January 26, 2021
4:00PM
-
5:00PM
Zoom info to follow
Add to Calendar
2021-01-26 16:00:00
2021-01-26 17:00:00
Learning functions on the space of persistence diagrams
Speaker: Jose Perea (Michigan State University)
Speaker's URL: https://www.joperea.com/
Abstract: The persistence diagram is an increasingly useful shape descriptor from Topological Data Analysis, but its use alongside typical machine learning techniques requires mathematical finesse. We will describe in this talk a mathematical framework addressing the problem of approximating continuous functions on compact subsets of the space of persistence diagrams. We will also show how these techniques can be applied to problems in semi-supervised learning where these descriptors are relevant.
URL associated with Seminar: https://tgda.osu.edu/activities/tdga-seminar/
Zoom info to follow
OSU ASC Drupal 8
ascwebservices@osu.edu
America/New_York
public
Date Range
2021-01-26 16:00:00
2021-01-26 17:00:00
Learning functions on the space of persistence diagrams
Speaker: Jose Perea (Michigan State University)
Speaker's URL: https://www.joperea.com/
Abstract: The persistence diagram is an increasingly useful shape descriptor from Topological Data Analysis, but its use alongside typical machine learning techniques requires mathematical finesse. We will describe in this talk a mathematical framework addressing the problem of approximating continuous functions on compact subsets of the space of persistence diagrams. We will also show how these techniques can be applied to problems in semi-supervised learning where these descriptors are relevant.
URL associated with Seminar: https://tgda.osu.edu/activities/tdga-seminar/
Zoom info to follow
America/New_York
public
Speaker: Jose Perea (Michigan State University)
Speaker's URL: https://www.joperea.com/
Abstract: The persistence diagram is an increasingly useful shape descriptor from Topological Data Analysis, but its use alongside typical machine learning techniques requires mathematical finesse. We will describe in this talk a mathematical framework addressing the problem of approximating continuous functions on compact subsets of the space of persistence diagrams. We will also show how these techniques can be applied to problems in semi-supervised learning where these descriptors are relevant.
URL associated with Seminar: https://tgda.osu.edu/activities/tdga-seminar/
