21. UAI 2005: Edinburgh, Scotland, UK

• Shuchi Chawla, Cynthia Dwork, Frank McSherry, Kunal Talwar:
  On Privacy-Preserving Histograms.
  
• Pieter Abbeel, Daphne Koller, Andrew Y. Ng:
  Learning Factor Graphs in Polynomial Time & Sample Complexity. 1-9
  
• Ayesha R. Ali, Thomas S. Richardson, Peter Spirtes, Jiji Zhang:
  Towards Characterizing Markov Equivalence Classes for Directed Acyclic Graphs with Latent Variables. 10-17
  
• Eric Altendorf, Angelo C. Restificar, Thomas G. Dietterich:
  Learning from Sparse Data by Exploiting Monotonicity Constraints. 18-26
  
• Leila Amgoud:
  A Unified Setting for Inference and Decision: An Argumentation-based Approach. 26-33
  
• Itai Ashlagi, Dov Monderer, Moshe Tennenholtz:
  On the Value of Correlation. 34-41
  
• Darius Braziunas, Craig Boutilier:
  Local Utility Elicitation in GAI Models. 42-49
  
• Jonathan Bredin, David C. Parkes:
  Models for Truthful Online Double Auctions. 50-59
  
• Daniel Bryce, Subbarao Kambhampati:
  Cost Sensitive Reachability Heuristics for Handling State Uncertainty. 60-68
  
• Ryszard Kowalczyk:
  Efficient Algorithm for Estimation of Qualitative Expected Utility in Possibilistic Case-based Reasoning. 69-76
  
• Zhihong Cai, Manabu Kuroki:
  Counterfactual Reasoning in Linear Structural Equation Models. 77-84
  
• Peter Carbonetto, Jacek Kisynski, Nando de Freitas, David Poole:
  Nonparametric Bayesian Logic. 85-93
  
• Jennifer Carlson, Robin R. Murphy:
  Use of Dempster-Shafer Conflict Metric to Detect Interpretation Inconsistency. 94-103
  
• Krishnendu Chatterjee, Thomas A. Henzinger, Ranjit Jhala, Rupak Majumdar:
  Counterexample-guided Planning. 104-111
  
• Mark Chavira, David Allen, Adnan Darwiche:
  Exploiting Evidence in Probabilistic Inference. 112-127
  
• Adnan Darwiche, Hei Chan, Arthur Choi:
  On Bayesian Network Approximation by Edge Deletion. 128-135
  
• Barry R. Cobb, Prakash P. Shenoy:
  Hybrid Bayesian Networks with Linear Deterministic Variables. 136-144
  
• Vincent Conitzer, Tuomas Sandholm:
  Common Voting Rules as Maximum Likelihood Estimators. 145-152
  
• Cassio Polpo de Campos, Fabio Gagliardi Cozman:
  Belief Updating and Learning in Semi-Qualitative Probabilistic Networks. 153-160
  
• Peter R. de Waal, Linda C. van der Gaag:
  Stable Independence in Perfect Maps. 161-168
  
• Carmel Domshlak, Thorsten Joachims:
  Unstructuring User Preferences: Efficient Non-Parametric Utility Revelation. 169-177
  
• Frederick Eberhardt, Clark Glymour, Richard Scheines:
  On the Number of Experiments Sufficient and in the Worst Case Necessary to Identify All Causal Relations Among N Variables. 178-184
  
• Eyal Even-Dar, Sham M. Kakade, Yishay Mansour:
  Planning in POMDPs Using Multiplicity Automata. 185-192
  
• A. J. Feelders, Linda C. van der Gaag:
  Learning Bayesian Network Parameters with Prior Knowledge about Context-Specific Qualitative Influences. 193-200
  
• Norm Ferns, Prakash Panangaden, Doina Precup:
  Metrics for Markov Decision Processes with Infinite State Spaces. 201-208
  
• Vibhav Gogate, Rina Dechter:
  Approximate Inference Algorithms for Hybrid Bayesian Networks with Discrete Constraints. 209-216
  
• Vibhav Gogate, Rina Dechter, Bozhena Bidyuk, Craig Rindt, James Marca:
  Modeling Transportation Routines using Hybrid Dynamic Mixed Networks. 217-224
  
• Gianluigi Greco, Francesco Scarcello:
  Bounding the Uncertainty of Graphical Games: The Complexity of Simple Requirements, Pareto and Strong Nash Equilibria. 225-232
  
• Yuhong Guo, Dana F. Wilkinson, Dale Schuurmans:
  Maximum Margin Bayesian Networks. 233-242
  
• Joseph Y. Halpern, Riccardo Pucella:
  Evidence with Uncertain Likelihoods. 243-250
  
• Rafay Hammid, Siddhartha Maddi, Amos Y. Johnson, Aaron F. Bobick, Irfan A. Essa, Charles Lee Isbell Jr.:
  Unsupervised Activity Discovery and Characterization From Event-Streams. 251-258
  
• Markus Harva, Tapani Raiko, Antti Honkela, Harri Valpola, Juha Karhunen:
  Bayes Blocks: An Implementation of the Variational Bayesian Building Blocks Framework. 259-266
  
• Shen-Shyang Ho, Harry Wechsler:
  On the Detection of Concept Changes in Time-Varying Data Stream by Testing Exchangeability. 267-274
  
• Eric Horvitz, Johnson Apacible, Raman Sarin, Lin Liao:
  Prediction, Expectation, and Surprise: Methods, Designs, and Study of a Deployed Traffic Forecasting Service. 275-283
  
• Changsung Kang, Jin Tian:
  Local Markov Property for Models Satisfying Composition Axiom. 284-291
  
• Eldar Karabaev, Olga Skvortsova:
  A Heuristic Search Algorithm for Solving First-Order MDPs. 292-299
  
• Kristian Kersting, Tapani Raiko:
  "Say EM" for Selecting Probabilistic Models for Logical Sequences. 300-307
  
• Mike Klaas, Nando de Freitas, Arnaud Doucet:
  Toward Practical N2 Monte Carlo: the Marginal Particle Filter. 308-315
  
• Vladimir Kolmogorov, Martin J. Wainwright:
  On the Optimality of Tree-reweighted Max-product Message-passing. 316-323
  
• Andreas Krause, Carlos Guestrin:
  Near-optimal Nonmyopic Value of Information in Graphical Models. 324-331
  
• Nando de Freitas, Hendrik Kück:
  Learning about Individuals from Group Statistics. 332-339
  
• Manabu Kuroki, Zhihong Cai, Hiroki Motogaito:
  The Graphical Identification for Total Effects by using Surrogate Variables. 340-345
  
• Kathryn B. Laskey, Paulo Cesar G. da Costa:
  Of Starships and Klingons: Bayesian Logic for the 23rd Century. 346-353
  
• Yaxin Liu, Sven Koenig:
  Existence and Finiteness Conditions for Risk-Sensitive Planning: Results and Conjectures. 354-363
  
• Andres Madsen:
  A Differential Semantics of Lazy AR Propagation. 364-371
  
• Sridhar Mahadevan:
  Representation Policy Iteration. 372-379
  
• Robert Mateescu, Rina Dechter:
  The Relationship Between AND/OR Search and Variable Elimination. 380-387
  
• Andrew McCallum, Kedar Bellare, Fernando C. N. Pereira:
  A Conditional Random Field for Discriminatively-trained Finite-state String Edit Distance. 388-395
  
• Joris M. Mooij, Hilbert J. Kappen:
  Sufficient Conditions for Convergence of Loopy Belief Propagation. 396-403
  
• Mukund Narasimhan, Jeff A. Bilmes:
  A Submodular-supermodular Procedure with Applications to Discriminative Structure Learning. 404-412
  
• Alexandru Niculescu-Mizil, Rich Caruana:
  Obtaining Calibrated Probabilities from Boosting. 413-
  
• Uri Nodelman, Christian R. Shelton, Daphne Koller:
  Expectation Maximization and Complex Duration Distributions for Continuous Time Bayesian Networks.
  
• Uri Nodelman, Daphne Koller, Christian R. Shelton:
  Expectation Propagation for Continuous Time Bayesian Networks. 431-440
  
• Anna Osepayshvili, Michael P. Wellman, Daniel M. Reeves, Jeffrey K. MacKie-Mason:
  Self-Confirming Price Prediction for Bidding in Simultaneous Ascending Auctions. 441-449
  
• Mark Paskin, Sebastian Thrun:
  Robotic Mapping with Polygonal Random Fields. 450-458
  
• Yun Peng, Zhongli Ding:
  Modifying Bayesian Networks by Probability Constraints. 459-466
  
• Avi Pfeffer, Terry Tai:
  Asynchronous Dynamic Bayesian Networks. 467-476
  
• Guilin Qi, Weiru Liu, David A. Bell:
  A Revision-Based Approach to Resolving Conflicting Information. 477-484
  
• Silja Renooij, Linda C. van der Gaag:
  Exploiting Evidence-dependent Sensitivity Bounds. 485-492
  
• Michal Rosen-Zvi, Michael I. Jordan, Alan L. Yuille:
  The DLR Hierarchy of Approximate Inference. 493-500
  
• Matthew R. Rudary, Satinder P. Singh, David Wingate:
  Predictive Linear-Gaussian Models of Stochastic Dynamical Systems. 501-508
  
• Scott Sanner, Craig Boutilier:
  Approximate Linear Programming for First-order MDPs. 509-517
  
• Eerika Savia, Kai Puolamäki, Janne Sinkkonen, Samuel Kaski:
  Two-Way Latent Grouping Model for User Preference Prediction. 518-524
  
• Shohei Shimizu, Aapo Hyvärinen, Yutaka Kano, Patrik O. Hoyer:
  Discovery of Non-gaussian Linear Causal Models using ICA. 525-533
  
• Susan M. Shortreed, Marina Meila:
  Unsupervised Spectral Learning. 534-541
  
• Trey Smith, Reid G. Simmons:
  Point-Based POMDP Algorithms: Improved Analysis and Implementation. 542-547
  
• Marc Teyssier, Daphne Koller:
  Ordering-Based Search: A Simple and Effective Algorithm for Learning Bayesian Networks. 548-549
  
• Finnegan Southey, Michael H. Bowling, Bryce Larson, Carmelo Piccione, Neil Burch, Darse Billings, D. Chris Rayner:
  Bayes? Bluff: Opponent Modelling in Poker. 550-558
  
• Umberto Straccia:
  Description Logics with Fuzzy Concrete Domains. 559-567
  
• Charles A. Sutton, Andrew McCallum:
  Piecewise Training for Undirected Models. 568-575
  
• Daniel Szer, François Charpillet, Shlomo Zilberstein:
  MAA*: A Heuristic Search Algorithm for Solving Decentralized POMDPs. 576-590
  
• Jin Tian:
  Generating Markov Equivalent Maximal Ancestral Graphs by Single Edge Replacement. 591-598
  
• Segev Wasserkrug, Avigdor Gal, Opher Etzion:
  A Model for Reasoning with Uncertain Rules in Event Composition Systems. 599-608
  
• Max Welling, Thomas P. Minka, Yee Whye Teh:
  Structured Region Graphs: Morphing EP into GBP. 609-614
  
• Paul Weng:
  Qualitative Decision Making Under Possibilistic Uncertainty: Toward more Discriminating Criteria. 615-622
  
• John R. Wicks, Amy Greenwald:
  An Algorithm for Computing Stochastically Stable Distributions with Applications to Multiagent Learning in Repeated Games. 623-632
  
• Eric P. Xing, Rong Yan, Alexander G. Hauptmann:
  Mining Associated Text and Images with Dual-Wing Harmoniums. 633-641
  
• Huizhen Yu:
  A Function Approximation Approach to Estimation of Policy Gradient for POMDP with Structured Policies. 642-657
  
• Luke S. Zettlemoyer, Michael Collins:
  Learning to Map Sentences to Logical Form: Structured Classification with Probabilistic Categorial Grammars. 658-666
  
• Jiji Zhang, Peter Spirtes:
  A Transformational Characterization of Markov Equivalence for Directed Acyclic Graphs with Latent Variables. 667-674
  
• Alice X. Zheng, Irina Rish, Alina Beygelzimer:
  Efficient Test Selection in Active Diagnosis via Entropy Approximation. 675-
  

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