Name
Abstract | ||
|---|---|---|
We consider the problem of minimizing a sum of several convex nonsmooth functions. We introduce a new algorithm called the selective linearization method, which iteratively linearizes all but one of the functions and employs simple proximal steps. The algorithm is a form of multiple operator splitting in which the order of processing partial functions is not fixed, but rather determined in the course of calculations. Global convergence is proved and estimates of the convergence rate are derived. Specifically, the number of iterations needed to achieve solution accuracy epsilon is of order O(ln( 1/epsilon)/epsilon). |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1137/15M103217X | SIAM JOURNAL ON OPTIMIZATION |
Keywords | Field | DocType |
nonsmooth optimization,operator splitting,multiple blocks,alternating linearization | Convergence (routing),Discrete mathematics,Operator splitting,Mathematical optimization,Regular polygon,Rate of convergence,Convex optimization,Linearization,Partial function,Mathematics | Journal |
Volume | Issue | ISSN |
27 | 2 | 1052-6234 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yu Du | 1 | 65 | 10.11 |
| Xiaodong Lin | 2 | 63 | 4.32 |
| Andrzej Ruszczynski | 3 | 675 | 80.15 |