Motivated by the numerous applications of analysing opinions in multi-domain scenarios, this paper studies the potential of a still rarely considered approach to the problem of mu...
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 ...
Currently, the statistical framework based on Hidden Markov Models (HMMs) plays a relevant role in speech synthesis, while voice conversion systems based on Gaussian Mixture Model...
Image analysis is still considered as the bottleneck in 2D-gel based expression proteomics analysis for biomarkers discovery. We are presenting a new end-to-end image analysis pip...
The hierarchical Dirichlet process (HDP) is a Bayesian nonparametric mixed membership model--each data point is modeled with a collection of components of different proportions. T...
Sinead Williamson, Chong Wang, Katherine A. Heller...