This paper develops a general, formal framework for modeling term dependencies via Markov random fields. The model allows for arbitrary text features to be incorporated as eviden...
In many multi agent learning problems, it is difficult to determine, a priori, the agent reward structure that will lead to good performance. This problem is particularly pronoun...
Pose and illumination changes from picture to picture are two main barriers toward full automatic face recognition. In this paper, a novel method to handle both pose and lighting c...
This paper investigates a novel model-free reinforcement learning architecture, the Natural Actor-Critic. The actor updates are based on stochastic policy gradients employing Amari...
A major challenge facing grid applications is the appropriate handling of failures. In this paper we address the problem of making parallel Java applications based on Remote Method...