19. UAI 2003: Acapulco, Mexico
Christopher Meek, Uffe Kjærulff (Eds.): 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 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
- Andrea Bobbio, Stefania Montani, Luigi Portinale: Parametric Dependability Analysis through Probabilistic Horn Abduction. 65-72
- Craig Boutilier, Rajarshi Das, Jeffrey O. Kephart, Gerald Tesauro, William E. Walsh: Cooperative Negotiation in Autonomic Systems using Incremental Utility Elicitation. 89-97
- 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
- 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
- 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
- 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
- Milos Hauskrecht, Tomás Singliar: Monte-Carlo optimizations for resource allocation problems in stochastic network systems. 305-312
- 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
- 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
- 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
- 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
- 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
- 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
- Chen-Hsiang Yeang, Martin Szummer: Markov Random Walk Representations with Continuous Distributions. 600-607
- 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
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last updated on 2013-06-18T214307 by the dblp team