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Separable Nonnegative Matrix Factorization Using Powered Ratio-of-Norms Regularization
Separable nonnegative matrix factorization (SNMF) has been widely used for low-rank representation and clustering of nonnegative data, owing to its ability to produce part-based and interpretable decompositions. In particular, SNMF is closely related to graph clustering and community detection. To e
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