3 papers
math.NA2025
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.NA2025
Superfast 1-Norm Estimation
Soo Go, Victor Y. Pan
A matrix algorithm is said to be superfast (that is, runs at sublinear cost) if it involves much fewer scalars and flops than the input matrix has entries. Such algorithms have bee…
math.NA2024
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…