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Matthew McCarver

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#machine learning Preprint Aug 2026

Separable Nonnegative Matrix Factorization Using Powered Ratio-of-Norms Regularization

This work develops efficient algorithms based on the difference-of-convex function algorithm (DCA) and the alternating direction method of multipliers (ADMM) to enhance sparsity and identifiability of the learned factors in separable nonnegative matrix factorization.

Matthew McCarver, Jing Qin · 0 citations