26 citations · 137 across the 17 of their papers we have counts for
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3 papers · 1 filter
math.NA2017★ 3 cited
Computing low-rank approximations of large-scale matrices with the Tensor Network randomized SVD
Kim Batselier, Wenjian Yu, Luca Daniel +1
We propose a new algorithm for the computation of a singular value decomposition (SVD) low-rank approximation of a matrix in the Matrix Product Operator (MPO) format, also called t…
cs.DS2017★ 16 cited
Single-Pass PCA of Large High-Dimensional Data
Wenjian Yu, Yu Gu, Jian Li +2
Principal component analysis (PCA) is a fundamental dimension reduction tool in statistics and machine learning. For large and high-dimensional data, computing the PCA (i.e., the s…
math.NA2017★ 11 cited
A Fast Implementation of Singular Value Thresholding Algorithm using Recycling Rank Revealing Randomized Singular Value Decomposition
Yaohang Li, Wenjian Yu
In this paper, we present a fast implementation of the Singular Value Thresholding (SVT) algorithm for matrix completion. A rank-revealing randomized singular value decomposition (…