Robust Subspace Clustering by Cauchy Loss Function | |
Li, Xuelong1,2; Lu, Quanmao3; Dong, Yongsheng3,4; Tao, Dacheng5,6 | |
作者部门 | 光谱成像技术研究室 |
2019-07 | |
发表期刊 | IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS |
卷号 | 30期号:7页码:2067-2078 |
产权排序 | 3 |
摘要 | Subspace clustering is a problem of exploring the low-dimensional subspaces of high-dimensional data. State-ofthe-art approaches are designed by following the model of spectral clustering-based method. These methods pay much attention to learn the representation matrix to construct a suitable similarity matrix and overlook the influence of the noise term on subspace clustering. However, the real data are always contaminated by the noise and the noise usually has a complicated statistical distribution. To alleviate this problem, in this paper, we propose a subspace clustering method based on Cauchy loss function (CLF). Particularly, it uses CLF to penalize the noise term for suppressing the large noise mixed in the real data. This is due to that the CLF's influence function has an upper bound that can alleviate the influence of a single sample, especially the sample with a large noise, on estimating the residuals. Furthermore, we theoretically prove the grouping effect of our proposed method, which means that highly correlated data can he grouped together. Finally, experimental results on five real data sets reveal that our proposed method outperforms several representative clustering methods. |
关键词 | Cauchy loss function (CLF) grouping effect noise suppression similarity matrix subspace clustering |
DOI | 10.1109/TNNLS.2018.2876327 |
收录类别 | SCI |
语种 | 英语 |
WOS记录号 | WOS:000472605500012 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.opt.ac.cn/handle/181661/31570 |
专题 | 光谱成像技术研究室 |
通讯作者 | Dong, Yongsheng |
作者单位 | 1.Northwestern Polytech Univ, Sch Comp Sci, Xian 710072, Shaanxi, Peoples R China 2.Northwestern Polytech Univ, Ctr OPT IMagery Anal & Learning, Xian 710072, Shaanxi, Peoples R China 3.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian 710119, Shaanxi, Peoples R China 4.Henan Univ Sci & Technol, Sch Informat Engn, Luoyang 471023, Peoples R China 5.Univ Sydney, Fac Engn & Informat Technol, UBTECH Sydney Artificial Intelligence Ctr, Darlington, NSW 2008, Australia 6.Univ Sydney, Fac Engn & Informat Technol, Sch Comp Sci, Darlington, NSW 2008, Australia |
推荐引用方式 GB/T 7714 | Li, Xuelong,Lu, Quanmao,Dong, Yongsheng,et al. Robust Subspace Clustering by Cauchy Loss Function[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2019,30(7):2067-2078. |
APA | Li, Xuelong,Lu, Quanmao,Dong, Yongsheng,&Tao, Dacheng.(2019).Robust Subspace Clustering by Cauchy Loss Function.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,30(7),2067-2078. |
MLA | Li, Xuelong,et al."Robust Subspace Clustering by Cauchy Loss Function".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 30.7(2019):2067-2078. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Robust Subspace Clus(3374KB) | 期刊论文 | 出版稿 | 限制开放 | CC BY-NC-SA | 请求全文 |
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