On the best approximation algorithm by low-rank matrices in Chebyshev's norm

DOI10.1134/S0965542522050141zbMath1496.65058WikidataQ114075110 ScholiaQ114075110MaRDI QIDQ2149032

Sergey Morozov, Nikolai L. Zamarashkin, Evgenij E. Tyrtyshnikov

Publication date: 27 June 2022

Published in: Computational Mathematics and Mathematical Physics (Search for Journal in Brave)

zbMATH Keywords

Remez algorithmapproximation by low-rank matricesChebyshev's approximation

Mathematics Subject Classification ID

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

Related Items (3)

A note on error bounds for pseudo skeleton approximations of matrices ⋮ On the optimal rank-1 approximation of matrices in the Chebyshev norm ⋮ On the distance to low-rank matrices in the maximum norm

Uses Software

• OBOE

Cites Work

• Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions
• Hierarchical matrices. A means to efficiently solve elliptic boundary value problems
• A theory of pseudoskeleton approximations
• Pseudo-skeleton approximations with better accuracy estimates
• Why Are Big Data Matrices Approximately Low Rank?
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