While research on articulated human motion and pose estimation has progressed rapidly in the last few years, there has been no systematic quantitative evaluation of competing meth...
Leonid Sigal, Alexandru O. Balan, Michael J. Black
Abstract. In this paper, we revisit the consensus of computational complexity on exact inference in Bayesian networks. We point out that even in singly connected Bayesian networks,...
A wide variety of function approximation schemes have been applied to reinforcement learning. However, Bayesian filtering approaches, which have been shown efficient in other field...
— Our objective is to find a small set of images that summarize a robot’s visual experience along a path. We present a novel on-line algorithm for this task. This algorithm is...
Recently several researchers have investigated techniques for using data to learn Bayesian networks containing compact representations for the conditional probability distribution...
David Maxwell Chickering, David Heckerman, Christo...