We consider the general problem of learning from labeled and unlabeled data. Given a set of points, some of them are labeled, and the remaining points are unlabeled. The goal is to...
Most approaches to classifying media content assume a fixed, closed vocabulary of labels. In contrast, we advocate machine learning approaches which take advantage of the millions...
A pervasive virtual instructor is an artificially intelligent instructor that may appear transparent to the learner or appear in the form of a threedimensional graphical character...
— Recent advances in machine learning and adaptive motor control have enabled efficient techniques for online learning of stationary plant dynamics and it’s use for robust pre...
Abstract. We study the problem of learning from positive and unlabeled examples. Although several techniques exist for dealing with this problem, they all assume that positive exam...