Joint Robust Multi-view Spectral Clustering
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Networks and Communications,General Neuroscience,Software
Link
https://link.springer.com/content/pdf/10.1007/s11063-020-10257-0.pdf
Reference50 articles.
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2. Zhang Z et al (2018) Binary multi-view clustering. IEEE Trans Pattern Anal Mach Intell 41(7):1774–1782
3. Yu H et al (2019) An active three-way clustering method via low-rank matrices for multi-view data. Inf Sci 507:823–839
4. Wang N et al (2019) Structured sparse multi-view feature selection based on weighted hinge loss. Multimed Tools Appl 78(11):15455–15481
5. Li J et al (2018) Feature selection: a data perspective. ACM Comput Surv (CSUR) 50(6):94
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