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Back to Departmental Colloquium: Spring 2022

Departmental Colloquium


Date: Thursday, Apr 14, 2022

Time: 4:00PM

Location: JWB 335


Jeff Calder

University of Minnesota

Title

Boundary estimation and Hamilton-Jacobi equations on point clouds

Abstract

This talk will discuss recent work on estimating the boundary of a domain from iid samples, and on solving Hamilton-Jacobi equations on graphs. We’ll present a method for boundary estimation that is scalable to large datasets in high dimensional settings, and provide statistical guarantees that the method identifies all samples within a desired distance of the boundary. We’ll show that the method can be used to solve PDEs on point clouds with Dirichlet boundary conditions, which has applications to problems like data depth and machine learning. We will also present some work on robust approximations of graph distances via the solution of particular Hamilton-Jacobi equations on graphs, and discuss applications to data depth and semi-supervised learning. This is joint work with Dejan Slepcev, Sangmin Park, and Mahmood Ettehad.

Differential Equations Data Science and Machine Learning

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