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Larry Wasserman, Topological Data Analysis

Friday, February 13, 2015
12:00 AM
411 West Hall

Topological Data Analysis (TDA) refers to a collection of techniques for extracting interesting features from point clouds and images. I will discuss two different approaches to TDA.  The first is persistent homology, which is a multiscale method for finding voids of different dimensions.  The second is ridge estimation which is aimed at finding high density filaments and walls.  This is joint work with members of TopStat (www.stat.cmu.edu/topstat).