19 citations · 33 across the 7 of their papers we have counts for
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math.NA2019
Iterative Refinement and Oversampling for Low Rank Approximation
Victor Y. Pan, Qi Luan, Soo Go
Iterative refinement is particularly popular for numerical solution of linear systems of equations. We extend it to Low Rank Approximation of a matrix (LRA) and observe close link…
math.NA2019★ 6 cited
CUR Low Rank Approximation of a Matrix at Sublinear Cost
Soo Go, Qi Luan, Victor Y. Pan +2
Low rank approximation of a matrix (hereafter LRA) is a highly important area of Numerical Linear and Multilinear Algebra and Data Mining and Analysis. One can operate with an LRA…
math.NA2019
QRP Variation of Cross--Approximation Iterations for Low Rank Approximation
Victor Y. Pan, John Svadlenka
We call matrix algorithms superfast if they use much fewer flops and memory cells than the input matrix has entries. Using such algorithms is indispensable for Big Data Mining and…