Auto-weighted multi-view clustering via kernelized graph learning

Author:

Huang ShudongORCID,Kang ZhaoORCID,Tsang Ivor W.,Xu ZenglinORCID

Publisher

Elsevier BV

Subject

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

Reference48 articles.

1. Integrate and conquer: double-sided two-dimensional k-means via integrating of projection and manifold construction;Peng;ACM Trans. Intell. Syst. Technol.,2018

2. Low-rank kernel learning for graph-based clustering;Kang;Knowl. Based Syst.,2018

3. Self-paced and soft-weighted nonnegative matrix factorization for data representation;Huang;Knowl. Based Syst.,2018

4. Spectral co-clustering ensemble;Huang;Knowl. Based Syst.,2015

5. F. Nie, X. Wang, H. Huang, Clustering and projected clustering with adaptive neighbors, in: Proceedings of the Twentieth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ACM, 2014, pp. 977–986.

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