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Spectral clustering with distinction and consensus learning on multiple views data
2018
PLoS ONE
Since multi-view data are available in many real-world clustering problems, multi-view clustering has received considerable attention in recent years. Most existing multi-view clustering methods learn consensus clustering results but do not make full use of the distinct knowledge in each view so that they cannot well guarantee the complementarity across different views. In this paper, we propose a Distinction based Consensus Spectral Clustering (DCSC), which not only learns a consensus result
doi:10.1371/journal.pone.0208494
pmid:30521611
pmcid:PMC6283548
fatcat:6r752ff45fdwrgq5diz7r56qd4