We consider the problem of multi-task reinforcement learning where the learner is provided with a set of tasks, for which only a small number of samples can be generated for any g...
In this work we present new in-network techniques for communication efficient approximate query processing in wireless sensornets. We use a model-based approach that constructs a...
Alexandra Meliou, Carlos Guestrin, Joseph M. Helle...
Beam-ACO algorithms are hybrid methods that combine the metaheuristic ant colony optimization with beam search. They heavily rely on accurate and computationally inexpensive boundi...
In this paper, we first introduce a 3D morphing method for landmark-based volume deformation, using various scattered data interpolation schemes. Qualitative and speed comparisons...
Abstract— In this paper, we consider a class of continuoustime, continuous-space stochastic optimal control problems. Building upon recent advances in Markov chain approximation ...