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19th UAI 2003: Acapulco, Mexico
- Christopher Meek, Uffe Kjærulff:
UAI '03, Proceedings of the 19th Conference in Uncertainty in Artificial Intelligence, Acapulco, Mexico, August 7-10 2003. Morgan Kaufmann 2003, ISBN 0-127-05664-5 - 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 S. 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, Fábio 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 A. 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 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 M. 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 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 L. 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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