We consider the problem of learning incoherent sparse and lowrank patterns from multiple tasks. Our approach is based on a linear multi-task learning formulation, in which the spa...
We consider the problem of Semi-supervised Learning (SSL) from general unlabeled data, which may contain irrelevant samples. Within the binary setting, our model manages to better...
Kaizhu Huang, Zenglin Xu, Irwin King, Michael R. L...
Background: Probability based statistical learning methods such as mutual information and Bayesian networks have emerged as a major category of tools for reverse engineering mecha...
Abstract. We present a method of learning a Bayesian model of a traveler moving through an urban environment. This technique is novel in that it simultaneously learns a unified mo...
Donald J. Patterson, Lin Liao, Dieter Fox, Henry A...
The Web is now a huge information repository with a rich semantic structure that, however, is primarily addressed to human understanding rather than automated processing by a compu...