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• W1882879704 abstract "Non-negative matrix factorization (NMF) is a natural model of admixture and is widely used in science and engineering. A plethora of algorithms have been developed to tackle NMF, but due to the non-convex nature of the problem, there is little guarantee on how well these methods work. Recently a surge of research have focused on a very restricted class of NMFs, called separable NMF, where provably correct algorithms have been developed. In this paper, we propose the notion of subset-separable NMF, which substantially generalizes the property of separability. We show that subset-separability is a natural necessary condition for the factorization to be unique or to have minimum volume. We developed the Face-Intersect algorithm which provably and efficiently solves subset-separable NMF under natural conditions, and we prove that our algorithm is robust to small noise. We explored the performance of Face-Intersect on simulations and discuss settings where it empirically outperformed the state-of-art methods. Our work is a step towards finding provably correct algorithms that solve large classes of NMF problems." @default.
• W1882879704 created "2016-06-24" @default.
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• W1882879704 date "2015-07-08" @default.
• W1882879704 modified "2023-09-23" @default.
• W1882879704 title "Intersecting Faces: Non-negative Matrix Factorization With New Guarantees" @default.
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• W1882879704 doi "https://doi.org/10.48550/arxiv.1507.02189" @default.
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