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A Unified Framework for Establishing Error Bounds for Structured Convex Optimization Problems
Title: "A Unified Framework for Establishing Error Bounds for Structured Convex Optimization Problems" Speaker: Anthony Man-Cho So Chinese University of Hong Kong Time/Date: Friday, Apr 8, 11am - 12noon Location: Room 3501 (lift 25/26) Abstract: In recent years, we have witnessed a widespread use of first-order methods (FOMs) to solve large-scale structured convex optimization problems. It is well known that many FOMs will converge linearly if the problem at hand possesses a certain Lipschitzian error bound. In this talk, we shall present a new framework for establishing such error bounds for a host of structured convex optimization problems. Our framework makes essential use of the notions of calmness and metric subregularity from variational analysis. It not only unifies and simplifies the proofs of several existing error bounds but also leads to a new error bound for structured convex optimization with nuclear norm regularization. We believe that our techniques will have further applications in the development of error bounds and convergence rate analysis of first-order methods. More information on the CSE Theory Seminars can be found at http://cse.hkust.edu.hk/tcsc/seminars.html