We introduce and study Recursive Markov Chains (RMCs), which extend ordinary finite state Markov chains with the ability to invoke other Markov chains in a potentially recursive m...
We consider approximate policy evaluation for finite state and action Markov decision processes (MDP) in the off-policy learning context and with the simulation-based least square...
We consider the problem of learning multiscale graphical models. Given a collection of variables along with covariance specifications for these variables, we introduce hidden var...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...
The popularity of email has triggered researchers to look for ways to help users better organize the enormous amount of information stored in their email folders. One challenge th...
In this paper we address the problem of organizing hidden-Web databases. Given a heterogeneous set of Web forms that serve as entry points to hidden-Web databases, our goal is to ...