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math.NA2020★ 2 cited
An Alternating Rank-K Nonnegative Least Squares Framework (ARkNLS) for Nonnegative Matrix Factorization
Delin Chu, Wenya Shi, Srinivas Eswar +1
Nonnegative matrix factorization (NMF) is a prominent technique for data dimensionality reduction that has been widely used for text mining, computer vision, pattern discovery, and…
math.NA2019
PLANC: Parallel Low Rank Approximation with Non-negativity Constraints
Srinivas Eswar, Koby Hayashi, Grey Ballard +3
We consider the problem of low-rank approximation of massive dense non-negative tensor data, for example to discover latent patterns in video and imaging applications. As the size…