The problem of learning with positive and unlabeled examples arises frequently in retrieval applications. We transform the problem into a problem of learning with noise by labelin...
Multi-task learning refers to the learning problem of performing inference by jointly considering multiple related tasks. There have already been many research efforts on supervise...
This paper presents new and effective algorithms for learning kernels. In particular, as shown by our empirical results, these algorithms consistently outperform the so-called uni...
Theoretical understanding and extension of mean shift procedure has received much attention recently [8, 18, 3]. In this paper, we present a theoretical exploration and an algorit...
Abstract. We propose a novel method for action detection based on a new action descriptor called a shape flow that represents both the shape and movement of an object in a holistic...