Sparse Generalized Inverses

October 10, 2019, 9:00 AM - 9:45 AM


Auditorium (Amphitheatre Banque Nationale)

HEC Montreal

Cote-Sainte-Catherine Building

Click here for map.

Jon Lee, University of Michigan

Generalized inverses are ubiquitous in matrix algebra and its applications. Not all Moore-Penrose properties are needed to ensure that a generalized inverse solves key problems, like least squares. So there is the opportunity to find sparser generalized inverses that do the jobs. I will present theoretical and computational results on various approaches to this, in particular approximation algorithms and convex relaxation. Joint works with: Marcia Fampa, Luze Xu and Gabriel Ponte.