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Research questionHow can we learn sparse symmetric similarity graphs that are doubly stochastic and enforce a chosen number of clusters?Learning a graph that is simultaneously sparse, symmetric, and doubly stochastic can conflict with imposing cluster structure. The graph must also encode the desired number of disconnected or separable groups.
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Latest papersRecent research connected to this question, newest first.Doubly Stochastic Adaptive Neighbors Clustering via the Marcus MappingThe source studies similarity-graph clustering, introduces the Marcus mapping and the ANCMM algorithm, and discusses its connection to a specific optimal transport problem. Evidence includes comparisons with existing clustering algorithms; no particular application domain is specified.research paper · Sep 2, 2026
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