August 1, 1997 - August 3, 1997

Uncertainty in Artificial Intelligence (UAI) ’97

Location: Providence, Rhode Island, USA

Thursday, July 31

Time	Session
8:00–8:30	Conference and Course Registration
8:30–6:00	Full-Day Course on Uncertain Reasoning

Friday, August 1

Time	Session
8:00–8:25	Main Conference Registration
8:25–8:30	Opening Remarks Dan Geiger and Prakash P. Shenoy
8:30–9:30	Invited talk I: Local Computation Algorithms Steffen L. Lauritzen
9:30–10:30	Invited talk II: Coding Theory and Probability Propagation in Loopy Bayesian Networks Robert J. McEliece
10:30–11:00	Break
11:00–12:00	Plenary Session I: Modeling 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
12:00–1:30	Lunch
1:30–3:00	Plenary Session II: Learning & Clustering 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
3:00–3:30	Poster Session I: Overview Presentations
3:30–5:30	Poster Session I 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

Saturday, August 2

Time	Session
8:30–9:30	Invited talk III: Genetic Linkage Analysis Alejandro A. Schaffer
9:30–10:30	Plenary Session III: Markov Decision Processes 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
10:30–11:00	Break
11:00–12:00	Panel Discussion
12:00–1:30	Lunch
1:30–3:00	Plenary Session IV: Foundations 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.
3:00–3:30	Poster Session II: Overview Presentations
3:30–5:30	Poster Session II 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
7:15–9:30	UAI ’97 Dinner Banquet How I Became Uncertain Eugene Charniak

Sunday, August 3

Time	Session
8:20–9:20	Invited talk IV: Gaussian processes – a replacement for supervised neural networks? David J.C. MacKay
9:20–10:40	Plenary Session V: Applications of Uncertain Reasoning 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
10:40–11:00	Break
11:00–12:00	Panel Discussion
12:00–1:30	Lunch
1:30–3:00	Plenary Session VI: Developments in Belief and Possibility 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
3:00–3:30	Break
3:30–5:00	Plenary Session VII: Topics on Inference 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