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作者:

Sun, Yanfeng (Sun, Yanfeng.) (学者:孙艳丰) | Gao, Junbin (Gao, Junbin.) | Hong, Xia (Hong, Xia.) | Guo, Yi (Guo, Yi.) | Harris, Chris J. (Harris, Chris J..)

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摘要:

This paper is concerned with tensor clustering with the assistance of dimensionality reduction approaches. A class of formulation for tensor clustering is introduced based on tensor Tucker decomposition models. In this formulation, an extra tensor mode is formed by a collection of tensors of the same dimensions and then used to assist a Tucker decomposition in order to achieve data dimensionality reduction. We design two types of clustering models for the tensors: PCA Tensor Clustering model and Non-negative Tensor Clustering model, by utilizing different regularizations. The tensor clustering can thus be solved by the optimization method based on the alternative coordinate scheme. Interestingly, our experiments show that the proposed models yield comparable or even better performance compared to most recent clustering algorithms based on matrix factorization. © 2014 IEEE.

关键词:

Cluster analysis Clustering algorithms Factorization Matrix algebra Reduction Tensors

作者机构:

  • [ 1 ] [Sun, Yanfeng]Beijing Municipal Key Lab of Multimedia and Intelligent Software Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Gao, Junbin]School of Computing and Mathematics, Charles Start University, Bathurst; NSW; 2795, Australia
  • [ 3 ] [Hong, Xia]School of Systems Engineering, University of Reading, Reading; RG6 6AY, United Kingdom
  • [ 4 ] [Guo, Yi]CSIRO Mathematics, Informatics and Statistics, North Ryde; NSW; 1670, Australia
  • [ 5 ] [Harris, Chris J.]Electronics and Computer Science, University of Southampton, Southampton, United Kingdom

通讯作者信息:

  • 孙艳丰

    [sun, yanfeng]beijing municipal key lab of multimedia and intelligent software technology, beijing university of technology, beijing; 100124, china

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年份: 2014

页码: 1565-1572

语种: 英文

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SCOPUS被引频次: 7

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