Abstract. This paper proposes an algorithm for combinatorial optimizations that uses reinforcement learning and estimation of joint probability distribution of promising solutions ...
Most studies about instant messaging (IM) are based on self-report data. We logged thousands of real IM conversations and examined them to find characteristic patterns of IM use i...
Ellen Isaacs, Candace A. Kamm, Diane J. Schiano, A...
We consider Gaussian multiresolution (MR) models in which coarser, hidden variables serve to capture statistical dependencies among the finest scale variables. Tree-structured MR ...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...
We consider the problem of inferring the most likely social network given connectivity constraints imposed by observations of outbreaks within the network. Given a set of vertices ...
We generalise the problem of inverse reinforcement learning to multiple tasks, from multiple demonstrations. Each one may represent one expert trying to solve a different task, or ...