[AI Seminar] AI Seminar -- Professor Rina Dechter -- April 26, 2016

Ellen Vitercik vitercik at cs.cmu.edu
Mon Apr 25 09:50:55 EDT 2016

This is a reminder that this talk is tomorrow, Tuesday, April 26th.


On Wed, Apr 20, 2016 at 1:44 PM, Ellen Vitercik <vitercik at cs.cmu.edu> wrote:

> Dear faculty and students,
> We look forward to seeing you this Tuesday, April 26th, at noon in NSH
> 3305 for AI Seminar. To learn more about the seminar and lunch, or to
> volunteer to give a talk, please visit the AI Lunch webpage
> <http://www.cs.cmu.edu/~aiseminar/>. *We are looking for someone to give
> a talk on May 10th*.
> UC Irvine Professor Rina Dechter <http://www.ics.uci.edu/~dechter/> will
> give a talk titled "Modern Exact and Approximate Combinatorial
> Optimization Algorithms (max-product and max-sum-product) for Graphical
> models."
> *Abstract: *In this talk I will present several principles behind state
> of the art algorithms for solving combinatorial optimization tasks defined
> over graphical models (Bayesian networks, Markov networks, constraint
> networks, Influence diagrams) and demonstrate their performance on some
> benchmarks.
> Specifically I will present branch and bound search algorithms which
> explore the AND/OR search space over graphical models and thus exploit
> problem's decomposition (using AND nodes), equivalence (by caching) and
> pruning irrelevant subspaces via the power of bounding heuristics. In
> particular I will show how the two ideas of mini-bucket partitioning which
> relaxes the input problem using node duplication only, combined with linear
> programming relaxations ideas which optimize
> cost-shifting/re-parameterization schemes, can yield tight bounding
> heuristic information within systematic, anytime, search. I will then show
> our recent extension to solving the far more challenging task of Marginal
> Map (as time permits).
> Notably, a solver for finding the most probable explanation (MPE or MAP),
> embedding these principles has won first place in all time categories in
> the 2012 PASCAL2 approximate inference challenge, and first or second place
> in the UAI-2014 competitions.
> Parts of this work were done jointly with: Radu Marinescu, Kalev Kask,
> Alex Ihler, Robesrt Mateescu and Lars Otten.
> *Bio:* Rina 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 Mathematics 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, and 'Reasoning with Probabilistic and Deterministic
> Graphical Models: Exact Algorithms' by Morgan and Claypool publishers,
> 2013, has co-authored over 150 research papers, and has served on the
> editorial boards of: Artificial Intelligence, the Constraint Journal,
> Journal of Artificial Intelligence Research, Logical Methods in Computer
> Science (LMCS) and journal of Machine Learning (JLMR). 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, received the 2007 Association of Constraint
> Programming (ACP) research excellence award and is a 2013 Fellow of the
> ACM. She has been Co-Editor-in-Chief of Artificial Intelligence, since 2011.
> Best,
> Ellen and Ariel
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