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ORCID16th UAI 2000: Stanford, California, USA
- Craig Boutilier, Moisés Goldszmidt:
UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30 - July 3, 2000. Morgan Kaufmann 2000, ISBN 1-55860-709-9 - Teresa Alsinet, Lluís Godo:
A Complete Calcultis for Possibilistic Logic Programming with Fuzzy Propositional Variables. 1-10 - Christophe Andrieu, Nando de Freitas, Arnaud Doucet:
Reversible Jump MCMC Simulated Annealing for Neural Networks. 11-18 - Ann Becker, Dan Geiger, Christopher Meek:
Perfect Tree-like Markovian Distributions. 19-23 - Daniel S. Bernstein, Shlomo Zilberstein, Neil Immerman:
The Complexity of Decentralized Control of Markov Decision Processes. 32-37 - Jeff A. Bilmes:
Dynamic Bayesian Multinets. 38-45 - Christopher M. Bishop, Michael E. Tipping:
Variational Relevance Vector Machines. 46-53 - Craig Boutilier:
Approximately Optimal Monitoring of Plan Preconditions. 54-62 - Urszula Chajewska, Daphne Koller:
Utilities as Random Variables: Density Estimation and Structure Discovery. 63-71 - Jian Cheng, Marek J. Druzdzel:
Computational Investigation of Low-Discrepancy Sequences in Simulation Algorithms for Bayesian Networks. 72-81 - David Maxwell Chickering, David Heckerman:
A Decision Theoretic Approach to Targeted Advertising. 82-88 - Frans Coetzee, Steve Lawrence, C. Lee Giles:
Bayesian Classification and Feature Selection from Finite Data Sets. 89-97 - Gregory F. Cooper:
A Bayesian Method for Causal Modeling and Discovery Under Selection. 98-106 - Fábio Gagliardi Cozman:
Separation Properties of Sets of Probability Measures. 107-114 - James Cussens:
Stochastic Logic Programs: Sampling, Inference and Applications. 115-122 - Adnan Darwiche:
A Differential Approach to Inference in Bayesian Networks. 123-132 - Adnan Darwiche:
Any-Space Probabilistic Inference. 133-142 - Sanjoy Dasgupta:
Experiments with Random Projection. 143-151 - Sanjoy Dasgupta, Leonard J. Schulman:
A Two-Round Variant of EM for Gaussian Mixtures. 152-159 - Ian Davidson:
Minimum Message Length Clustering Using Gibbs Sampling. 160-167 - Scott Davies, Andrew W. Moore:
Mix-nets: Factored Mixtures of Gaussians in Bayesian Networks with Mixed Continuous And Discrete Variables. 168-175 - Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, Stuart Russell:
Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks. 176-183 - Brendan J. Frey, Nebojsa Jojic:
Learning Graphical Models of Images, Videos and Their Spatial Transformations. 184-191 - Nir Friedman, Dan Geiger, Noam Lotner:
Likelihood Computations Using Value Abstraction. 192-200 - Nir Friedman, Daphne Koller:
Being Bayesian about Network Structure. 201-210 - Nir Friedman, Iftach Nachman:
Gaussian Process Networks. 211-219 - Phan Hong Giang, Prakash P. Shenoy:
A Qualitative Linear Utility Theory for Spohn's Theory of Epistemic Beliefs. 220-229 - Peter Gorniak, David Poole:
Building a Stochastic Dynamic Model of Application Use. 230-237 - Peter Grünwald:
Maximum Entropy and the Glasses You are Looking Through. 238-246 - Joseph Y. Halpern:
Conditional Plausibility Measures and Bayesian Networks. 247-255 - Michael Harvey, Radford M. Neal:
Inference for Belief Networks Using Coupling From the Past. 256-263 - David Heckerman, David Maxwell Chickering, Christopher Meek, Robert Rounthwaite, Carl Myers Kadie:
Dependency Networks for Collaborative Filtering and Data Visualization. 264-273 - Søren Højsgaard:
YGGDRASIL-A statistical package for learning Split Models. 274-281 - Michael C. Horsch, William S. Havens:
Probabilistic Arc Consistency: A Connection between Constraint Reasoning and Probabilistic Reasoning. 282-290 - Tony Jebara, Tommi S. Jaakkola:
Feature Selection and Dualities in Maximum Entropy Discrimination. 291-300 - Radim Jirousek:
Marginalization in Composed Probabilistic Models. 301-308 - Souhila Kaci, Salem Benferhat, Didier Dubois, Henri Prade:
A principled analysis of merging operations in possibilistic logic. 24-31 - Michael J. Kearns, Yishay Mansour, Satinder Singh:
Fast Planning in Stochastic Games. 309-316 - Uffe Kjærulff, Linda C. van der Gaag:
Making Sensitivity Analysis Computationally Efficient. 317-325 - Daphne Koller, Ronald Parr:
Policy Iteration for Factored MDPs. 326-334 - Pierfrancesco La Mura:
Game Networks. 335-342 - Pedro Larrañaga, Ramon Etxeberria, José Antonio Lozano, José M. Peña:
Combinatonal Optimization by Learning and Simulation of Bayesian Networks. 343-352 - Tsai-Ching Lu, Marek J. Druzdzel, Tze-Yun Leong:
Causal Mechanism-based Model Constructions. 353-362 - Thomas Lukasiewicz:
Credal Networks under Maximum Entropy. 363-370 - Peter McBurney, Simon Parsons:
Risk Agoras: Dialectical Argumentation for Scientific Reasoning. 371-379 - Marina Meila, Tommi S. Jaakkola:
Tractable Bayesian Learning of Tree Belief Networks. 380-388 - Brian Milch, Daphne Koller:
Probabilistic Models for Agent's Beliefs and Decisions. 389-396 - Andrew W. Moore:
The Anchors Hierarchy: Using the Triangle Inequality to Survive High Dimensional Data. 397-405 - Andrew Y. Ng, Michael I. Jordan:
PEGASUS: A policy search method for large MDPs and POMDPs. 406-415 - Thomas D. Nielsen, Finn Verner Jensen:
Representing and Solving Asymmetric Bayesian Decision Problems. 416-425 - Thomas D. Nielsen, Pierre-Henri Wuillemin, Finn Verner Jensen, Uffe Kjærulff:
Using ROBDDs for Inference in Bayesian Networks with Troubleshooting as an Example. 426-435 - Dennis Nilsson, Steffen L. Lauritzen:
Evaluating Influence Diagrams using LIMIDs. 436-445 - Luis E. Ortiz, Leslie Pack Kaelbling:
Adaptive Importance Sampling for Estimation in Structured Domains. 446-454 - Tim Paek, Eric Horvitz:
Conversation as Action Under Uncertainty. 455-464 - Dmitry Pavlov, Heikki Mannila, Padhraic Smyth:
Probabilistic Models for Query Approximation with Large Sparse Binary Data Sets. 465-472 - David M. Pennock, Eric Horvitz, Steve Lawrence, C. Lee Giles:
Collaborative Filtering by Personality Diagnosis: A Hybrid Memory and Model-Based Approach. 473-480 - David M. Pennock, Michael P. Wellman:
Compact Securities Markets for Pareto Optimal Reallocation of Risk. 481-488 - Leonid Peshkin, Kee-Eung Kim, Nicolas Meuleau, Leslie Pack Kaelbling:
Learning to Cooperate via Policy Search. 489-496 - Pascal Poupart, Craig Boutilier:
Value-Directed Belief State Approximation for POMDPs. 497-506 - David V. Pynadath, Michael P. Wellman:
Probabilistic State-Dependent Grammars for Plan Recognition. 507-514 - Silja Renooij, Linda C. van der Gaag, Simon Parsons, Shaw Green:
Pivotal Pruning of Trade-offs in QPNs. 515-522 - Dale Schuurmans, Finnegan Southey:
Monte Carlo inference via greedy importance sampling. 523-532 - Marc Sebban, Richard Nock:
Combining Feature and Example Pruning by Uncertainty Minimization. 533-540 - Satinder Singh, Michael J. Kearns, Yishay Mansour:
Nash Convergence of Gradient Dynamics in General-Sum Games. 541-548 - Claus Skaanning:
A Knowledge Acquisition Tool for Bayesian-Network Troubleshooters. 549-557 - Harald Steck:
On the Use of Skeletons when Learning in Bayesian Networks. 558-565 - Amos J. Storkey:
Dynamic Trees: A Structured Variational Method Giving Efficient Propagation Rules. 566-573 - Loo-Nin Teow, Kia-Fock Loe:
An Uncertainty Framework for Classification. 574-579 - Jin Tian:
A Branch-and-Bound Algorithm for MDL Learning Bayesian Networks. 580-588 - Jin Tian, Judea Pearl:
Probabilities of Causation: Bounds and Identification. 589-598 - Shivakumar Vaithyanathan, Byron Dom:
Model-Based Hierarchical Clustering. 599-608 - Jirina Vejnarová:
Conditional Independence and Markov Properties in Possibility Theory. 609-616 - Haiqin Wang, Marek J. Druzdzel:
User Interface Tools for Navigation in Conditional Probability Tables and Elicitation of Probabilities in Bayesian Networks. 617-625 - Wim Wiegerinck:
Variational Approximations between Mean Field Theory and the Junction Tree Algorithm. 626-633 - David M. Williamson, Russell G. Almond, Robert J. Mislevy:
Model Criticism of Bayesian Networks with Latent Variables. 634-643 - Frank Wittig, Anthony Jameson:
Exploiting Qualitative Knowledge in the Learning of Conditional Probabilities of Bayesian Networks. 644-652
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