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An efficient Nystrom spectral clustering algorithm using incomplete Cholesky decomposition

文献类型：期刊论文

作者Jia, Hongjie1,2; Wang, Liangjun1; Song, Heping1; Mao, Qirong1,2; Ding, Shifei3,4
刊名EXPERT SYSTEMS WITH APPLICATIONS
出版日期2021-12-30
卷号186页码:11
关键词Spectral clustering Nystrom approximation Incomplete Cholesky decomposition Large data set
ISSN号0957-4174
DOI10.1016/j.eswa.2021.115813
英文摘要Nystrom method can estimate the eigenvectors of a large kernel matrix with the eigenvectors of a small sampled sub-matrix. However, we may encounter two problems when using Nystrom method to speed up spectral clustering: one problem is the approximate eigenvectors generated by standard Nystrom method are sub-optimal, so they may impair the performance of spectral clustering; another one is the accurate Nystrom approximation needs a sufficient number of samples, which will increase the eigen-decomposition cost on the sampled sub-matrix. To solve these problems, this paper proposes an efficient Nystrom spectral clustering algorithm using incomplete Cholesky decomposition, in which a new matrix factorization strategy is designed for Nystrom spectral clustering to meet the orthogonal constraints, and an efficient eigensolver based on incomplete Cholesky decomposition is developed to accelerate the Nystrom approximation. In this way, the obtained approximate orthogonal eigenvectors will help to improve the clustering quality, and the developed eigenvector calculation method will help to reduce the clustering complexity. The experimental results show that the proposed algorithm performs well on many challenging data sets, and it can accomplish more complex clustering tasks with limited computing resources.
资助项目National Natural Science Foundation of China[61906077] ; National Natural Science Foundation of China[62176106] ; National Natural Science Foundation of China[62172193] ; National Natural Science Foundation of China[61976216] ; National Natural Science Foundation of China[61601202] ; Key Projects of the National Natural Science Foundation of China[U1836220] ; Natural Science Foundation of Jiangsu Province[BK20190838] ; China Postdoctoral Science Foundation[2020M671376] ; China Postdoctoral Science Foundation[2020T130257] ; Natural Science Foundation of the Jiangsu Higher Education Institutions of China[18KJB520009]
WOS研究方向Computer Science ; Engineering ; Operations Research & Management Science
语种英语
WOS记录号WOS:000705533700007
出版者PERGAMON-ELSEVIER SCIENCE LTD
源URL[http://119.78.100.204/handle/2XEOYT63/17004]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Mao, Qirong
作者单位1.Jiangsu Univ, Sch Comp Sci & Commun Engn, Zhenjiang 212013, Jiangsu, Peoples R China
2.Jiangsu Engn Res Ctr Big Data Ubiquitous Percept, Zhenjiang 212013, Jiangsu, Peoples R China
3.China Univ Min & Technol, Sch Comp Sci & Technol, Xuzhou 221116, Jiangsu, Peoples R China
4.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100090, Peoples R China
推荐引用方式
GB/T 7714		 Jia, Hongjie,Wang, Liangjun,Song, Heping,et al. An efficient Nystrom spectral clustering algorithm using incomplete Cholesky decomposition[J]. EXPERT SYSTEMS WITH APPLICATIONS,2021,186:11.
APA Jia, Hongjie,Wang, Liangjun,Song, Heping,Mao, Qirong,&Ding, Shifei.(2021).An efficient Nystrom spectral clustering algorithm using incomplete Cholesky decomposition.EXPERT SYSTEMS WITH APPLICATIONS,186,11.
MLA Jia, Hongjie,et al."An efficient Nystrom spectral clustering algorithm using incomplete Cholesky decomposition".EXPERT SYSTEMS WITH APPLICATIONS 186(2021):11.

入库方式： OAI收割

来源：计算技术研究所

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