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Rina Dechter |
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Advances in Search and Inference for Graphical ModelsTuesday morning, 17th August, 2010, Room 6.1.36
The goal of this talk is to present the algorithmic principles behind the progress that has been made in the past decade in this area in the graphical models communities such as Constraint networks and Probabilistic networks, focusing on optimization queries and likelihood and counting queries. It will focus on: (1) how bounded-inference (e.g., mini-bucket and mini-clustering schemes) can be used to generate lower-bound and upper bound approximations and on their use as heuristics for search; (2) how these heuristics are contrasted and compare with those based on linear programming and on soft arc-consistency; (3) the role of caching goods during search; (4) how problem decomposition can be incorporated into search using AND/OR search spaces; (5) how problem structure can be exploited to yield more efficient compilation schemes for probabilistic inference and post-optimality analysis. All these enhancements yield a new generation of search algorithms (e.g., branch and bound or best-first search) that can trade-off time and space using a few controlling parameters. Complexity analysis and empirical demonstration of all algorithms will be presented on variety of benchmarks for Max-CSP, for the Most Probable Explanation (MPE) task for probabilistic reasoning, for Integer Programming and for general constraint optimization tasks. Example benchmarks include radio-frequency problems, linkage analysis, combinatorial auctions, and coding networks. Short biosRina Dechter is a professor of Computer Science at the University of California, Irvine. She received her PhD in Computer Science at UCLA in 1985, an MS degree in Applied Mathematic from the Weizmann Institute and a B.S in Mathematics and Statistics from the Hebrew University, Jerusalem. Her research centers on computational aspects of automated reasoning and knowledge representation including search, constraint processing and probabilistic reasoning. Professor Dechter is an author of Constraint Processing published by Morgan Kaufmann, 2003, has authored over 100 research papers, and has served on the editorial boards of: Artificial Intelligence, the Constraint Journal, Journal of Artificial Intelligence Research and Logical Method in Computer Science (LMCS). She was awarded the Presidential Young investigator award in 1991, is a fellow of the American association of Artificial Intelligence since 1994, was a Radcliffe Fellowship 2005-2006 and received the 2007 Association of Constraint Programming (ACP) research excellence award.
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