DC Semidefinite Programming

Abstract: DC (Difference-of-Convex) optimization has been an active area of research in nonsmooth nonlinear optimization for over 30 years. The interest in this class of problems is based on the fact that one can efficiently utilize ideas and methods of convex analysis/optimization to solve DC optimization problems. The main results of DC optimization can be extended to the case of nonlinear semidefinite programming problems, i.e. problems with matrix-valued constraints, in several different ways. We will discuss two possible generalizations of the notion of DC function to the case of matrix-valued functions and show how these generalizations lead to two different DC optimization approaches to nonlinear semidefinite programming.

optimization and control

Audience: researchers in the topic

Variational Analysis and Optimisation Webinar

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