Multiple kernel clustering based on centered kernel alignment-Reference-Cited by-同舟云学术

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Multiple kernel clustering based on centered kernel alignment

Published:2014-11 Issue:11 Volume:47 Page:3656-3664
ISSN:0031-3203
Container-title:Pattern Recognition
language:en
Short-container-title:Pattern Recognition

Author:

Lu Yanting,Wang Liantao,Lu Jianfeng,Yang Jingyu,Shen Chunhua

Funder

National Natural Science Foundation of China (NSFC)

Natural Science Foundation of Jiangsu Province

Fundamental Research Funds for the Central Universities

Priority Academic Program Development of Jiangsu Higher Education Institutions

Jiangsu Key Laboratory of Image and Video Understanding for Social Safety (Nanjing University of Science and Technology)

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference37 articles.

1. T. Li, S. Ma, M. Ogihara, Document clustering via adaptive subspace iteration, in: Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, ACM, New York, NY, USA, 2004, pp. 218–225.

2. C.H.Q. Ding, T. Li, Adaptive dimension reduction using discriminant analysis and k-means clustering, in: Z. Ghahramani (Ed.), Proceedings of the 24th International Conference on Machine Learning, ACM, New York, NY, USA, 2007, pp. 521–528.

3. Feature selection and kernel learning for local learning-based clustering;Zeng;IEEE Trans. Pattern Anal. Mach. Intell.,2011

4. Minkowski metric, feature weighting and anomalous cluster initializing in k-means clustering;de Amorim;Pattern Recognit.,2012

5. B. Zhao, J. T. Kwok, C. Zhang, Multiple kernel clustering, in: Proceedings of the SIAM International Conference on Data Mining, Society for Industrial and Applied Mathematics, PA, USA, 2009, pp. 638–649.

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