Background: Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors f...
Bo Chen, Minhua Chen, John William Paisley, Aimee ...
Determining the occurrence of an event is fundamental to developing systems that can observe and react to them. Often, this determination is based on collecting video and/or audio...
Dmitry N. Zotkin, Ramani Duraiswami, Larry S. Davi...
Two-dimensional gel electrophoresis (2DGE) is a technique to separate individual proteins in biological samples. The 2DGE technique results in gel images where proteins appear as d...
Ji Won Yoon, Simon J. Godsill, ChulHun Kang, Tae-S...
A non-parametric hierarchical Bayesian framework is developed for designing a classifier, based on a mixture of simple (linear) classifiers. Each simple classifier is termed a loc...
Chunping Wang, Xuejun Liao, Lawrence Carin, David ...
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...