mlsanityData to 7 Oct 2026

Algorithms, Initializations, and Convergence for the Nonnegative Matrix Factorization

arXiv 1407.7299 ↗First posted 28 Jul 2014math.NA cs.LG cs.NAcited by 9

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Abstract (arXiv)

It is well known that good initializations can improve the speed and accuracy of the solutions of many nonnegative matrix factorization (NMF) algorithms. Many NMF algorithms are sensitive with respect to the initialization of W or H or both. This is especially true of algorithms of the alternating least squares (ALS) type, including the two new ALS algorithms that we present in this paper. We compare the results of six initialization procedures (two standard and four new) on our ALS algorithms. Lastly, we discuss the practical issue of choosing an appropriate convergence criterion.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Jul 2014.

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Citing papers per year: 2021: 4; 2022: 4; 2023: 0; 2024: 1.

9 papers.