Title :
On Convergence Analysis of Iterative Smoothing Methods for a Class of Nonsmooth Convex Minimization Problems
Author :
Sanming Liu ; Zhijie Wang
Author_Institution :
Dept. of Math. & Phys., Shanghai Dianji Univ. Shanghai, Shanghai, China
Abstract :
We consider the problem of minimizing a convex objective which is the sum of a smooth part and a non-smooth part. Inspired by various application, we focus on the case when the non-smooth part is a max function. In this paper, we consider to solve such problems using iterative smoothing-gradient methods. We conduct run-time complexity and convergence analysis of smoothing algorithms.
Keywords :
gradient methods; minimisation; convergence analysis; convex objective; iterative smoothing methods; iterative smoothing-gradient methods; max function; nonsmooth convex minimization problems; nonsmooth part; run-time complexity; smooth part; smoothing algorithms; Algorithm design and analysis; Approximation algorithms; Complexity theory; Convergence; Convex functions; Optimization; Smoothing methods; convergence analysis; exponential smoothing technique; non-smooth convex optimization; run-time complexity;
Conference_Titel :
Computational Sciences and Optimization (CSO), 2014 Seventh International Joint Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-5371-4
DOI :
10.1109/CSO.2014.53
