Difference: ArrowClusterCFISummaries (8 vs. 9)

Revision 92007-05-11 - jtillett

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META TOPICPARENT	name="SunGridEngine"

The Arrow cluster and our 22 CPLEX licenses were funded under a CFI grant. This grant requires us to complete annual reports explaining how this infrastructure is being used. If you use the cluster or CPLEX licenses for a project, large or small, please enter a bullet item here that gives a short description of your project and the role the cluster played. If you used these resources for multiple projects and/or for a period of time that spans the time periods given here, please create multiple bullets.

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May 2006 -- May 2007

Sample project: description (year(s); students/faculty involved)

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Modeling boundedly rational agents in a bargaining scenario: We investigated the implementation of a new opponent model for boundedly rational players in a negotiation game. Arrow was used to run simulations of bargaining scenarios formulated as POMDPs. (2006-7; Jennifer Tillett, Kevin Leyton-Brown)

Learning network structure using L1 regularization: many machine learning algorithms are embarassingly parallel, since they involve running the same code on different subsets of the data for purposes of cross validation, estimating error bars, etc; we used many Arrow nodes to speed up the experiments described in "Learning Graphical Model Structure using L1-Regularization Paths", M Schmidt, A Niculescu-Mizil, K Murphy. AAAI'07
Bayesian learning of network structure features: in a related project, we looked at new MCMC algorithms for estimating probabilities of network features. We used Arrow to speed up the experiments described in "Bayesian structure learning using dynamic programming and MCMC", D Eaton, K Murphy, UAI'07 to appear.
Action Graph Games: Using the arrow cluster we carried out computational experiments evaluating the performance of our proposed algorithms for action graph games, which is a compact representation of game-theoretic models. (May 2006 - ongoing; Albert Xin Jiang and Kevin Leyton-Brown, CS)

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