Brown University

Providence, Rhode Island, USA

Dan Geiger and Prakash P. Shenoy

8:25-8:30am

Steffen L. Lauritzen

8:30-9:30am

Robert J. McEliece

9:30-10:30am

11:00-12:00am

**Object-Oriented Bayesian Networks**

(winner of the best student paper award)

*Daphne Koller and Avi Pfeffer***Problem-Focused Incremental Elicitation of Multi-Attribute Utility Models**

*Vu Ha and Peter Haddawy***Representing Aggregate Belief through the Competitive Equilibrium of a Securities Market**

*David M. Pennock and Michael P. Wellman*

1:30-3:00pm

**A Bayesian Approach to Learning Bayesian Networks with Local Structure**

*David Maxwell Chickering, David Heckerman, and Chris Meek***Batch and On-line Parameter Estimation in Bayesian Networks**

*Eric Bauer, Daphne Koller, and Yoram Singer***Sequential Update of Bayesian Networks Structure**

*Nir Friedman and Moises Goldszmidt***An Information-Theoretic Analysis of Hard and Soft Assignment Methods for Clustering**

*Michael Kearns, Yishay Mansour, and Andrew Ng*

3:00-3:30pm

**Algorithms for Learning Decomposable Models and Chordal Graphs**

*Luis M. de Campos and Juan F. Huete***Defining Explanation in Probabilistic Systems**

*Urszula Chajewska and Joseph Y. Halpern***Exploring Parallelism in Learning Belief Networks**

*T. Chu and Yang Xiang***Efficient Induction of Finite State Automata**

*Matthew S. Collins and Jonathon J. Oliver***A Scheme for Approximating Probabilistic Inference**

*Rina Dechter and Irina Rish***Limitations of Skeptical Default Reasoning**

*Jens Doerpmund***The Complexity of Plan Existence and Evaluation in Probabilistic Domains**

*Judy Goldsmith, Michael L. Littman, and Martin Mundhenk***Learning Bayesian Nets that Perform Well**

*Russell Greiner, Dale Schuurmans, and Adam Grove***Model Selection for Bayesian-Network Classifiers**

*David Heckerman and Christopher Meek***Time-Critical Action: Representations and Application**

*Eric Horvitz and Adam Seiver***Composition of Probability Measures on Finite Spaces**

*Radim Jirousek***Computational Advantages of Relevance Reasoning in Bayesian Belief Networks**

*Yan Lin and Marek J. Druzdzel***Support and Plausibility Degrees in Generalized Functional Models**

*Paul-Andre Monney***On Stable Multi-Agent Behavior in Face of Uncertainty**

*Moshe Tennenholtz***Cost-Sharing in Bayesian Knowledge Bases**

*Solomon Eyal Shimony, Carmel Domshlak and Eugene Santos Jr.***Independence of Causal Influence and Clique Tree Propagation**

*Nevin L. Zhang and Li Yan*

Alejandro A. Schaffer

8:30-9:30am

9:30-10:30am

**Model Reduction Techniques for Computing Approximately Optimal Solutions for Markov Decision Processes**

*Thomas Dean, Robert Givan and Sonia Leach***Incremental Pruning: A Simple, Fast, Exact Algorithm for Partially Observable Markov Decision Processes**

*Anthony Cassandra, Michael L. Littman and Nevin L. Zhang***Region-based Approximations for Planing in Stochastic Domains**

*Nevin L. Zhang and Wenju Liu*

1:30-3:00pm

**Two Senses of Utility Independence**

*Yoav Shoham***Probability Update: Conditioning vs. Cross-Entropy**

*Adam J. Grove and Joseph Y. Halpern***Probabilistic Acceptance**

*Henry E. Kyburg Jr.*

3:00-3:30pm

**Network Fragments: Representing Knowledge for Probabilistic Models**

*Kathryn Blackmond Laskey and Suzanne M. Mahoney***Correlated Action Effects in Decision Theoretic Regression**

*Craig Boutilier***A Standard Approach for Optimizing Belief-Network Inference**

*Adnan Darwiche and Gregory Provan***Myopic Value of Information for Influence Diagrams**

*Soren L. Dittmer and Finn V. Jensen***Algorithm Portfolio Design Theory vs. Practice**

*Carla P. Gomes and Bart Selman***Learning Belief Networks in Domains with Recursively Embedded Pseudo Independent Submodels**

*J. Hu and Yang Xiang***Relational Bayesian Networks**

*Manfred Jaeger***A Target Classification Decision Aid**

*Todd Michael Mansell***Structure and Parameter Learning for Causal Independence and Causal Interactions Models**

*Christopher Meek and David Heckerman***An Investigation into the Cognitive Processing of Causal Knowledge**

*Richard E. Neapolitan, Scott B. Morris, and Doug Cork***Learning Bayesian Networks from Incomplete Databases**

*Marco Ramoni and Paola Sebastiani***Incremental Map Generation by Low Cost Robots Based on Possibility/Necessity Grids**

*M. Lopez Sanchez, R. Lopez de Mantaras, and C. Sierra***Sequential Thresholds: Evolving Context of Default Extensions**

*Choh Man Teng***Score and Information for Recursive Exponential Models with Incomplete Data**

*Bo Thiesson***Fast Value Iteration for Goal-Directed Markov Decision Processes**

*Nevin L. Zhang and Weihong Zhang*

How I Became Uncertain, *Eugene Charniak
*

David J.C. MacKay

8:20-9:20am

9:20-10:40am

**Bayes Networks for Sonar Sensor Fusion**

*Ami Berler and Solomon Eyal Shimony***Image Segmentation in Video Sequences: A Probabilistic Approach**

*Nir Friedman and Stuart Russell***Lexical Access for Speech Understanding using Minimum Message Length Encoding**

*Ian Thomas, Ingrid Zukerman, Bhavani Raskutti, Jonathan Oliver, David Albrecht***Perception, Attention, and Resources: A Decision-Theoretic Approach to Graphics Rendering**

*Eric Horvitz and Jed Lengyel*

1:30-3:00pm

**Decision-making under Ordinal Preferences and Comparative Uncertainty**

*D. Dubois, H. Fargier, and H. Prade***Inference with Idempotent Valuations**

*Luis D. Hernandez and Serafin Moral***Corporate Evidential Decision Making in Performance Prediction Domains**

*A.G. Buchner, W. Dubitzky, A. Schuster, P. Lopes P.G. O'Donoghue, J.G. Hughes, D.A. Bell, K. Adamson, J.A. White, J. Anderson, M.D. Mulvenna***Exploiting Uncertain and Temporal Information in Correlation**

*John Bigham*

3:30-5:00pm

**Nonuniform Dynamic Discretization in Hybrid Networks**

*Alexander V. Kozlov and Daphne Koller***Robustness Analysis of Bayesian Networks with Local Convex Sets of Distributions**

*Fabio Cozman***Structured Arc Reversal and Simulation of Dynamic Probabilistic Networks**

*Adrian Y. W. Cheuk and Craig Boutilier***Nested Junction Trees**

*Uffe Kjaerulff*

If you have questions or comments about the UAI '97 program, contact the UAI '97 Program Chairs: Dan Geiger and Prakash P. Shenoy. For questions about the UAI '97 conference, please contact the Conference Chair, Eric Horvitz.