Name
Abstract | ||
|---|---|---|
In this paper, we develop new subgradient methods for solving nonsmooth convex optimization problems. These methods guarantee the best possible rate of convergence for the whole sequence of test points. Our methods are applicable as efficient real-time stabilization tools for potential systems with infinite horizon. Preliminary numerical experiments confirm a high efficiency of the new schemes. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/s10957-014-0677-5 | J. Optimization Theory and Applications |
Keywords | Field | DocType |
Convex optimization, Nonsmooth optimzation, Subgradient methods, Rate of convergence, Primal-dual methods, 90C25, 90C47, 68Q25 | Mathematical optimization,Subgradient method,Infinite horizon,Rate of convergence,Convex optimization,Monotone polygon,Mathematics | Journal |
Volume | Issue | ISSN |
165 | 3 | 1573-2878 |
Citations | PageRank | References |
3 | 0.47 | 3 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yurii Nesterov | 1 | 1800 | 168.77 |
| V. Shikhman | 2 | 3 | 0.47 |