A fast convex conjugated algorithm for sparse recovery
文献类型：期刊论文
| 作者 | He, Ran1; Yuan, Xiaotong2; Zheng, Wei-Shi3; Ran He(赫然)
|
| 刊名 | NEUROCOMPUTING
 |
| 出版日期 | 2013-09-04 |
| 卷号 | 115页码:178-185 |
| 关键词 | Sparse representation Half-quadratic minimization L1 minimization |
| 英文摘要 | Sparse recovery aims to find the sparsest solution of an underdetermined system X beta=y. This paper studies simple yet efficient sparse recovery algorithms from a novel viewpoint of convex conjugacy. To this end, we induce a family of convex conjugated loss functions as a smooth approximation of l(0)-norm. Then we apply the additive form of half-quadratic (HQ) optimization to solve these loss functions and to reformulate the sparse recovery problem as an augmented quadratic constraint problem that can be efficiently computed by alternate minimization. At each iteration, we compute the auxiliary vector of HQ via minimizer function and then we project this vector into the nullspace of the homogeneous linear system X beta=0 such that a feasible and sparser solution is obtained. Extensive experiments on random sparse signals and robust face recognition corroborate our claims and validate that our method outperforms the state-of-the-art l(1) minimization algorithms in terms of computational cost and estimation error. (C) 2013 Elsevier B.V. All rights reserved. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Artificial Intelligence |
| 研究领域[WOS] | Computer Science |
| 关键词[WOS] | LINEAR INVERSE PROBLEMS ; LEAST-SQUARES ; THRESHOLDING ALGORITHM ; PATTERN-RECOGNITION ; MINIMIZATION ; RECONSTRUCTION ; SIGNAL ; L(1)-MINIMIZATION ; REPRESENTATION ; PURSUIT |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000320476500019 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/3814]  |
| 专题 | 自动化研究所_智能感知与计算研究中心 |
| 通讯作者 | Ran He(赫然) |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 2.Rutgers State Univ, Dept Stat, Piscataway, NJ 08816 USA 3.Sun Yat Sen Univ, Sch Informat Sci & Technol, Guangzhou 510275, Guangdong, Peoples R China |
| 推荐引用方式 GB/T 7714 | He, Ran,Yuan, Xiaotong,Zheng, Wei-Shi,et al. A fast convex conjugated algorithm for sparse recovery[J]. NEUROCOMPUTING,2013,115:178-185. |
| APA | He, Ran,Yuan, Xiaotong,Zheng, Wei-Shi,&Ran He.(2013).A fast convex conjugated algorithm for sparse recovery.NEUROCOMPUTING,115,178-185. |
| MLA | He, Ran,et al."A fast convex conjugated algorithm for sparse recovery".NEUROCOMPUTING 115(2013):178-185. |
入库方式： OAI收割
来源：自动化研究所
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