In this paper, we examine on-line learning problems in which the target concept is allowed to change over time. In each trial a master algorithm receives predictions from a large ...
This paper examines important factors for link prediction in networks and provides a general, high-performance framework for the prediction task. Link prediction in sparse network...
Ryan Lichtenwalter, Jake T. Lussier, Nitesh V. Cha...
Abstract. Side-chain prediction is an important subproblem of the general protein folding problem. Despite much progress in side-chain prediction, performance is far from satisfact...
We consider the estimation of a sparse parameter vector from measurements corrupted by white Gaussian noise. Our focus is on unbiased estimation as a setting under which the difï¬...
Alexander Jung, Zvika Ben-Haim, Franz Hlawatsch, Y...
— In this paper we present a general framework for predicting the positioning uncertainty of underwater vehicles. We apply this framework to common examples from marine robotics:...