UAI 2000

75 papers

A Bayesian Method for Causal Modeling and Discovery Under Selection Gregory F. Cooper

A Branch-and-Bound Algorithm for MDL Learning Bayesian Networks Jin Tian

A Complete Calcultis for Possibilistic Logic Programming with Fuzzy Propositional Variables Teresa Alsinet, Lluís Godo

A Decision Theoretic Approach to Targeted Advertising David Maxwell Chickering, David Heckerman

A Differential Approach to Inference in Bayesian Networks Adnan Darwiche

A Knowledge Acquisition Tool for Bayesian-Network Troubleshooters Claus Skaanning

A Principled Analysis of Merging Operations in Possibilistic Logic Souhila Kaci, Salem Benferhat, Didier Dubois, Henri Prade

A Qualitative Linear Utility Theory for Spohn's Theory of Epistemic Beliefs Phan Hong Giang, Prakash P. Shenoy

A Two-Round Variant of EM for Gaussian Mixtures Sanjoy Dasgupta, Leonard J. Schulman

Adaptive Importance Sampling for Estimation in Structured Domains Luis E. Ortiz, Leslie Pack Kaelbling

An Uncertainty Framework for Classification Loo-Nin Teow, Kia-Fock Loe

Any-Space Probabilistic Inference Adnan Darwiche

Approximately Optimal Monitoring of Plan Preconditions Craig Boutilier

Bayesian Classification and Feature Selection from Finite Data Sets Frans Coetzee, Steve Lawrence, C. Lee Giles

Being Bayesian About Network Structure Nir Friedman, Daphne Koller

Building a Stochastic Dynamic Model of Application Use Peter Gorniak, David Poole

Causal Mechanism-Based Model Constructions Tsai-Ching Lu, Marek J. Druzdzel, Tze-Yun Leong

Collaborative Filtering by Personality Diagnosis: A Hybrid Memory and Model-Based Approach David M. Pennock, Eric Horvitz, Steve Lawrence, C. Lee Giles

Combinatonal Optimization by Learning and Simulation of Bayesian Networks Pedro Larrañaga, Ramon Etxeberria, José Antonio Lozano, José M. Peña

Combining Feature and Example Pruning by Uncertainty Minimization Marc Sebban, Richard Nock

Compact Securities Markets for Pareto Optimal Reallocation of Risk David M. Pennock, Michael P. Wellman

Computational Investigation of Low-Discrepancy Sequences in Simulation Algorithms for Bayesian Networks Jian Cheng, Marek J. Druzdzel

Conditional Independence and Markov Properties in Possibility Theory Jirina Vejnarová

Conditional Plausibility Measures and Bayesian Networks Joseph Y. Halpern

Conversation as Action Under Uncertainty Tim Paek, Eric Horvitz

Credal Networks Under Maximum Entropy Thomas Lukasiewicz

Dependency Networks for Collaborative Filtering and Data Visualization David Heckerman, David Maxwell Chickering, Christopher Meek, Robert Rounthwaite, Carl Myers Kadie

Dynamic Bayesian Multinets Jeff A. Bilmes

Dynamic Trees: A Structured Variational Method Giving Efficient Propagation Rules Amos J. Storkey

Evaluating Influence Diagrams Using LIMIDs Dennis Nilsson, Steffen L. Lauritzen

Experiments with Random Projection Sanjoy Dasgupta

Exploiting Qualitative Knowledge in the Learning of Conditional Probabilities of Bayesian Networks Frank Wittig, Anthony Jameson

Fast Planning in Stochastic Games Michael J. Kearns, Yishay Mansour, Satinder Singh

Feature Selection and Dualities in Maximum Entropy Discrimination Tony Jebara, Tommi S. Jaakkola

Game Networks Pierfrancesco La Mura

Gaussian Process Networks Nir Friedman, Iftach Nachman

Inference for Belief Networks Using Coupling from the past Michael Harvey, Radford M. Neal

Learning Graphical Models of Images, Videos and Their Spatial Transformations Brendan J. Frey, Nebojsa Jojic

Learning to Cooperate via Policy Search Leonid Peshkin, Kee-Eung Kim, Nicolas Meuleau, Leslie Pack Kaelbling

Likelihood Computations Using Value Abstraction Nir Friedman, Dan Geiger, Noam Lotner

Making Sensitivity Analysis Computationally Efficient Uffe Kjærulff, Linda C. van der Gaag

Marginalization in Composed Probabilistic Models Radim Jirousek

Maximum Entropy and the Glasses You Are Looking Through Peter Grünwald

Minimum Message Length Clustering Using Gibbs Sampling Ian Davidson

Mix-Nets: Factored Mixtures of Gaussians in Bayesian Networks with Mixed Continuous and Discrete Variables Scott Davies, Andrew W. Moore

Model Criticism of Bayesian Networks with Latent Variables David M. Williamson, Russell G. Almond, Robert J. Mislevy

Model-Based Hierarchical Clustering Shivakumar Vaithyanathan, Byron Dom

Monte Carlo Inference via Greedy Importance Sampling Dale Schuurmans, Finnegan Southey

Nash Convergence of Gradient Dynamics in General-Sum Games Satinder Singh, Michael J. Kearns, Yishay Mansour

On the Use of Skeletons When Learning in Bayesian Networks Harald Steck

PEGASUS: A Policy Search Method for Large MDPs and POMDPs Andrew Y. Ng, Michael I. Jordan

Perfect Tree-like Markovian Distributions Ann Becker, Dan Geiger, Christopher Meek

Pivotal Pruning of Trade-Offs in QPNs Silja Renooij, Linda C. van der Gaag, Simon Parsons, Shaw Green

Policy Iteration for Factored MDPs Daphne Koller, Ronald Parr

Probabilistic Arc Consistency: A Connection Between Constraint Reasoning and Probabilistic Reasoning Michael C. Horsch, William S. Havens

Probabilistic Models for Agent's Beliefs and Decisions Brian Milch, Daphne Koller

Probabilistic Models for Query Approximation with Large Sparse Binary Data Sets Dmitry Pavlov, Heikki Mannila, Padhraic Smyth

Probabilistic State-Dependent Grammars for Plan Recognition David V. Pynadath, Michael P. Wellman

Probabilities of Causation: Bounds and Identification Jin Tian, Judea Pearl

Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, Stuart Russell

Representing and Solving Asymmetric Bayesian Decision Problems Thomas D. Nielsen, Finn Verner Jensen

Reversible Jump MCMC Simulated Annealing for Neural Networks Christophe Andrieu, Nando de Freitas, Arnaud Doucet

Risk Agoras: Dialectical Argumentation for Scientific Reasoning Peter McBurney, Simon Parsons

Separation Properties of Sets of Probability Measures Fábio Gagliardi Cozman

Stochastic Logic Programs: Sampling, Inference and Applications James Cussens

The Anchors Hierarchy: Using the Triangle Inequality to Survive High Dimensional Data Andrew W. Moore

The Complexity of Decentralized Control of Markov Decision Processes Daniel S. Bernstein, Shlomo Zilberstein, Neil Immerman

Tractable Bayesian Learning of Tree Belief Networks Marina Meila, Tommi S. Jaakkola

User Interface Tools for Navigation in Conditional Probability Tables and Elicitation of Probabilities in Bayesian Networks Haiqin Wang, Marek J. Druzdzel

Using ROBDDs for Inference in Bayesian Networks with Troubleshooting as an Example Thomas D. Nielsen, Pierre-Henri Wuillemin, Finn Verner Jensen, Uffe Kjærulff

Utilities as Random Variables: Density Estimation and Structure Discovery Urszula Chajewska, Daphne Koller

Value-Directed Belief State Approximation for POMDPs Pascal Poupart, Craig Boutilier

Variational Approximations Between Mean Field Theory and the Junction Tree Algorithm Wim Wiegerinck

Variational Relevance Vector Machines Christopher M. Bishop, Michael E. Tipping

YGGDRASIL-A Statistical Package for Learning Split Models Søren Højsgaard