The appearance of dynamic scenes is often largely governed by a latent low-dimensional dynamic process. We show how to learn a mapping from video frames to this lowdimensional rep...
This paper examines the notion of symmetry in Markov decision processes (MDPs). We define symmetry for an MDP and show how it can be exploited for more effective learning in singl...
In this paper we propose to study budget semi-supervised learning, i.e., semi-supervised learning with a resource budget, such as a limited memory insufficient to accommodate and/...
Zhi-Hua Zhou, Michael Ng, Qiao-Qiao She, Yuan Jian...
This paper is concerned with bridging the gap between requirements, provided as a set of scenarios, and conforming design models. The novel aspect of our approach is to exploit lea...
Abstract. In this paper, we propose and study a new on-line algorithm for learning a SVM based on Radial Basis Function Kernel: Local Incremental Learning of SVM or LISVM. Our meth...