114 citations · 170 across the 17 of their papers we have counts for
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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★ 5 cited
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…
math.NA2015
Integer Low Rank Approximation of Integer matrices
Bo Dong, Matthew M. Lin, Haesun Park
Integer data sets frequently appear in many applications in sciences and technology. To analyze these, integer low rank approximation has received much attention due to its capacit…