We present a probabilistic approach to shape matching which is invariant to rotation, translation and scaling. Shapes are represented by unlabeled point sets, so discontinuous bou...
Within-network regression addresses the task of regression in partially labeled networked data where labels are sparse and continuous. Data for inference consist of entities associ...
Exponentially growing photo collections motivate the needs for automatic image annotation for effective manipulations (e.g., search, browsing). Most of the prior works rely on sup...
Abstract--In this paper we propose a new multi-view semisupervised learning algorithm called Local Co-Training (LCT). The proposed algorithm employs a set of local models with vect...
Learning theory has largely focused on two main learning scenarios. The first is the classical statistical setting where instances are drawn i.i.d. from a fixed distribution and...
Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari