9:00 AM-10:30 AM
Room: Savannah 3
Convex optimization is a fundamental branch of optimization. It provides a suitable framework for many problems, classical (such as image reconstruction) and contemporary (such as semidefinite programming). In this minisymposium, the speakers will discuss convex optimization problems and associated objects from a computational point of view. They will focus on the symbolic and numerical computation of Fenchel conjugates; the symbolic computation of derivatives of functions on spaces of symmetric matrices; and Fenchel-duality based computational approach to image reconstruction.
Organizers: Heinz H Bauschke
Okanagan University College, Kelowna, Canada
Simon Fraser University, Burnaby, Canada