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Math Colloquium
Hayden Schaeffer
CalTech
Title: L1 optimization and numerical PDEs

Abstract: The L1 regularized least squares problem has seen many applications in imaging and data sciences. Inspired by its success, my talk will focus on what we can learn from this model and how it can be used to create numerical solvers for PDEs or improve the implementation of known methods. In particular, I will examine the connections between sparsity and free boundary problems, with a focus on the divisible sandpile problem. I will also talk about the construction and implementation of fast iterative solvers for fully nonlinear 2nd order elliptic PDEs.

Date: Wednesday, October 22, 2014
Time: 4:30 pm
Location: Wean Hall 7500
Submitted by:  Bohman
Note: Refreshments at 4:00 pm, Wean Hall 6220.