Table of Contents

• Markov Equivalence Classes for Maximal Ancestral GraphsAyesha R. Ali, Thomas Richardson. 1-9
• Learning Hierarchical Object Maps of Non-Stationary Environments with Mobile RobotsDragomir Anguelov, Rahul Biswas, Daphne Koller, Benson Limketkai, Sebastian Thrun. 10-17
• A Constraint Satisfaction Approach to the Robust Spanning Tree Problem with Interval DataIonut D. Aron, Pascal Van Hentenryck. 18-25
• On the Construction of the Inclusion Boundary Neighbourhood for Markov Equivalence Classes of Bayesian Network StructuresVincent Auvray, Louis Wehenkel. 26-35
• Tree-dependent Component AnalysisFrancis R. Bach, Michael I. Jordan. 36-44
• Bipolar Possibilistic RepresentationsSalem Benferhat, Didier Dubois, Souhila Kaci, Henri Prade. 45-52
• Learning with Scope, with Application to Information Extraction and ClassificationDavid M. Blei, J. Andrew Bagnell, Andrew McCallum. 53-60
• Qualitative MDPs and POMDPs: An Order-Of-Magnitude ApproximationBlai Bonet, Judea Pearl. 61-68
• Introducing Variable Importance Tradeoffs into CP-NetsRonen I. Brafman, Carmel Domshlak. 69-76
• Planning under Continuous Time and Resource Uncertainty: A Challenge for AIJohn L. Bresina, Richard Dearden, Nicolas Meuleau, Sailesh Ramkrishnan, David E. Smith, Richard Washington. 77-84
• Generalized Instrumental VariablesCarlos Brito, Judea Pearl. 85-93
• Finding Optimal Bayesian NetworksDavid Maxwell Chickering, Christopher Meek. 94-102
• Complexity of Mechanism DesignVincent Conitzer, Tuomas Sandholm. 103-110
• Continuation Methods for Mixing Heterogenous SourcesAdrian Corduneanu, Tommi Jaakkola. 111-118
• Interpolating Conditional Density TreesScott Davies, Andrew W. Moore. 119-127
• Iterative Join-Graph PropagationRina Dechter, Kalev Kask, Robert Mateescu. 128-136
• An Information-Theoretic External Cluster-Validity MeasureByron Dom. 137-145
• Causes and Explanations in the Structural-Model Approach : Tractable CasesThomas Eiter, Thomas Lukasiewicz. 146-153
• The Thing that we Tried Didn t Work very Well: Deictic Representation in Reinforcement LearningSarah Finney, Peter P. Wakker, Leslie Pack Kaelbling, Tim Oates. 154-161
• Factorization of Discrete Probability DistributionsDan Geiger, Christopher Meek, Bernd Sturmfels. 162-169
• Statistical Decisions Using Likelihood Information Without Prior ProbabilitiesPhan Hong Giang, Prakash P. Shenoy. 170-178
• Reduction of Maximum Entropy Models to Hidden Markov ModelsJoshua Goodman. 179-186
• Updating ProbabilitiesPeter Grünwald, Joseph Y. Halpern. 187-196
• Distributed Planning in Hierarchical Factored MDPsCarlos Guestrin, Geoffrey J. Gordon. 197-206
• Reasoning about ExpectationJoseph Y. Halpern, Riccardo Pucella. 207-215
• Expectation Propogation for Approximate Inference in Dynamic Bayesian NetworksTom Heskes, Onno Zoeter. 216-223
• Coordinates: Probabilistic Forecasting of Presence and AvailabilityEric Horvitz, Paul Koch, Carl Myers Kadie, Andy Jacobs. 224-233
• Unconstrained Influence DiagramsFinn Verner Jensen, Marta Vomlelová. 234-241
• CFW: A Collaborative Filtering System Using Posteriors over Weights of EvidenceCarl Myers Kadie, Christopher Meek, David Heckerman. 242-250
• A Bayesian Network Scoring Metic that Is Based on Globally Uniform Parameter PriorsMehmet Kayaalp, Gregory F. Cooper. 251-258
• Efficient Nash Computation in Large Population Games with Bounded InfluenceMichael J. Kearns, Yishay Mansour. 259-266
• Dimension Correction for Hierarchical Latent Class ModelsTomás Kocka, Nevin Lianwen Zhang. 267-274
• Almost-everywhere Algorithmic Stability and Generalization ErrorSamuel Kutin, Partha Niyogi. 275-282
• Value Function Approximation in Zero-Sum Markov GamesMichail G. Lagoudakis, Ronald Parr. 283-292
• General Lower Bounds based on Computer Generated Higher Order ExpansionsMartijn A. R. Leisink, Hilbert J. Kappen. 293-300
• Monitoring a Complez Physical System using a Hybrid Dynamic Bayes NetUri Lerner, Brooks Moses, Scott Maricia, Sheila A. McIlraith, Daphne Koller. 301-310
• Polynomial Value Iteration Algorithms for Detrerminstic MDPsOmid Madani. 311-318
• Decayed MCMC FilteringBhaskara Marthi, Hanna Pasula, Stuart J. Russell, Yuval Peres. 319-326
• Formalizing Scenario AnalysisPeter McBurney, Simon Parsons. 327-334
• Staged Mixture Modelling and BoostingChristopher Meek, Bo Thiesson, David Heckerman. 335-343
• Optimal Time Bounds for Approximate ClusteringRamgopal R. Mettu, C. Greg Plaxton. 344-351
• Expectation-Propogation for the Generative Aspect ModelThomas P. Minka, John D. Lafferty. 352-359
• Real-valued All-Dimensions Search: Low-overhead Rapid Searching over Subsets of AttributesAndrew W. Moore, Jeff G. Schneider. 360-369
• Factored Particles for Scalable MonitoringBrenda Ng, Leonid Peshkin, Avi Pfeffer. 370-377
• Continuous Time Bayesian NetworksUri Nodelman, Christian R. Shelton, Daphne Koller. 378-387
• MAP Complexity Results and Approximation MethodsJames D. Park. 388-396
• Bayesian Network Classifiers in a High Dimensional FrameworkTatjana Pavlenko, Dietrich von Rosen. 397-404
• Modelling Information Incorporation in Markets, with Application to Detecting and Explaining EventsDavid M. Pennock, Sandip Debnath, Eric J. Glover, C. Lee Giles. 405-413
• Mechanism Design with Execution UncertaintyRyan Porter, Amir Ronen, Yoav Shoham, Moshe Tennenholtz. 414-421
• From Qualitative to Quantitative Probabilistic NetworksSilja Renooij, Linda C. van der Gaag. 422-429
• Inference with Seperately Specified Sets of Probabilities in Credal NetworksJosé Carlos Ferreira da Rocha, Fabio Gagliardi Cozman. 430-437
• Asymptotic Model Selection for Naive Bayesian NetworksDmitry Rusakov, Dan Geiger. 438-445
• Advances in BoostingRobert E. Schapire. 446-452
• An MDP-based Recommender SystemGuy Shani, Ronen I. Brafman, David Heckerman. 453-460
• Reinforcement Learning with Partially Known World DynamicsChristian R. Shelton. 461-468
• Unsupervised Active Learning in Large DomainsHarald Steck, Tommi Jaakkola. 469-476
• Real-Time Inference with Large-Scale Temporal Bayes NetsMasami Takikawa, Bruce D Ambrosio, Ed Wright. 477-484
• Discriminative Probabilistic Models for Relational DataBenjamin Taskar, Pieter Abbeel, Daphne Koller. 485-492
• Loopy Belief Propogation and Gibbs MeasuresSekhar Tatikonda, Michael I. Jordan. 493-500
• Anytime State-Based Solution Methods for Decision Processes with non-Markovian RewardsSylvie Thiébaux, Froduald Kabanza, John K. Slaney. 501-510
• Particle Filters in RoboticsSebastian Thrun. 511-518
• On the Testable Implications of Causal Models with Hidden VariablesJin Tian, Judea Pearl. 519-527
• Exploiting Functional Dependence in Bayesian Network InferenceJirí Vomlel. 528-535
• A New Class of upper Bounds on the Log Partition FunctionMartin J. Wainwright, Tommi Jaakkola, Alan S. Willsky. 536-543
• Decision Principles to Justify Carnap s Updating Method and to Suggest CorrectionsPeter P. Wakker. 544-551
• Adaptive Foreground and Shadow Detection in Image SequencesYang Wang, Tele Tan. 552-559
• IPF for Discrete Chain Factor GraphsWim Wiegerinck, Tom Heskes. 560-567
• Inductive Policy Selection for First-Order MDPsSung Wook Yoon, Alan Fern, Robert Givan. 568-576
• Robust Feature Selection by Mutual Information DistributionsMarco Zaffalon, Marcus Hutter. 577-584