A problem of planning for cooperative teams under uncertainty is a crucial one in multiagent systems. Decentralized partially observable Markov decision processes (DECPOMDPs) prov...
We present an analysis of concentration-of-expectation phenomena in layered Bayesian networks that use generalized linear models as the local conditional probabilities. This frame...
Many multimedia applications rely on the computation of logarithms, for example, when estimating log-likelihoods for Gaussian Mixture Models. Knowing of the demand to compute loga...
We study the problem of computing approximate quantiles in large-scale sensor networks communication-efficiently, a problem previously studied by Greenwald and Khana [12] and Shri...
We present tractable, exact algorithms for learning actions' effects and preconditions in partially observable domains. Our algorithms maintain a propositional logical repres...