Compiling Bayesian networks (BNs) is one of the hot topics in the area of probabilistic modeling and processing. In this paper, we propose a new method of compiling BNs into multi...
—Today’s enterprise data centers are shifting towards a utility computing model where many business critical applications share a common pool of infrastructure resources that o...
This paper describes a novel browsing paradigm, taking benefit of the various types of links (e.g. thematic, temporal, references, etc.) that can be automatically built between mul...
Motivated by applications like elections, web-page ranking, revenue maximization etc., we consider the question of inferring popular rankings using constrained data. More specific...
We introduce a framework for actively learning visual categories from a mixture of weakly and strongly labeled image examples. We propose to allow the categorylearner to strategic...