Concentration of norms and eigenvalues of random matrices

DOI10.1016/S0022-1236(03)00198-8zbMath1064.15027arXivmath/0211192OpenAlexW2074916818MaRDI QIDQ1883231

Mark W. Meckes

Publication date: 1 October 2004

Published in: Journal of Functional Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/math/0211192

zbMATH Keywords

eigenvaluesrandom matriceslarge deviationssingular valuesconcentration of measureconcentration of normsTalagrand's isoperimetric inequality

Mathematics Subject Classification ID

Inequalities involving eigenvalues and eigenvectors (15A42) Norms of matrices, numerical range, applications of functional analysis to matrix theory (15A60) Miscellaneous inequalities involving matrices (15A45) Large deviations (60F10) Random matrices (algebraic aspects) (15B52)

Related Items (11)

Erratum to: Outliers in the spectrum of iid matrices with bounded rank perturbations ⋮ Nonasymptotic upper bounds for the reconstruction error of PCA ⋮ Separating populations with wide data: a spectral analysis ⋮ Separating Populations with Wide Data: A Spectral Analysis ⋮ Random matrices, nonbacktracking walks, and orthogonal polynomials ⋮ Singular vectors under random perturbation ⋮ Concentration for noncommutative polynomials in random matrices ⋮ Concentration of the empirical spectral distribution of random matrices with dependent entries ⋮ Singular value decomposition of large random matrices (for two-way classification of microarrays) ⋮ RANDOM MATRICES: SHARP CONCENTRATION OF EIGENVALUES ⋮ Random non-Abelian G-circulant matrices. Spectrum of random convolution operators on large finite groups

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