Table of Contents

• On the Acceptability of Arguments in Preference-based ArgumentationLeila Amgoud, Claudette Cayrol. 1-7 [doi]
• Merging uncertain knowledge bases in a possibilistic logic frameworkSalem Benferhat, Claudio Sossai. 8-15 [doi]
• A Hybrid Algorithm to Compute Marginal and Joint Beliefs in Bayesian Networks and Its ComplexityMark Bloemeke, Marco Valtorta. 16-23 [doi]
• Structured Reachability Analysis for Markov Decision ProcessesCraig Boutilier, Ronen I. Brafman, Christopher W. Geib. 24-32 [doi]
• Tractable Inference for Complex Stochastic ProcessesXavier Boyen, Daphne Koller. 33-42 [doi]
• Empirical Analysis of Predictive Algorithms for Collaborative FilteringJohn S. Breese, David Heckerman, Carl Myers Kadie. 43-52 [doi]
• Query Expansion in Information Retrieval Systems using a Bayesian Network-Based ThesaurusLuis M. de Campos, Juan M. Fernández-Luna, Juan F. Huete. 53-60 [doi]
• Dealing with Uncertainty in Situation Assessment: towards a Symbolic ApproachCharles Castel, Corine Cossart, Catherine Tessier. 61-68 [doi]
• Marginalizing in Undirected Graph and Hypergraph ModelsEnrique Castillo, Juan M. Fernández-Luna, Pilar Sanmartin. 69-78 [doi]
• Utility Elicitation as a Classification ProblemUrszula Chajewska, Lise Getoor, Joseph Norman, Yuval Shahar. 79-88 [doi]
• Irrelevance and Independence Relations in quasi-Bayesian NetworksFabio Gagliardi Cozman. 89-96 [doi]
• Dynamic JointreesAdnan Darwiche. 97-104 [doi]
• On the semi-Markov Equivalence of Causal ModelsBenoit Desjardins. 105-112 [doi]
• Comparative uncertainty, belief functions and accepted beliefsDidier Dubois, Hélène Fargier, Henri Prade. 113-120 [doi]
• Qualitative Decision Theory with Sugeno IntegralsDidier Dubois, Henri Prade, Régis Sabbadin. 121-128 [doi]
• The Bayesian Structural EM AlgorithmNir Friedman. 129-138 [doi]
• Learning the Structure of Dynamic Probabilistic NetworksNir Friedman, Kevin P. Murphy, Stuart J. Russell. 139-147 [doi]
• Learning by TransductionAlexander Gammerman, Katy S. Azoury, Vladimir Vapnik. 148-155 [doi]
• Graphical Models and Exponential FamiliesDan Geiger. 156-165 [doi]
• Psychological and Normative Theories of Causal Power and the Probabilities of CausesClark Glymour. 166-172 [doi]
• Updating Sets of ProbabilitiesAdam J. Grove, Joseph Y. Halpern. 173-182 [doi]
• Minimum Encoding Approaches for Predictive ModelingPeter Grünwald, Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri. 183-192 [doi]
• Toward Case-Based Preference Elicitation: Similarity Measures on Preference StructuresVu A. Ha, Peter Haddawy. 193-201 [doi]
• Axiomatizing Causal ReasoningJoseph Y. Halpern. 202-210 [doi]
• Solving POMDPs by Searching in Policy SpaceEric A. Hansen. 211-219 [doi]
• Hierarchical Solution of Markov Decision Processes using Macro-actionsMilos Hauskrecht, Nicolas Meuleau, Leslie Pack Kaelbling, Thomas Dean, Craig Boutilier. 220-229 [doi]
• Inferring Informational Goals from Free-Text Queries: A Bayesian ApproachDavid Heckerman, Eric Horvitz. 230-237 [doi]
• Evaluating Las Vegas Algorithms: Pitfalls and RemediesHolger H. Hoos, Thomas Stützle. 238-245 [doi]
• An Anytime Algorithm for Decision Making under UncertaintyMichael C. Horsch, David Poole. 246-255 [doi]
• The Lumière Project: Bayesian User Modeling for Inferring the Goals and Needs of Software UsersEric Horvitz, Jack S. Breese, David Heckerman, David Hovel, Koos Rommelse. 256-265 [doi]
• Any Time Probabilistic Reasoning for Sensor ValidationPablo H. Ibargüengoytia, Luis Enrique Sucar, Sunil Vadera. 266-273 [doi]
• Measure Selection: Notions of Rationality and Representation IndependenceManfred Jaeger. 274-281 [doi]
• Implementing Resolute Choice Under UncertaintyJean-Yves Jaffray. 282-288 [doi]
• Dealing with uncertainty on the initial state of a Petri netIman Jarkass, Michèle Rombaut. 289-295 [doi]
• Hierarchical Mixtures-of-Experts for Exponential Family Regression Models with Generalized Linear Mean Functions: A Survey of Approximation and Consistency ResultsWenxin Jiang, Martin A. Tanner. 296-303 [doi]
• Exact Inference of Hidden Structure from Sample Data in noisy-OR NetworksMichael J. Kearns, Yishay Mansour. 304-310 [doi]
• Large Deviation Methods for Approximate Probabilistic InferenceMichael J. Kearns, Lawrence K. Saul. 311-319 [doi]
• Mixture Representations for Inference and Learning in Boltzmann MachinesNeil D. Lawrence, Christopher M. Bishop, Michael I. Jordan. 320-327 [doi]
• A Comparison of Lauritzen-Spiegelhalter, Hugin, and Shenoy-Shafer Architectures for Computing Marginals of Probability DistributionsVasilica Lepar, Prakash P. Shenoy. 328-337 [doi]
• Incremental Tradeoff Resolution in Qualitative Probabilistic NetworksChao-Lin Liu, Michael P. Wellman. 338-345 [doi]
• Using Qualitative Relationships for Bounding Probability DistributionsChao-Lin Liu, Michael P. Wellman. 346-353 [doi]
• Magic Inference Rules for Probabilistic Deduction under Taxonomic KnowledgeThomas Lukasiewicz. 354-361 [doi]
• Lazy Propagation in Junction TreesAnders L. Madsen, Finn Verner Jensen. 362-369 [doi]
• Constructing Situation Specific Belief NetworksSuzanne M. Mahoney, Kathryn B. Laskey. 370-37 [doi]
• Treatment Choice in Heterogeneous Populations Using Experiments without Covariate DataCharles F. Manski. 379-385 [doi]
• An Experimental Comparison of Several Clustering and Initialization MethodsMarina Meila, David Heckerman. 386-395 [doi]
• From Likelihood to PlausibilityPaul-André Monney. 396-403 [doi]
• A Multivariate Discretization Method for Learning Bayesian Networks from Mixed DataStefano Monti, Gregory F. Cooper. 404-413 [doi]
• Resolving Conflicting Arguments under UncertaintiesBenson Hin Kwong Ng, Kam-Fai Wong, Boon Toh Low. 414-421 [doi]
• Flexible Decomposition Algorithms for Weakly Coupled Markov Decision ProblemsRonald Parr. 422-430 [doi]
• Logarithmic Time Parallel Bayesian InferenceDavid M. Pennock. 431-438 [doi]
• Learning From What You Don t ObserveMark A. Peot, Ross D. Shachter. 439-446 [doi]
• Context-specific approximation in probabilistic inferenceDavid Poole. 447-454 [doi]
• Empirical Evaluation of Approximation Algorithms for Probabilistic DecodingIrina Rish, Kalev Kask, Rina Dechter. 455-463 [doi]
• Decision Theoretic Foundations of Graphical Model SelectionPaola Sebastiani, Marco Ramoni. 464-471 [doi]
• On the Geometry of Bayesian Graphical Models with Hidden VariablesRaffaella Settimi, Jim Q. Smith. 472-479 [doi]
• Bayes-Ball: The Rational Pastime (for Determining Irrelevance and Requisite Information in Belief Networks and Influence Diagrams)Ross D. Shachter. 480-487 [doi]
• Switching PortfoliosYoram Singer. 488-495 [doi]
• Bayesian Networks from the Point of View of Chain GraphsMilan Studený. 496-503 [doi]
• Learning Mixtures of DAG ModelsBo Thiesson, Christopher Meek, David Maxwell Chickering, David Heckerman. 504-513 [doi]
• Probabilistic Inference in Influence DiagramsNevin Lianwen Zhang. 514-522 [doi]
• Planning with Partially Observable Markov Decision Processes: Advances in Exact Solution MethodNevin Lianwen Zhang, Stephen S. Lee. 523-530 [doi]
• Flexible and Approximate Computation through State-Space ReductionAndrea Bobbio. 531-538 [doi]