KMS Of Academy of mathematics and systems sciences, CAS
An Efficient Orthonormalization-Free Approach for Sparse Dictionary Learning and Dual Principal Component Pursuit | |
Hu, Xiaoyin1,2; Liu, Xin1,2,3 | |
2020-06-01 | |
发表期刊 | SENSORS |
卷号 | 20期号:11页码:25 |
摘要 | Sparse dictionary learning (SDL) is a classic representation learning method and has been widely used in data analysis. Recently, the |
关键词 | dual principal component pursuit orthogonality constraint sparse dictionary learning stiefel manifold |
DOI | 10.3390/s20113041 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[11971466] ; National Natural Science Foundation of China[11991021] ; National Natural Science Foundation of China[11991020] ; Key Research Program of Frontier Sciences, Chinese Academy of Sciences[ZDBS-LY-7022] ; National Center for Mathematics and Interdisciplinary Sciences, Chinese Academy of Sciences ; Youth Innovation Promotion Association, Chinese Academy of Sciences |
WOS研究方向 | Chemistry ; Engineering ; Instruments & Instrumentation |
WOS类目 | Chemistry, Analytical ; Engineering, Electrical & Electronic ; Instruments & Instrumentation |
WOS记录号 | WOS:000552737900034 |
出版者 | MDPI |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.amss.ac.cn/handle/2S8OKBNM/51901 |
专题 | 中国科学院数学与系统科学研究院 |
通讯作者 | Hu, Xiaoyin |
作者单位 | 1.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Math Sci, Beijing 100049, Peoples R China 3.State Key Lab Sci & Engn Comp, Beijing 100190, Peoples R China |
推荐引用方式 GB/T 7714 | Hu, Xiaoyin,Liu, Xin. An Efficient Orthonormalization-Free Approach for Sparse Dictionary Learning and Dual Principal Component Pursuit[J]. SENSORS,2020,20(11):25. |
APA | Hu, Xiaoyin,&Liu, Xin.(2020).An Efficient Orthonormalization-Free Approach for Sparse Dictionary Learning and Dual Principal Component Pursuit.SENSORS,20(11),25. |
MLA | Hu, Xiaoyin,et al."An Efficient Orthonormalization-Free Approach for Sparse Dictionary Learning and Dual Principal Component Pursuit".SENSORS 20.11(2020):25. |
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