19. UAI 2003: Acapulco, Mexico

• David Allen, Adnan Darwiche:
  New Advances in Inference by Recursive Conditioning. 2-10
  
• David Azari, Eric Horvitz, Susan T. Dumais, Eric Brill:
  Web-Based Question Answering: A Decision-Making Perspective. 11-19
  
• Fahiem Bacchus, Shannon Dalmao, Toniann Pitassi:
  Value Elimination: Bayesian Interence via Backtracking Search. 20-28
  
• Salem Benferhat, Sylvain Lagrue, Odile Papini:
  A possibilistic handling of partially ordered information. 29-36
  
• Bozhena Bidyuk, Rina Dechter:
  An Empirical Study of w-Cutset Sampling for Bayesian Networks. 37-46
  
• Jeff A. Bilmes, Chris D. Bartels:
  On Triangulating Dynamic Graphical Models. 47-56
  
• Christopher M. Bishop, Markus Svensén:
  Bayesian Hierarchical Mixtures of Experts. 57-64
  
• Andrea Bobbio, Stefania Montani, Luigi Portinale:
  Parametric Dependability Analysis through Probabilistic Horn Abduction. 65-72
  
• Janneke H. Bolt, Silja Renooij, Linda C. van der Gaag:
  Upgrading Ambiguous Signs in QPNs. 73-80
  
• Richard Booth, Eva Richter:
  On revising fuzzy belief bases. 81-88
  
• Craig Boutilier, Rajarshi Das, Jeffrey O. Kephart, Gerald Tesauro, William E. Walsh:
  Cooperative Negotiation in Autonomic Systems using Incremental Utility Elicitation. 89-97
  
• Craig Boutilier, Richard S. Zemel, Benjamin M. Marlin:
  Active Collaborative Filtering. 98-106
  
• Hei Chan, Adnan Darwiche:
  Reasoning about Bayesian Network Classifiers. 107-115
  
• Sanjay Chaudhuri, Thomas Richardson:
  Using the structure of d-connecting paths as a qualitative measure of the strength of dependence. 116-123
  
• David Maxwell Chickering, Christopher Meek, David Heckerman:
  Large-Sample Learning of Bayesian Networks is NP-Hard. 124-133
  
• Darya Chudova, Scott Gaffney, Padhraic Smyth:
  Probabilistic Models For Joint Clustering And Time-Warping Of Multidimensional Curves. 134-141
  
• Gert de Cooman, Marco Zaffalon:
  Updating with incomplete observations. 142-150
  
• Adrian Corduneanu, Tommi Jaakkola:
  On Information Regularization. 151-158
  
• Christopher Crick, Avi Pfeffer:
  Loopy Belief Propagation as a Basis for Communication in Sensor Networks. 159-166
  
• Denver Dash, Marek J. Druzdzel:
  Robust Independence Testing for Constraint-Based Learning of Causal Structure. 167-174
  
• Rina Dechter, Robert Mateescu:
  A Simple Insight into Iterative Belief Propagation's Success. 175-183
  
• Mathias Drton, Thomas S. Richardson:
  A New Algorithm for Maximum Likelihood Estimation in Gaussian Graphical Models for Marginal Independence. 184-191
  
• Thomas Eiter, Thomas Lukasiewicz:
  Probabilistic Reasoning about Actions in Nonmonotonic Causal Theories. 192-199
  
• Gal Elidan, Nir Friedman:
  The Information Bottleneck EM Algorithm. 200-208
  
• Zhengzhu Feng, Eric A. Hansen, Shlomo Zilberstein:
  Symbolic Generalization for On-line Planning. 209-216
  
• José Carlos Ferreira da Rocha, Fabio Gagliardi Cozman, Cassio Polpo de Campos:
  Inference in Polytrees with Sets of Probabilities. 217-224
  
• Alberto Finzi, Thomas Lukasiewicz:
  Structure-Based Causes and Explanations in the Independent Choice Logic. 225-232
  
• M. Julia Flores, José A. Gámez, Kristian G. Olesen:
  Incremental compilation of Bayesian networks. 233-240
  
• Ari Frank, Dan Geiger, Zohar Yakhini:
  A Distance-Based Branch and Bound Feature Selection Algorithm. 241-248
  
• Eibe Frank, Mark Hall, Bernhard Pfahringer:
  Locally Weighted Naive Bayes. 249-256
  
• Brendan J. Frey:
  Extending Factor Graphs so as to Unify Directed and Undirected Graphical Models. 257-264
  
• Yong Gao:
  Phase Transition of Tractability in Constraint Satisfaction and Bayesian Network Inference. 265-271
  
• Phan Hong Giang, Prakash P. Shenoy:
  Decision Making with Partially Consonant Belief Functions. 272-280
  
• Amir Globerson, Gal Chechik, Naftali Tishby:
  Sufficient Dimensionality Reduction with Irrelevance Statistics. 281-288
  
• Charles Gretton, David Price, Sylvie Thiébaux:
  Implementation and Comparison of Solution Methods for Decision Processes with Non-Markovian Rewards. 289-296
  
• Joseph Y. Halpern, Riccardo Pucella:
  A Logic for Reasoning about Evidence. 297-304
  
• Milos Hauskrecht, Tomás Singliar:
  Monte-Carlo optimizations for resource allocation problems in stochastic network systems. 305-312
  
• Tom Heskes, Kees Albers, Bert Kappen:
  Approximate Inference and Constrained Optimization. 313-320
  
• Mark Hopkins:
  Layerwidth: Analysis of a New Metric for Directed Acyclic Graphs. 321-328
  
• Rong Jin, Luo Si, ChengXiang Zhai:
  Preference-based Graphic Models for Collaborative Filtering. 329-336
  
• Shyong K. Lam, David M. Pennock, Dan Cosley, Steve Lawrence:
  1 Billion Pages = 1 Million Dollars? Mining the Web to Play "Who Wants to be a Millionaire?". 337-345
  
• David Larkin:
  Approximate Decomposition: A Method for Bounding and Estimating Probabilistic and Deterministic Queries. 346-353
  
• Gregory Lawrence, Noah J. Cowan, Stuart J. Russell:
  Efficient Gradient Estimation for Motor Control Learning. 354-361
  
• Guy Lebanon:
  Learning Riemannian Metrics. 362-369
  
• Liping Liu, Catherine Shenoy, Prakash P. Shenoy:
  A Linear Belief Function Approach to Portfolio Evaluation. 370-377
  
• Daniel J. Lizotte, Omid Madani, Russell Greiner:
  Budgeted Learning of Naive-Bayes Classifiers. 378-385
  
• Fletcher Lu, Dale Schuurmans:
  Monte Carlo Matrix Inversion Policy Evaluation. 386-393
  
• Radu Marinescu, Kalev Kask, Rina Dechter:
  Systematic vs. Non-systematic Algorithms for Solving the MPE Task. 394-402
  
• Andrew McCallum:
  Efficiently Inducing Features of Conditional Random Fields. 403-410
  
• Christopher Meek, David Maxwell Chickering:
  Practically Perfect. 411-416
  
• Nicolas Meuleau, David E. Smith:
  Optimal Limited Contingency Planning. 417-426
  
• Francisco Mugica, Àngela Nebot, Pilar Gómez:
  Dealing with Uncertainty in Fuzzy Inductive Reasoning Methodology. 427-434
  
• Jens Dalgaard Nielsen, Tomás Kocka, José Manuel Peña:
  On Local Optima in Learning Bayesian Networks. 435-442
  
• Daniel Nikovski, Matthew Brand:
  Marginalizing Out Future Passengers in Group Elevator Control. 443-450
  
• Uri Nodelman, Christian R. Shelton, Daphne Koller:
  Learning Continuous Time Bayesian Networks. 451-458
  
• James D. Park, Adnan Darwiche:
  Solving MAP Exactly using Systematic Search. 459-468
  
• Patrice Perny, Olivier Spanjaard:
  An Axiomatic Approach to Robustness in Search Problems with Multiple Scenarios. 469-476
  
• Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun:
  Policy-contingent abstraction for robust robot control. 477-484
  
• Rómer Rosales, Brendan J. Frey:
  Learning Generative Models of Similarity Matrices. 485-492
  
• Matthew Rosencrantz, Geoffrey J. Gordon, Sebastian Thrun:
  Decentralized Sensor Fusion with Distributed Particle Filters. 493-500
  
• Dmitry Rusakov, Dan Geiger:
  Automated Analytic Asymptotic Evaluation of the Marginal Likelihood for Latent Models. 501-508
  
• Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahramani:
  On the Convergence of Bound Optimization Algorithms. 509-516
  
• Vítor Santos Costa, David Page, Maleeha Qazi, James Cussens:
  CLP(BN): Constraint Logic Programming for Probabilistic Knowledge. 517-524
  
• Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller, Nir Friedman:
  Learning Module Networks. 525-534
  
• Rita Sharma, David Poole:
  Efficient Inference in Large Discrete Domains. 535-542
  
• Ricardo Bezerra de Andrade e Silva, Richard Scheines, Clark Glymour, Peter Spirtes:
  Learning Measurement Models for Unobserved Variables. 543-550
  
• Benjamin Stewart, Jonathan Ko, Dieter Fox, Kurt Konolige:
  The Revisiting Problem in Mobile Robot Map Building: A Hierarchical Bayesian Approach. 551-558
  
• Amos J. Storkey, Nigel C. Hambly, Christopher K. I. Williams, Robert G. Mann:
  Renewal Strings for Cleaning Astronomical Databases. 559-566
  
• Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin Zhao:
  Boltzmann Machine Learning with the Latent Maximum Entropy Principle. 567-574
  
• Max Welling, Richard S. Zemel, Geoffrey E. Hinton:
  Efficient Parametric Projection Pursuit Density Estimation. 575-582
  
• Eric P. Xing, Michael I. Jordan, Stuart J. Russell:
  A generalized mean field algorithm for variational inference in exponential families. 583-591
  
• Keisuke Yamazaki, Sumio Watanabe:
  Stochastic Complexity of Bayesian Networks. 592-599
  
• Chen-Hsiang Yeang, Martin Szummer:
  Markov Random Walk Representations with Continuous Distributions. 600-607
  
• Joel Young, Thomas Dean:
  Exploiting Locality in Searching the Web. 608-615
  
• Kai Yu, Anton Schwaighofer, Volker Tresp, Wei-Ying Ma, HongJiang Zhang:
  Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes. 616-623
  
• Changhe Yuan, Marek J. Druzdzel:
  An Importance Sampling Algorithm Based on Evidence Pre-propagation. 624-631
  
• Jiji Zhang, Peter Spirtes:
  Strong Faithfulness and Uniform Consistency in Causal Inference. 632-639
  

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