In this paper we propose a novel algorithm for multi-task learning with boosted decision trees. We learn several different learning tasks with a joint model, explicitly addressing...
Olivier Chapelle, Pannagadatta K. Shivaswamy, Srin...
We study online learning in an oblivious changing environment. The standard measure of regret bounds the difference between the cost of the online learner and the best decision in...
We describe online algorithms for learning a rotation from pairs of unit vectors in Rn . We show that the expected regret of our online algorithm compared to the best fixed rotati...
Research suggests that collaboration in an on-line course can enhance learning, reduce feelings of isolation, increase satisfaction with the course, and increase motivation. Unfor...
Sandra C. Hughes, Leah Wickersham, David L. Ryan-J...
We treat tracking as a matching problem of detected keypoints between successive frames. The novelty of this paper is to learn classifier-based keypoint descriptions allowing to i...