Name
Title | ||
|---|---|---|
On Convergence Analysis of Iterative Smoothing Methods for a Class of Nonsmooth Convex Minimization Problems |
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. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/CSO.2014.53 | CSO |
Keywords | Field | DocType |
smooth part,exponential smoothing technique,convex objective,nonsmooth convex minimization problems,convergence analysis,non-smooth convex optimization,iterative smoothing methods,smoothing algorithms,gradient methods,nonsmooth part,max function,iterative smoothing-gradient methods,non-smooth convex optimization, exponential smoothing technique, run-time complexity, convergence analysis,minimisation,run-time complexity,convex functions,approximation algorithms,convergence,optimization,algorithm design and analysis | Mathematical optimization,Computer science,Convex combination,Proximal Gradient Methods,Subderivative,Proper convex function,Conic optimization,Convex optimization,Ellipsoid method,Convex analysis | Conference |
ISSN | Citations | PageRank |
2158-799X | 0 | 0.34 |
References | Authors | |
5 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sanming Liu | 1 | 3 | 2.56 |
| Zhijie Wang | 2 | 2 | 4.76 |