Principal component analysis based on non-parametric maximum entropy
文献类型：期刊论文
| 作者 | He, Ran1; Hu, Baogang2; Yuan, XiaoTong3; Zheng, Wei-Shi4; Baogang Hu ; Ran He(赫然)
|
| 刊名 | NEUROCOMPUTING
 |
| 出版日期 | 2010-06-01 |
| 卷号 | 73期号:10-12页码:1840-1852 |
| 关键词 | PCA Entropy Subspace learning Information theoretic learning |
| 英文摘要 | In this paper, we propose an improved principal component analysis based on maximum entropy (MaxEnt) preservation, called MaxEnt-PCA, which is derived from a Parzen window estimation of Renyi's quadratic entropy. Instead of minimizing the reconstruction error either based on L-2-norm or L-1-norm, the MaxEnt-PCA attempts to preserve as much as possible the uncertainty information of the data measured by entropy. The optimal solution of MaxEnt-PCA consists of the eigenvectors of a Laplacian probability matrix corresponding to the MaxEnt distribution. MaxEnt-PCA (1) is rotation invariant, (2) is free from any distribution assumption, and (3) is robust to outliers. Extensive experiments on real-world datasets demonstrate the effectiveness of the proposed linear method as compared to other related robust PCA methods. (C) 2010 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] | KERNEL EIGENVALUE PROBLEM ; RECOGNITION ; PCA ; EIGENFACES ; EXTRACTION ; ALGORITHM ; EXTENSION ; L1-NORM ; POINTS |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000279134100034 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/2811]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_多媒体计算与图形学团队 |
| 作者单位 | 1.Dalian Univ Technol, Sch Elect & Informat Engn, Dalian 116024, Peoples R China 2.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China 3.Natl Univ Singapore, Dept Elect & Comp Engn, Singapore 117548, Singapore 4.Queen Mary Univ London, Dept Comp Sci, London, England |
| 推荐引用方式 GB/T 7714 | He, Ran,Hu, Baogang,Yuan, XiaoTong,et al. Principal component analysis based on non-parametric maximum entropy[J]. NEUROCOMPUTING,2010,73(10-12):1840-1852. |
| APA | He, Ran,Hu, Baogang,Yuan, XiaoTong,Zheng, Wei-Shi,Baogang Hu,&Ran He.(2010).Principal component analysis based on non-parametric maximum entropy.NEUROCOMPUTING,73(10-12),1840-1852. |
| MLA | He, Ran,et al."Principal component analysis based on non-parametric maximum entropy".NEUROCOMPUTING 73.10-12(2010):1840-1852. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。