniy Vorobeychik, Daniel M. Reeves, Michael P. Wellman. 400-407 [doi]
• Policy Iteration for Relational MDPsChenggang Wang, Roni Khardon. 408-415 [doi]
• MAP Estimation, Linear Programming and Belief Propagation with Convex Free EnergiesYair Weiss, Chen Yanover, Talya Meltzer. 416-425 [doi]
• Importance Sampling via Variational OptimizationYdo Wexler, Dan Geiger. 426-433 [doi]
• More-or-Less CP-NetworksFusun Yaman, Marie desJardins. 434-441 [doi]
• Bayesian Active Distance Metric LearningLiu Yang, Rong Jin, Rahul Sukthankar. 442-449 [doi]
• A Characterization of Markov Equivalence Classes for Directed Acyclic Graphs with Latent VariablesJiji Zhang. 450-457 [doi]
• Learning Selectively Conditioned Forest Structures with Applications to DBNs and ClassificationBrian D. Ziebart, Anind K. Dey, James A. Bagnell. 458-465 [doi]
• Ranking Under UncertaintyOr Zuk, Liat Ein-Dor, Eytan Domany. 466-473 [doi]
• Making life better one large system at a time: Challenges for UAI researchMoisés Goldszmidt. 475-481 [doi]
• Statistical Mechanics of Biological NetworksMarco Ramoni. 482-483 [doi]