Speaker: Frank E. Curtis, Lehigh University

Title: Nonconvex Optimization: Opportunities and Challenges

Abstract: Much of the history of mathematical optimization has focused on theory and algorithms for solving convex problems, with much conventional wisdom holding the opinion that if a problem is not formulated to be convex, then it has been formulated incorrectly. However, in the past few years, researchers and practitioners have loosened the shackles. Now is a heyday of nonconvex optimization. In this talk, we’ll discuss the opportunities of embracing nonconvex optimization, but also warn about the resulting challenges. We’ll also discuss related topics, such as how one should compare numerical algorithms in the presence of nonconvexity and stochasticity.

Department of Mathematical Sciences
George Mason University
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