Speaker: Lucas Simões, University of Campinas, Brazil
Location: Warren Weaver Hall 1302
Date: Sept. 22, 2017, 10 a.m.
Minimization problems involving nonsmooth functions appear in many real problems. For convex objective functions, Bundle Methods are important and effective tools for solving nonsmooth optimization problems. However, when the problem is not convex, the theoretical and practical aspects are not so well developed. A reliable alternative to these methods is the Gradient Sampling (GS) algorithm. Based on GS ideas, this talk presents a new method that tries to move superlinearly to the solution of the optimization problem.