Recent advances in large-margin classification of data residing in general metric spaces (rather than Hilbert spaces) enable classification under various natural metrics, such as ...
Lee-Ad Gottlieb, Leonid Kontorovich, Robert Krauth...
We present a new online learning algorithm in the selective sampling framework, where labels must be actively queried before they are revealed. We prove bounds on the regret of ou...
In learning, a semantic or behavioral U-shape occurs when a learner rst learns, then unlearns, and, nally, relearns, some target concept (on the way to success). Within the framew...
In standard online learning, the goal of the learner is to maintain an average loss that is "not too big" compared to the loss of the best-performing function in a fixed...
We consider the problem of planning in a stochastic and discounted environment with a limited numerical budget. More precisely, we investigate strategies exploring the set of poss...
Active learning has been successfully applied to many natural language processing tasks for obtaining annotated data in a cost-effective manner. We propose several extensions to an...
Abstract. Climate models are complex mathematical models designed by meteorologists, geophysicists, and climate scientists to simulate and predict climate. Given temperature predic...