The probabilistic estimates on the largest and smallest $q$-singular values of random matrices
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Publication:5246840
DOI10.1090/S0025-5718-2014-02895-0zbMath1314.60028MaRDI QIDQ5246840
Publication date: 22 April 2015
Published in: Mathematics of Computation (Search for Journal in Brave)
Martingales with discrete parameter (60G42) Random matrices (probabilistic aspects) (60B20) Sums of independent random variables; random walks (60G50) Large deviations (60F10)
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Cites Work
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- On the distribution of the roots of certain symmetric matrices
- The least singular value of a random square matrix is O\((n ^{- 1/2})\)
- Random matrices: The distribution of the smallest singular values
- Sparsest solutions of underdetermined linear systems via \( \ell _q\)-minimization for \(0<q\leqslant 1\)
- The smallest eigenvalue of a large dimensional Wishart matrix
- On the limit of the largest eigenvalue of the large dimensional sample covariance matrix
- A note on the largest eigenvalue of a large dimensional sample covariance matrix
- A limit theorem for the norm of random matrices
- Condition numbers of random matrices
- Norms of random matrices
- A note on universality of the distribution of the largest eigenvalues in certain sample covariance matrices
- Invertibility of random matrices: norm of the inverse
- The Littlewood-Offord problem and invertibility of random matrices
- On the permanent of random Bernoulli matrices
- Sparse recovery with pre-Gaussian random matrices
- Non-asymptotic theory of random matrices: extreme singular values
- Smooth analysis of the condition number and the least singular value
- A Remark on Stirling's Formula
- On the singularity probability of random Bernoulli matrices
- Restricted isometry properties and nonconvex compressive sensing
- RANDOM MATRICES: THE CIRCULAR LAW
- On the efficiency of algorithms of analysis
- Eigenvalues and Condition Numbers of Random Matrices
- Numerical inverting of matrices of high order
- Probability Theory
