Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
Base station location has significant impact on network lifetime performance for a sensor network. For a multihop sensor network, this problem is particular challenging as we need ...
We study the computational and sample complexity of parameter and structure learning in graphical models. Our main result shows that the class of factor graphs with bounded degree...
—We consider the problem of positioning a cloud of points in the Euclidean space Rd , from noisy measurements of a subset of pairwise distances. This task has applications in var...
We address the problems of I/O scheduling and buffer management for general reference strings in a parallel I/O system. Using the standard parallel disk model withD disks and a sh...