We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
We present SEMANDAQ, a prototype system for improving the quality of relational data. Based on the recently proposed conditional functional dependencies (CFDs), it detects and rep...
We describe a Markov chain method for sampling from the distribution of the hidden state sequence in a non-linear dynamical system, given a sequence of observations. This method u...
In this article we present three key ideas which together form a flexible framework for maximizing user-perceived quality under given resources with modern video codecs (H.264). F...
Abstract— Human-robot collaborative task achievement requires the robot to reason not only about its current beliefs but also about the ones of its human partner. In this paper, ...