Table of Contents

• A Factorized Variational Technique for Phase Unwrapping in Markov Random FieldKannan Achan, Brendan J. Frey, Ralf Koetter. 1-6 [doi]
• Efficient Approximation for Triangulation of Minimum Treewidth7-15 [doi]
• Markov Chain Monte Carlo using Tree-Based Priors on Model StructureNicos Angelopoulos, James Cussens. 16-23 [doi]
• Graphical readings of possibilistic logic basesSalem Benferhat, Didier Dubois, Souhila Kaci, Henri Prade. 24-31 [doi]
• Pre-processing for Triangulation of Probabilistic NetworksHans Leo Bodlaender, Arie M. C. A. Koster, Frank van den Eijkhof, Linda C. van der Gaag. 32-39 [doi]
• A Calculus for Causal RelevanceBlai Bonet. 40-47 [doi]
• Instrumentality Tests RevisitedBlai Bonet. 48-55 [doi]
• UCP-Networks: A Directed Graphical Representation of Conditional UtilitiesCraig Boutilier, Fahiem Bacchus, Ronen I. Brafman. 56-64 [doi]
• When do Numbers Really Matter?Hei Chan, Adnan Darwiche. 65-74 [doi]
• Confidence Inference in Bayesian NetworksJian Cheng, Marek J. Druzdzel. 75-82 [doi]
• Semi-Instrumental Variables: A Test for Instrument AdmissibilityTianjiao Chu, Richard Scheines, Peter Spirtes. 83-90 [doi]
• Conditions Under Which Conditional Independence and Scoring Methods Lead to Identical Selection of Bayesian Network ModelsRobert G. Cowell. 91-97 [doi]
• Linearity Properties of Bayes Nets with Binary VariablesDavid Danks, Clark Glymour. 98-104 [doi]
• Using Bayesian Networks to Identify the Causal Effect of Speeding in Individual Vehicle/Pedestrian CollisionsGary A. Davis. 105-111 [doi]
• Hybrid Processing of Beliefs and ConstraintsRina Dechter, David Larkin. 112-119 [doi]
• Variational MCMCNando de Freitas, Pedro A. d. F. R. Højen-Sørensen, Stuart J. Russell. 120-127 [doi]
• Efficient Stepwise Selection in Decomposable ModelsAmol Deshpande, Minos N. Garofalakis, Michael I. Jordan. 128-135 [doi]
• Incorporating Expressive Graphical Models in VariationalApproximations: Chain-graphs and Hidden VariablesTal El-Hay, Nir Friedman. 136-143 [doi]
• Learning the Dimensionality of Hidden VariablesGal Elidan, Nir Friedman. 144-151 [doi]
• Multivariate Information BottleneckNir Friedman, Ori Mosenzon, Noam Slonim, Naftali Tishby. 152-161 [doi]
• A Comparison of Axiomatic Approaches to Qualitative Decision Making Using Possibility TheoryPhan Hong Giang, Prakash P. Shenoy. 162-170 [doi]
• Enumerating Markov Equivalence Classes of Acyclic Digraph ModelsSteven B. Gillispie, Michael D. Perlman. 171-177 [doi]
• Robust Combination of Local ControllersCarlos Guestrin, Dirk Ormoneit. 178-185 [doi]
• Similarity Measures on Preference Structures, Part II: Utility FunctionsVu A. Ha, Peter Haddawy, John Miyamoto. 186-193 [doi]
• Causes and Explanations: A Structural-Model Approach: Part 1: CausesJoseph Y. Halpern, Judea Pearl. 194-202 [doi]
• A Logic for Reasoning about Upper ProbabilitiesJoseph Y. Halpern, Riccardo Pucella. 203-210 [doi]
• A Dynamic Programming Model for Determining Bidding Strategies in Sequential Auctions: Quasi-linear Utility and Budget ConstraintsHiromitsu Hattori, Makoto Yokoo, Yuko Sakurai, Toramatsu Shintani. 211-218 [doi]
• A Clustering Approach to Solving Large Stochastic Matching ProblemsMilos Hauskrecht, Eli Upfal. 219-226 [doi]
• Discovering Multiple Constraints that are Frequently Approximately SatisfiedGeoffrey E. Hinton, Yee Whye Teh. 227-234 [doi]
• A Bayesian Approach to Tackling Hard Computational ProblemsEric Horvitz, Yongshao Ruan, Carla P. Gomes, Henry A. Kautz, Bart Selman, David Maxwell Chickering. 235-244 [doi]
• Estimating Well-Performing Bayesian Networks using Bernoulli MixturesGeoff A. Jarrad. 245-252 [doi]
• Graphical Models for Game TheoryMichael J. Kearns, Michael L. Littman, Satinder P. Singh. 253-260 [doi]
• On characterizing Inclusion of Bayesian NetworksTomás Kocka, Remco R. Bouckaert, Milan Studený. 261-268 [doi]
• Improved learning of Bayesian networksTomás Kocka, Robert Castelo. 269-276 [doi]
• Classifier Learning with Supervised Marginal LikelihoodPetri Kontkanen, Petri Myllymäki, Henry Tirri. 277-284 [doi]
• Plausible reasoning from spatial observationsJérôme Lang, Philippe Muller. 285-292 [doi]
• Iterative Markov Chain Monte Carlo Computation of Reference Priors and Minimax RiskJohn D. Lafferty, Larry A. Wasserman. 293-300 [doi]
• Hypothesis Management in Situation-Specific Network ConstructionKathryn B. Laskey, Suzanne M. Mahoney, Ed Wright. 301-309 [doi]
• Inference in Hybrid Networks: Theoretical Limits and Practical AlgorithmsUri Lerner, Ronald Parr. 310-318 [doi]
• Exact Inference in Networks with Discrete Children of Continuous ParentsUri Lerner, Eran Segal, Daphne Koller. 319-328 [doi]
• Probabilistic Logic Programming under Inheritance with OverridingThomas Lukasiewicz. 329-336 [doi]
• Solving Influence Diagrams using HUGIN, Shafer-Shenoy and Lazy PropagationAnders L. Madsen, Dennis Nilsson. 337-345 [doi]
• A Bayesian Multiresolution Independence Test for Continuous VariablesDimitris Margaritis, Sebastian Thrun. 346-353 [doi]
• Aggregating Learned Probabilistic BeliefsPedrito Maynard-Reid II, Urszula Chajewska. 354-361 [doi]
• Expectation Propagation for approximate Bayesian inferenceThomas P. Minka. 362-369 [doi]
• Recognition Networks for Approximate Inference in BN20 NetworksQuaid Morris. 370-377 [doi]
• The Factored Frontier Algorithm for Approximate Inference in DBNsKevin P. Murphy, Yair Weiss. 378-385 [doi]
• A Case Study in Knowledge Discovery and Elicitation in an Intelligent Tutoring ApplicationAnn E. Nicholson, Tal Boneh, Tim A. Wilkin, Kaye Stacey, Liz Sonenberg, Vicki Steinle. 386-394 [doi]
• Lattice Particle FiltersDirk Ormoneit, Christiane Lemieux, David J. Fleet. 395-402 [doi]
• Approximating MAP using Local SearchJames D. Park, Adnan Darwiche. 403-410 [doi]
• Direct and Indirect EffectsJudea Pearl. 411-420 [doi]
• Sufficiency, Separability and Temporal Probabilistic ModelsAvi Pfeffer. 421-428 [doi]
• Toward General Analysis of Recursive Probability ModelsDaniel Pless, George F. Luger. 429-436 [doi]
• Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data EnvironmentsAlexandrin Popescul, Lyle H. Ungar, David M. Pennock, Steve Lawrence. 437-444 [doi]
• Vector-space Analysis of Belief-state Approximation for POMDPsPascal Poupart, Craig Boutilier. 445-452 [doi]
• Value-Directed Sampling Methods for POMDPsPascal Poupart, Luis E. Ortiz, Craig Boutilier. 453-461 [doi]
• A Mixed Graphical Model for Rhythmic ParsingChristopher Raphael. 462-471 [doi]
• Decision-Theoretic Planning with Concurrent Temporally Extended ActionsKhashayar Rohanimanesh, Sridhar Mahadevan. 472-479 [doi]
• A Tractable POMDP for Dynamic Sequencing with Applications to Personalized Internet Content ProvisionPaat Rusmevichientong, Benjamin Van Roy. 480-487 [doi]
• Symmetric Collaborative Filtering Using the Noisy Sensor ModelRita Sharma, David Poole. 488-495 [doi]
• Policy Improvement for POMDPs Using Normalized Importance SamplingChristian R. Shelton. 496-503 [doi]
• Maximum Likelihood Bounded Tree-Width Markov NetworksNathan Srebro. 504-511 [doi]
• Causal Discovery from ChangesJin Tian, Judea Pearl. 512-521 [doi]
• Bayesian Error-Bars for Belief Net InferenceTim Van Allen, Russell Greiner, Peter Hooper. 522-529 [doi]
• Analysing Sensitivity Data from Probabilistic NetworksLinda C. van der Gaag, Silja Renooij. 530-537 [doi]
• The Optimal Reward Baseline for Gradient-Based Reinforcement LearningLex Weaver, Nigel Tao. 538-545 [doi]
• Cross-covariance modelling via DAGs with hidden variablesJacob A. Wegelin, Thomas Richardson. 546-553 [doi]
• Belief Optimization for Binary Networks: A Stable Alternative to Loopy Belief PropagationMax Welling, Yee Whye Teh. 554-561 [doi]
• Statistical Modeling in Continuous Speech Recognition (CSR)Steve Young. 562-571 [doi]
• Planning and Acting under Uncertainty: A New Model for Spoken Dialogue SystemBo Zhang, Qingsheng Cai, Jianfeng Mao, Baining Guo. 572-579 [doi]
• Using Temporal Data for Making RecommendationsAndrew Zimdars, David Maxwell Chickering, Christopher Meek. 580-588 [doi]