Sayan Mukherjee - Duke

Starts: 4:00 pm on Thursday, September 29, 2011
Ends: 5:00 pm on Thursday, September 29, 2011
Location: MCS 148

TITLE: Geometry/topology and statistical inference -- ABSTRACT: In this talk I will illustrate two examples where geometric/topological ideas and statistical inference complement each other. In the first example, computational geometry is a central tool used to address a classic problem in statistics, inference of conditional dependence. In the second example, a classic object in topology and geometry, a Whitney stratified space, is stated as a mixture model and an algorithm for inference of mixture elements is provided as well as finite sample bounds for the algorithm.