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math.OC2024
Learning nonnegative matrix factorizations from compressed data
Abraar Chaudhry, Elizaveta Rebrova
We propose a flexible and theoretically supported framework for scalable nonnegative matrix factorization. The goal is to find nonnegative low-rank components directly from compres…
math.OC2022★ 1 cited
Sharp Analysis of Sketch-and-Project Methods via a Connection to Randomized Singular Value Decomposition
Michał Dereziński, Elizaveta Rebrova
Sketch-and-project is a framework which unifies many known iterative methods for solving linear systems and their variants, as well as further extensions to non-linear optimization…