UAI 1997

57 papers

A Bayesian Approach to Learning Bayesian Networks with Local Structure David Maxwell Chickering, David Heckerman, Christopher Meek

A Scheme for Approximating Probabilistic Inference Rina Dechter, Irina Rish

A Standard Approach for Optimizing Belief Network Inference Using Query DAGs Adnan Darwiche, Gregory M. Provan

A Target Classification Decision Aid Todd Michael Mansell

Algorithm Portfolio Design: Theory vs. Practice Carla P. Gomes, Bart Selman

Algorithms for Learning Decomposable Models and Chordal Graphs Luis M. de Campos, Juan F. Huete

An Information-Theoretic Analysis of Hard and Soft Assignment Methods for Clustering Michael J. Kearns, Yishay Mansour, Andrew Y. Ng

Bayes Networks for Sonar Sensor Fusion Ami Berler, Solomon Eyal Shimony

Cognitive Processing of Causal Knowledge Scott B. Morris, Doug Cork, Richard E. Neapolitan

Composition of Probability Measures on Finite Spaces Radim Jirousek

Computational Advantages of Relevance Reasoning in Bayesian Belief Networks Yan Lin, Marek J. Druzdzel

Conditional Utility, Utility Independence, and Utility Networks Yoav Shoham

Corporate Evidential Decision Making in Performance Prediction Domains Alex G. Büchner, Werner Dubitzky, Alfons Schuster, Philippe Lopes, Peter G. O'Donoghue, John G. Hughes, David A. Bell, Kenneth Adamson, John A. White, John M. C. C. Anderson, Maurice D. Mulvenna

Correlated Action Effects in Decision Theoretic Regression Craig Boutilier

Cost-Sharing in Bayesian Knowledge Bases Solomon Eyal Shimony, Carmel Domshlak, Eugene Santos Jr.

Decision-Making Under Ordinal Preferences and Comparative Uncertainty Didier Dubois, Hélène Fargier, Henri Prade

Defining Explanation in Probabilistic Systems Urszula Chajewska, Joseph Y. Halpern

Efficient Induction of Finite State Automata Matthew S. Collins, Jonathan J. Oliver

Estimation of Effects of Sequential Treatments by Reparameterizing Directed Acyclic Graphs James M. Robins, Larry A. Wasserman

Exploiting Uncertain and Temporal Information in Correlation John Bigham

Exploring Parallelism in Learning Belief Networks Tongsheng Chu, Yang Xiang

Fast Value Iteration for Goal-Directed Markov Decision Processes Nevin Lianwen Zhang, Weihong Zhang

Image Segmentation in Video Sequences: A Probabilistic Approach Nir Friedman, Stuart Russell

Incremental mAP Generation by Low Cost Robots Based on Possibility/Necessity Grids Maite López-Sánchez, Ramón López de Mántaras, Carles Sierra

Incremental Pruning: A Simple, Fast, Exact Method for Partially Observable Markov Decision Processes Anthony R. Cassandra, Michael L. Littman, Nevin Lianwen Zhang

Independence of Causal Influence and Clique Tree Propagation Nevin Lianwen Zhang, Li Yan

Inference with Idempotent Valuations Luis D. Hernández, Serafín Moral

Learning Bayesian Nets That Perform Well Russell Greiner, Adam J. Grove, Dale Schuurmans

Learning Bayesian Networks from Incomplete Databases Marco Ramoni, Paola Sebastiani

Learning Belief Networks in Domains with Recursively Embedded Pseudo Independent Submodels Jun Hu, Yang Xiang

Lexical Access for Speech Understanding Using Minimum Message Length Encoding Ian E. Thomas, Ingrid Zukerman, Jonathan J. Oliver, David W. Albrecht, Bhavani Raskutti

Limitations of Skeptical Default Reasoning Jens Doerpmund

Model Reduction Techniques for Computing Approximately Optimal Solutions for Markov Decision Processes Thomas L. Dean, Robert Givan, Sonia M. Leach

Models and Selection Criteria for Regression and Classification David Heckerman, Christopher Meek

Myopic Value of Information in Influence Diagrams Søren L. Dittmer, Finn Verner Jensen

Nested Junction Trees Uffe Kjærulff

Network Fragments: Representing Knowledge for Constructing Probabilistic Models Kathryn B. Laskey, Suzanne M. Mahoney

Nonuniform Dynamic Discretization in Hybrid Networks Alexander V. Kozlov, Daphne Koller

Object-Oriented Bayesian Networks Daphne Koller, Avi Pfeffer

On Stable Multi-Agent Behavior in Face of Uncertainty Moshe Tennenholtz

Perception, Attention, and Resources: A Decision-Theoretic Approach to Graphics Rendering Eric Horvitz, Jed Lengyel

Probabilistic Acceptance Henry E. Kyburg Jr.

Probability Update: Conditioning vs. Cross-Entropy Adam J. Grove, Joseph Y. Halpern

Problem-Focused Incremental Elicitation of Multi-Attribute Utility Models Vu A. Ha, Peter Haddawy

Region-Based Approximations for Planning in Stochastic Domains Nevin Lianwen Zhang, Wenju Liu

Relational Bayesian Networks Manfred Jaeger

Representing Aggregate Belief Through the Competitive Equilibrium of a Securities Market David M. Pennock, Michael P. Wellman

Robustness Analysis of Bayesian Networks with Local Convex Sets of Distributions Fábio Gagliardi Cozman

Score and Information for Recursive Exponential Models with Incomplete Data Bo Thiesson

Sequential Thresholds: Context Sensitive Default Extensions Choh Man Teng

Sequential Update of Bayesian Network Structure Nir Friedman, Moisés Goldszmidt

Structure and Parameter Learning for Causal Independence and Causal Interaction Models Christopher Meek, David Heckerman

Structured Arc Reversal and Simulation of Dynamic Probabilistic Networks Adrian Y. W. Cheuk, Craig Boutilier

Support and Plausibility Degrees in Generalized Functional Models Paul-André Monney

The Complexity of Plan Existence and Evaluation in Probabilistic Domains Judy Goldsmith, Michael L. Littman, Martin Mundhenk

Time-Critical Action: Representations and Application Eric Horvitz, Adam Seiver

Update Rules for Parameter Estimation in Bayesian Networks Eric Bauer, Daphne Koller, Yoram Singer