Experimental performance studies on computer systems, including Grids, require deep understandings on their workload characteristics. The need arises from two important and closel...
Active learning (AL) is an increasingly popular strategy for mitigating the amount of labeled data required to train classifiers, thereby reducing annotator effort. We describe ...
Byron C. Wallace, Kevin Small, Carla E. Brodley, T...
The hierarchical Dirichlet process hidden Markov model (HDP-HMM) is a flexible, nonparametric model which allows state spaces of unknown size to be learned from data. We demonstra...
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan,...
Multimedia applications are emerging in education, information dissemination, entertainment, as well as many other applications. The stringent requirements of such applications ma...
Transfer learning addresses the problem of how to utilize plenty of labeled data in a source domain to solve related but different problems in a target domain, even when the train...