KMS Of Academy of mathematics and systems sciences, CAS
On greedy randomized coordinate descent methods for solving large linear least-squares problems | |
Bai, Zhong-Zhi1,2; Wu, Wen-Ting1,2 | |
2019-08-01 | |
发表期刊 | NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS |
ISSN | 1070-5325 |
卷号 | 26期号:4页码:15 |
摘要 | For solving large scale linear least-squares problem by iteration methods, we introduce an effective probability criterion for selecting the working columns from the coefficient matrix and construct a greedy randomized coordinate descent method. It is proved that this method converges to the unique solution of the linear least-squares problem when its coefficient matrix is of full rank, with the number of rows being no less than the number of columns. Numerical results show that the greedy randomized coordinate descent method is more efficient than the randomized coordinate descent method. |
关键词 | convergence property coordinate descent method linear least-squares problem randomized iteration |
DOI | 10.1002/nla.2237 |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[11671393] |
WOS研究方向 | Mathematics |
WOS类目 | Mathematics, Applied ; Mathematics |
WOS记录号 | WOS:000474224800003 |
出版者 | WILEY |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.amss.ac.cn/handle/2S8OKBNM/35090 |
专题 | 计算数学与科学工程计算研究所 |
通讯作者 | Bai, Zhong-Zhi |
作者单位 | 1.Chinese Acad Sci, Acad Math & Syst Sci, State Key Lab Sci Engn Comp, Inst Computat Math & Sci Engn Comp, POB 2719, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Math Sci, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Bai, Zhong-Zhi,Wu, Wen-Ting. On greedy randomized coordinate descent methods for solving large linear least-squares problems[J]. NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS,2019,26(4):15. |
APA | Bai, Zhong-Zhi,&Wu, Wen-Ting.(2019).On greedy randomized coordinate descent methods for solving large linear least-squares problems.NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS,26(4),15. |
MLA | Bai, Zhong-Zhi,et al."On greedy randomized coordinate descent methods for solving large linear least-squares problems".NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS 26.4(2019):15. |
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