We present a Bayesian framework for learning higherorder transition models in video surveillance networks. Such higher-order models describe object movement between cameras in the...
Abstract. We present an approach for blindly decomposing an observed random vector x into f(As) where f is a diagonal function i.e. f = f1 × . . . × fm with one-dimensional funct...
In this paper, we address two issues of long-standing interest in the reinforcement learning literature. First, what kinds of performance guarantees can be made for Q-learning aft...
When a computer program requires legitimate access to confidential data, the question arises whether such a program may illegally reveal sensitive information. This paper proposes...
Existing approaches to debugging distributed systems involve a cycle of passive observation followed by computation replaying. We propose predicate control as an active approach t...