Mining cluster evolution from multiple correlated time-varying text corpora is important in exploratory text analytics. In this paper, we propose an approach called evolutionary h...
Abstract—We propose a probabilistic model for analyzing spatial activation patterns in multiple functional magnetic resonance imaging (fMRI) activation images such as repeated ob...
We develop a Bayesian framework for supervised dimension reduction using a flexible nonparametric Bayesian mixture modeling approach. Our method retrieves the dimension reduction ...
A logistic stick-breaking process (LSBP) is proposed for non-parametric clustering of general spatially- or temporally-dependent data, imposing the belief that proximate data are ...
Clustering methods are a useful and common first step in gene expression studies, but the results may be hard to interpret. We bring in explicitly an indicator of which genes tie ...