Low-Rank Approximation in the Frobenius Norm by Column and Row Subset Selection

Publication date: 26 January 2021

Published in: SIAM Journal on Matrix Analysis and Applications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1908.06059

zbMATH Keywords

low-rank approximation tensors cross approximation column subset selection

Mathematics Subject Classification ID

Numerical methods for low-rank matrix approximation; matrix compression (65F55)

Related Items (4)

Simpler is better: a comparative study of randomized pivoting algorithms for CUR and interpolative decompositions ⋮ Randomized Low-Rank Approximation for Symmetric Indefinite Matrices ⋮ Functional Tucker Approximation Using Chebyshev Interpolation ⋮ Some algorithms for maximum volume and cross approximation of symmetric semidefinite matrices

Uses Software

LAPACK
Chebfun
Chebfun2

Cites Work

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Deterministic Feature Selection for K-Means Clustering
An Extension of Chebfun to Two Dimensions
Fast monte-carlo algorithms for finding low-rank approximations

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