A Measure Concentration Effect for Matrices of High, Higher, and Even Higher Dimension

DOI10.1137/20M1376029zbMath1487.15031arXiv2010.13505MaRDI QIDQ5071430

Harry Yserentant

Publication date: 21 April 2022

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

Full work available at URL: https://arxiv.org/abs/2010.13505

zbMATH Keywords

measure concentrationhigh-dimensional matricesrandom projection theorem

Mathematics Subject Classification ID

Random matrices (probabilistic aspects) (60B20) Norms of matrices, numerical range, applications of functional analysis to matrix theory (15A60) Random matrices (algebraic aspects) (15B52)

Related Items (1)

An iterative method for the solution of Laplace-like equations in high and very high space dimensions

Cites Work

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• A mathematical introduction to compressive sensing
• Spectra of graphs
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• On the expansion of solutions of Laplace-like equations into traces of separable higher dimensional functions
• Extensions of Lipschitz mappings into a Hilbert space
• Smallest singular value of a random rectangular matrix
• Eigenvalues and Condition Numbers of Random Matrices
• High-Dimensional Probability
• Tensor Spaces and Numerical Tensor Calculus

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