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Jack S. Breese, Daphne Koller (Eds.): UAI '01: Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence, University of Washington, Seattle, Washington, USA, August 2-5, 2001. Morgan Kaufmann 2001 ISBN 1-55860-800-1- Kannan Achan, Brendan J. Frey, Ralf Koetter: A Factorized Variational Technique for Phase Unwrapping in Markov Random Field. 1-6
- Eyal Amir: Efficient Approximation for Triangulation of Minimum Treewidth. 7-15
- Nicos Angelopoulos, James Cussens: Markov Chain Monte Carlo using Tree-Based Priors on Model Structure. 16-23
- Salem Benferhat, Didier Dubois, Souhila Kaci, Henri Prade: Graphical readings of possibilistic logic bases. 24-31
- Hans L. Bodlaender, Arie M. C. A. Koster, Frank van den Eijkhof, Linda C. van der Gaag: Pre-processing for Triangulation of Probabilistic Networks. 32-39
- Blai Bonet: A Calculus for Causal Relevance. 40-47
- Blai Bonet: Instrumentality Tests Revisited. 48-55
- Craig Boutilier, Fahiem Bacchus, Ronen I. Brafman: UCP-Networks: A Directed Graphical Representation of Conditional Utilities. 56-64
- Tianjiao Chu, Richard Scheines, Peter Spirtes: Semi-Instrumental Variables: A Test for Instrument Admissibility. 83-90
- Robert G. Cowell: Conditions Under Which Conditional Independence and Scoring Methods Lead to Identical Selection of Bayesian Network Models. 91-97
- Gary A. Davis: Using Bayesian Networks to Identify the Causal Effect of Speeding in Individual Vehicle/Pedestrian Collisions. 105-111
- Amol Deshpande, Minos N. Garofalakis, Michael I. Jordan: Efficient Stepwise Selection in Decomposable Models. 128-135
- Tal El-Hay, Nir Friedman: Incorporating Expressive Graphical Models in VariationalApproximations: Chain-graphs and Hidden Variables. 136-143
- Nir Friedman, Ori Mosenzon, Noam Slonim, Naftali Tishby: Multivariate Information Bottleneck. 152-161
- Phan Hong Giang, Prakash P. Shenoy: A Comparison of Axiomatic Approaches to Qualitative Decision Making Using Possibility Theory. 162-170
- Steven B. Gillispie, Michael D. Perlman: Enumerating Markov Equivalence Classes of Acyclic Digraph Models. 171-177
- Vu A. Ha, Peter Haddawy, John Miyamoto: Similarity Measures on Preference Structures, Part II: Utility Functions. 186-193
- Joseph Y. Halpern, Judea Pearl: Causes and Explanations: A Structural-Model Approach: Part 1: Causes. 194-202
- Hiromitsu Hattori, Makoto Yokoo, Yuko Sakurai, Toramatsu Shintani: A Dynamic Programming Model for Determining Bidding Strategies in Sequential Auctions: Quasi-linear Utility and Budget Constraints. 211-218
- Milos Hauskrecht, Eli Upfal: A Clustering Approach to Solving Large Stochastic Matching Problems. 219-226
- Geoffrey E. Hinton, Yee Whye Teh: Discovering Multiple Constraints that are Frequently Approximately Satisfied. 227-234
- Eric Horvitz, Yongshao Ruan, Carla P. Gomes, Henry A. Kautz, Bart Selman, David Maxwell Chickering: A Bayesian Approach to Tackling Hard Computational Problems. 235-244
- Geoff A. Jarrad: Estimating Well-Performing Bayesian Networks using Bernoulli Mixtures. 245-252
- Tomás Kocka, Remco R. Bouckaert, Milan Studený: On characterizing Inclusion of Bayesian Networks. 261-268
- Petri Kontkanen, Petri Myllymäki, Henry Tirri: Classifier Learning with Supervised Marginal Likelihood. 277-284
- John D. Lafferty, Larry A. Wasserman: Iterative Markov Chain Monte Carlo Computation of Reference Priors and Minimax Risk. 293-300
- Kathryn B. Laskey, Suzanne M. Mahoney, Ed Wright: Hypothesis Management in Situation-Specific Network Construction. 301-309
- Uri Lerner, Ronald Parr: Inference in Hybrid Networks: Theoretical Limits and Practical Algorithms. 310-318
- Uri Lerner, Eran Segal, Daphne Koller: Exact Inference in Networks with Discrete Children of Continuous Parents. 319-328
- Thomas Lukasiewicz: Probabilistic Logic Programming under Inheritance with Overriding. 329-336
- Anders L. Madsen, Dennis Nilsson: Solving Influence Diagrams using HUGIN, Shafer-Shenoy and Lazy Propagation. 337-345
- Dimitris Margaritis, Sebastian Thrun: A Bayesian Multiresolution Independence Test for Continuous Variables. 346-353
- Thomas P. Minka: Expectation Propagation for approximate Bayesian inference. 362-369
- Quaid Morris: Recognition Networks for Approximate Inference in BN20 Networks. 370-377
- Kevin P. Murphy, Yair Weiss: The Factored Frontier Algorithm for Approximate Inference in DBNs. 378-385
- Ann E. Nicholson, Tal Boneh, Tim A. Wilkin, Kaye Stacey, Liz Sonenberg, Vicki Steinle: A Case Study in Knowledge Discovery and Elicitation in an Intelligent Tutoring Application. 386-394
- Judea Pearl: Direct and Indirect Effects. 411-420
- Avi Pfeffer: Sufficiency, Separability and Temporal Probabilistic Models. 421-428
- Alexandrin Popescul, Lyle H. Ungar, David M. Pennock, Steve Lawrence: Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data Environments. 437-444
- Pascal Poupart, Craig Boutilier: Vector-space Analysis of Belief-state Approximation for POMDPs. 445-452
- Christopher Raphael: A Mixed Graphical Model for Rhythmic Parsing. 462-471
- Khashayar Rohanimanesh, Sridhar Mahadevan: Decision-Theoretic Planning with Concurrent Temporally Extended Actions. 472-479
- Paat Rusmevichientong, Benjamin Van Roy: A Tractable POMDP for Dynamic Sequencing with Applications to Personalized Internet Content Provision. 480-487
- Christian R. Shelton: Policy Improvement for POMDPs Using Normalized Importance Sampling. 496-503
- Nathan Srebro: Maximum Likelihood Bounded Tree-Width Markov Networks. 504-511
- Linda C. van der Gaag, Silja Renooij: Analysing Sensitivity Data from Probabilistic Networks. 530-537
- Lex Weaver, Nigel Tao: The Optimal Reward Baseline for Gradient-Based Reinforcement Learning. 538-545
- Jacob A. Wegelin, Thomas S. Richardson: Cross-covariance modelling via DAGs with hidden variables. 546-553
- Max Welling, Yee Whye Teh: Belief Optimization for Binary Networks: A Stable Alternative to Loopy Belief Propagation. 554-561
- Steve Young: Statistical Modeling in Continuous Speech Recognition (CSR). 562-571
- Bo Zhang, Qingsheng Cai, Jianfeng Mao, Baining Guo: Planning and Acting under Uncertainty: A New Model for Spoken Dialogue System. 572-579
- Andrew Zimdars, David Maxwell Chickering, Christopher Meek: Using Temporal Data for Making Recommendations. 580-588
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last updated on 2013-06-19T201401 by the dblp team