KMS Of Academy of mathematics and systems sciences, CAS
| Gradient methods exploiting spectral properties | |
| Huang, Yakui1; Dai, Yu-Hong2; Liu, Xin-Wei1; Zhang, Hongchao3 | |
| 2020-02-15 | |
| Source Publication | OPTIMIZATION METHODS & SOFTWARE
 |
| ISSN | 1055-6788 |
| Pages | 25 |
| Abstract | We propose a new stepsize for the gradient method. It is shown that this new stepsize will converge to the reciprocal of the largest eigenvalue of the Hessian, when Dai-Yang's asymptotic optimal gradient method (Computational Optimization and Applications, 2006, 33(1): 73-88) is applied for minimizing quadratic objective functions. Based on this spectral property, we develop a monotone gradient method that takes a certain number of steps using the asymptotically optimal stepsize by Dai and Yang, and then follows by some short steps associated with this new stepsize. By employing one step retard of the asymptotic optimal stepsize, a nonmonotone variant of this method is also proposed. Under mild conditions, R-linear convergence of the proposed methods is established for minimizing quadratic functions. In addition, by combining gradient projection techniques and adaptive nonmonotone line search, we further extend those methods for general bound constrained optimization. Two variants of gradient projection methods combining with the Barzilai-Borwein stepsizes are also proposed. Our numerical experiments on both quadratic and bound constrained optimization indicate that the new proposed strategies and methods are very effective. |
| Keyword | Gradient methods spectral property Barizilai-Borwein method linear convergence quadratic optimization bound constrained optimization |
| DOI | 10.1080/10556788.2020.1727476 |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | National Natural Science Foundation of China[11701137] ; National Natural Science Foundation of China[11631013] ; National Natural Science Foundation of China[11671116] ; National 973 Program of China[2015CB856002] ; China Scholarship Council[201806705007] ; USA National Science Foundation[1522654] ; USA National Science Foundation[1819161] |
| WOS Research Area | Computer Science ; Operations Research & Management Science ; Mathematics |
| WOS Subject | Computer Science, Software Engineering ; Operations Research & Management Science ; Mathematics, Applied |
| WOS ID | WOS:000514512500001 |
| Publisher | TAYLOR & FRANCIS LTD |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.amss.ac.cn/handle/2S8OKBNM/50835 |
| Collection | 中国科学院数学与系统科学研究院 |
| Corresponding Author | Dai, Yu-Hong |
| Affiliation | 1.Hebei Univ Technol, Inst Math, Tianjin, Peoples R China 2.Chinese Acad Sci, Acad Math & Syst Sci, LSEC, Beijing, Peoples R China 3.Louisiana State Univ, Dept Math, Baton Rouge, LA 70803 USA |
| Recommended Citation GB/T 7714 | Huang, Yakui,Dai, Yu-Hong,Liu, Xin-Wei,et al. Gradient methods exploiting spectral properties[J]. OPTIMIZATION METHODS & SOFTWARE,2020:25. |
| APA | Huang, Yakui,Dai, Yu-Hong,Liu, Xin-Wei,&Zhang, Hongchao.(2020).Gradient methods exploiting spectral properties.OPTIMIZATION METHODS & SOFTWARE,25. |
| MLA | Huang, Yakui,et al."Gradient methods exploiting spectral properties".OPTIMIZATION METHODS & SOFTWARE (2020):25. |
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