Session II.2 - Continuous Optimization
Thursday, June 15, 17:00 ~ 17:30
Leveraging "partial" smoothness for faster convergence in nonsmooth optimization
Davis Damek
Cornell University, USA - This email address is being protected from spambots. You need JavaScript enabled to view it.
Nonsmoothness and nonconvexity are significant challenges in large-scale optimization problems, such as training neural networks and solving inverse problems in computational imaging. Although first-order methods are commonly used to address these problems, they are often considered slow. In this presentation, we introduce a (locally) accelerated first-order method that violates this perception by solving "generic" nonsmooth equations at a superlinear rate. The central insight is that nonsmooth functions often exhibit "partial" smoothness, which can be leveraged through a novel generalization of Newton's method.
Joint work with Vasileios Charisopoulos (Cornell University, University of Chicago).