What is it about?
This paper proposes a framework of consensus clustering or clustering ensemble, which ensembles multiple weak base results to obtain a consensus better clustering result. To do the ensemble, this paper learns a structured bipartite graph from base results, which shows the intrinsic cluster structure of the data.
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This page is a summary of: Self-paced Adaptive Bipartite Graph Learning for Consensus Clustering, ACM Transactions on Knowledge Discovery from Data, February 2023, ACM (Association for Computing Machinery),
DOI: 10.1145/3564701.
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