The structure of a Bayesian network (BN) encodes variable independence. Learning the structure of a BN, however, is typically of high computational complexity. In this paper, we e...
In this paper, we compare both discriminative and generative parameter learning on both discriminatively and generatively structured Bayesian network classifiers. We use either ma...
As with any application of machine learning, web search ranking requires labeled data. The labels usually come in the form of relevance assessments made by editors. Click logs can...
Switching activity estimation is a crucial step in estimating dynamic power consumption in CMOS circuits. In [1], we proposed a new switching probability model based on Bayesian N...
In this paper, we describe a dynamic Bayesian network or DBN based approach to both two-hand gestures and onehand gestures. Unlike wired glove-based approaches, the success of cam...