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Duality in convex optimization, via perturbation arguments

Kellie Macphee, University of Washington
Thursday, March 2, 2017 - 2:30pm
PDL C-36
Abstract: Sometimes optimization problems are hard. One method for attacking difficult problems is to pass to a dual formulation of the problem, solve this (potentially easier) dual problem, and then recover a solution to your original problem. In this talk, we will discuss how the duality method can be interpreted in terms of the sensitivity of solutions to perturbations in problem parameters. A traditional perturbation yields the classical Lagrange duality, and new work shows that a different choice of perturbation leads to the less-studied gauge duality.
No optimization background will be assumed.
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