The main goal of this research
project is to fundamentally advance visualization and data
summarization by novel geometric methods of mixture models. We will
develop theories and algorithms that uncover the prominent geometric
features of mixture density. Based on the theoretical advances, we
will develop novel approaches to clustering, dimension reduction,
variable selection, and temporal analysis. A suite of statistical
tools will be integrated as the technical backbone into a new visualization
system. Applications to very large-scale, high dimensional, and temporally
evolving data will be developed. The project is funded by NSF. Here
is the project website: New Geometric
Methods of Mixture Models for Interactive Visualization
Demos