PDE-inspired Methods for Graph-based Semi-supervised Learning

Jeff Calder (University of Minnesota, Twin Cities)

This talk will be an introduction to some recent research on PDE-inspired methods for graph-based learning, specifically for problems with very few labeled training examples. We'll discuss various models, including Laplace, p-Laplacian, re-weighted Laplacians, and Poisson learning, to highlight how connections between graph-PDEs and continuous PDEs can be used for analysis and development of new algorithms. The talk will be at an introductory level, suitable for graduate students.

Start date
Tuesday, Sept. 14, 2021, 1:25 p.m.
End date
Tuesday, Sept. 14, 2021, 2:25 p.m.

Walter Library 402