Finding Shape in Data

When
Start: 10/12/2016 - 4:15pm
End  : 10/12/2016 - 5:15pm

Category
Colloquium

Speaker
Brittany Fasy (Montana St.U.)

Abstract

Topology studies the structure of shapes. Topological data analysis (TDA) is the

study of the shape of (large, high-dimensional, and noisy) data. Often, in
TDA, the data set is transformed into a concise descriptor, such as a
persistence diagram or a dendogram, which can then be used to (indirectly)
compare or classify the data sets. In this talk, we will define a persistence
diagram and confidence sets for persistence diagrams. Then, we will discuss how
we can use these confidence sets to perform statistical hypothesis testing, and
provide a few examples of where we've applied (or are applying) these methods.
The examples will include road network analysis, prostate cancer diagnosis, and the study of matter throughout the universe.

 

Where
Kravis Center Lower Court 62, Claremont McKenna College