Table of Contents

• New Advances in Inference by Recursive ConditioningDavid Allen, Adnan Darwiche. 2-10
• Web-Based Question Answering: A Decision-Making PerspectiveDavid Azari, Eric Horvitz, Susan T. Dumais, Eric Brill. 11-19
• Value Elimination: Bayesian Interence via Backtracking SearchFahiem Bacchus, Shannon Dalmao, Toniann Pitassi. 20-28
• A possibilistic handling of partially ordered informationSalem Benferhat, Sylvain Lagrue, Odile Papini. 29-36
• An Empirical Study of w-Cutset Sampling for Bayesian NetworksBozhena Bidyuk, Rina Dechter. 37-46
• On Triangulating Dynamic Graphical ModelsJeff A. Bilmes, Chris Bartels. 47-56
• Bayesian Hierarchical Mixtures of ExpertsChristopher M. Bishop, Markus Svensén. 57-64
• Parametric Dependability Analysis through Probabilistic Horn AbductionAndrea Bobbio, Stefania Montani, Luigi Portinale. 65-72
• Upgrading Ambiguous Signs in QPNsJanneke H. Bolt, Silja Renooij, Linda C. van der Gaag. 73-80
• On revising fuzzy belief basesRichard Booth, Eva Richter. 81-88
• Cooperative Negotiation in Autonomic Systems using Incremental Utility ElicitationCraig Boutilier, Rajarshi Das, Jeffrey O. Kephart, Gerald Tesauro, William E. Walsh. 89-97
• Active Collaborative FilteringCraig Boutilier, Richard S. Zemel, Benjamin Marlin. 98-106
• Reasoning about Bayesian Network ClassifiersHei Chan, Adnan Darwiche. 107-115
• Using the structure of d-connecting paths as a qualitative measure of the strength of dependenceSanjay Chaudhuri, Thomas Richardson. 116-123
• Large-Sample Learning of Bayesian Networks is NP-HardDavid Maxwell Chickering, Christopher Meek, David Heckerman. 124-133
• Probabilistic Models For Joint Clustering And Time-Warping Of Multidimensional CurvesDarya Chudova, Scott Gaffney, Padhraic Smyth. 134-141
• Updating with incomplete observationsGert de Cooman, Marco Zaffalon. 142-150
• On Information RegularizationAdrian Corduneanu, Tommi Jaakkola. 151-158
• Loopy Belief Propagation as a Basis for Communication in Sensor NetworksChristopher Crick, Avi Pfeffer. 159-166
• Robust Independence Testing for Constraint-Based Learning of Causal StructureDenver Dash, Marek J. Druzdzel. 167-174
• A Simple Insight into Iterative Belief Propagation s SuccessRina Dechter, Robert Mateescu. 175-183
• A New Algorithm for Maximum Likelihood Estimation in Gaussian Graphical Models for Marginal IndependenceMathias Drton, Thomas S. Richardson. 184-191
• Probabilistic Reasoning about Actions in Nonmonotonic Causal TheoriesThomas Eiter, Thomas Lukasiewicz. 192-199
• The Information Bottleneck EM AlgorithmGal Elidan, Nir Friedman. 200-208
• Symbolic Generalization for On-line PlanningZhengzhu Feng, Eric A. Hansen, Shlomo Zilberstein. 209-216
• Inference in Polytrees with Sets of ProbabilitiesJosé Carlos Ferreira da Rocha, Fabio Gagliardi Cozman, Cassio Polpo de Campos. 217-224
• Structure-Based Causes and Explanations in the Independent Choice LogicAlberto Finzi, Thomas Lukasiewicz. 225-232
• Incremental compilation of Bayesian networksM. Julia Flores, José A. Gámez, Kristian G. Olesen. 233-240
• A Distance-Based Branch and Bound Feature Selection AlgorithmAri Frank, Dan Geiger, Zohar Yakhini. 241-248
• Locally Weighted Naive BayesEibe Frank, Mark Hall, Bernhard Pfahringer. 249-256
• Extending Factor Graphs so as to Unify Directed and Undirected Graphical ModelsBrendan J. Frey. 257-264
• Phase Transition of Tractability in Constraint Satisfaction and Bayesian Network InferenceYong Gao. 265-271
• Decision Making with Partially Consonant Belief FunctionsPhan Hong Giang, Prakash P. Shenoy. 272-280
• Sufficient Dimensionality Reduction with Irrelevance StatisticsAmir Globerson, Gal Chechik, Naftali Tishby. 281-288
• Implementation and Comparison of Solution Methods for Decision Processes with Non-Markovian RewardsCharles Gretton, David Price, Sylvie Thiébaux. 289-296
• A Logic for Reasoning about EvidenceJoseph Y. Halpern, Riccardo Pucella. 297-304
• Monte-Carlo optimizations for resource allocation problems in stochastic network systemsMilos Hauskrecht, Tomás Singliar. 305-312
• Approximate Inference and Constrained OptimizationTom Heskes, Kees Albers, Bert Kappen. 313-320
• Layerwidth: Analysis of a New Metric for Directed Acyclic GraphsMark Hopkins. 321-328
• Preference-based Graphic Models for Collaborative FilteringRong Jin, Luo Si, ChengXiang Zhai. 329-336
• 1 Billion Pages = 1 Million Dollars? Mining the Web to Play Who Wants to be a Millionaire? Shyong K. Lam, David M. Pennock, Dan Cosley, Steve Lawrence. 337-345
• Approximate Decomposition: A Method for Bounding and Estimating Probabilistic and Deterministic QueriesDavid Larkin. 346-353
• Efficient Gradient Estimation for Motor Control LearningGregory Lawrence, Noah J. Cowan, Stuart J. Russell. 354-361
• Learning Riemannian MetricsGuy Lebanon. 362-369
• A Linear Belief Function Approach to Portfolio EvaluationLiping Liu, Catherine Shenoy, Prakash P. Shenoy. 370-377
• Budgeted Learning of Naive-Bayes ClassifiersDaniel J. Lizotte, Omid Madani, Russell Greiner. 378-385
• Monte Carlo Matrix Inversion Policy EvaluationFletcher Lu, Dale Schuurmans. 386-393
• Systematic vs. Non-systematic Algorithms for Solving the MPE TaskRadu Marinescu 0002, Kalev Kask, Rina Dechter. 394-402
• Efficiently Inducing Features of Conditional Random FieldsAndrew McCallum. 403-410
• Practically PerfectChristopher Meek, David Maxwell Chickering. 411-416
• Optimal Limited Contingency PlanningNicolas Meuleau, David E. Smith. 417-426
• Dealing with Uncertainty in Fuzzy Inductive Reasoning MethodologyFrancisco Mugica, Àngela Nebot, Pilar Gómez. 427-434
• On Local Optima in Learning Bayesian NetworksJens D. Nielsen, Tomás Kocka, José Manuel Peña. 435-442
• Marginalizing Out Future Passengers in Group Elevator ControlDaniel Nikovski, Matthew Brand. 443-450
• Learning Continuous Time Bayesian NetworksUri Nodelman, Christian R. Shelton, Daphne Koller. 451-458
• Solving MAP Exactly using Systematic SearchJames D. Park, Adnan Darwiche. 459-468
• An Axiomatic Approach to Robustness in Search Problems with Multiple ScenariosPatrice Perny, Olivier Spanjaard. 469-476
• Policy-contingent abstraction for robust robot controlJoelle Pineau, Geoffrey J. Gordon, Sebastian Thrun. 477-484
• Learning Generative Models of Similarity MatricesRómer Rosales, Brendan J. Frey. 485-492
• Decentralized Sensor Fusion with Distributed Particle FiltersMatthew Rosencrantz, Geoffrey J. Gordon, Sebastian Thrun. 493-500
• Automated Analytic Asymptotic Evaluation of the Marginal Likelihood for Latent ModelsDmitry Rusakov, Dan Geiger. 501-508
• On the Convergence of Bound Optimization AlgorithmsRuslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahramani. 509-516
• CLP(BN): Constraint Logic Programming for Probabilistic KnowledgeVítor Santos Costa, David Page, Maleeha Qazi, James Cussens. 517-524
• Learning Module NetworksEran Segal, Dana Pe er, Aviv Regev, Daphne Koller, Nir Friedman. 525-534
• Efficient Inference in Large Discrete DomainsRita Sharma, David Poole. 535-542
• Learning Measurement Models for Unobserved VariablesRicardo Bezerra de Andrade e Silva, Richard Scheines, Clark Glymour, Peter Spirtes. 543-550
• The Revisiting Problem in Mobile Robot Map Building: A Hierarchical Bayesian ApproachBenjamin Stewart, Jonathan Ko, Dieter Fox, Kurt Konolige. 551-558
• Renewal Strings for Cleaning Astronomical DatabasesAmos J. Storkey, Nigel C. Hambly, Christopher K. I. Williams, Robert G. Mann. 559-566
• Boltzmann Machine Learning with the Latent Maximum Entropy PrincipleShaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin Zhao. 567-574
• Efficient Parametric Projection Pursuit Density EstimationMax Welling, Richard S. Zemel, Geoffrey E. Hinton. 575-582
• A generalized mean field algorithm for variational inference in exponential familiesEric P. Xing, Michael I. Jordan, Stuart J. Russell. 583-591
• Stochastic Complexity of Bayesian NetworksKeisuke Yamazaki, Sumio Watanabe. 592-599
• Markov Random Walk Representations with Continuous DistributionsChen-Hsiang Yeang, Martin Szummer. 600-607
• Exploiting Locality in Searching the WebJoel Young, Thomas Dean. 608-615
• Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical BayesKai Yu, Anton Schwaighofer, Volker Tresp, Wei-Ying Ma, HongJiang Zhang. 616-623
• An Importance Sampling Algorithm Based on Evidence Pre-propagationChanghe Yuan, Marek J. Druzdzel. 624-631
• Strong Faithfulness and Uniform Consistency in Causal InferenceJiji Zhang, Peter Spirtes. 632-639