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Sparsity and Gauge Optimization

Michael Friedlander
University of British Columbia


Gauge functions significantly generalize the notion of a norm, and gauge optimization is the class of problems for finding the element of a convex set that is minimal with respect to a gauge. These conceptually simple problems appear in a remarkable array of applications. Their gauge structure allows for a special kind of duality framework that may lead to new algorithmic approaches. I will illustrate these ideas with applications in sparse signal recovery.

Tuesday, November 12, 2013
11:00AM AP&M 2402