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Consider $n$ complex random matrices $X_1,\ldots,X_n$ of size $d\times d$ sampled i.i.d. from a distribution with mean $E[X]=\mu$. While the concentration of averages of these matrices is well-studied, the concentration of other functions…

Probability · Mathematics 2020-03-16 Tarun Kathuria , Satyaki Mukherjee , Nikhil Srivastava

We present a non-asymptotic concentration inequality for the random matrix product \begin{equation}\label{eq:Zn} Z_n = \left(I_d-\alpha X_n\right)\left(I_d-\alpha X_{n-1}\right)\cdots \left(I_d-\alpha X_1\right), \end{equation} where…

Probability · Mathematics 2020-08-20 Sina Baghal

In this paper we study the concentration properties for the eigenvalues of kernel matrices, which are central objects in a wide range of kernel methods and, more recently, in network analysis. We present a set of concentration inequalities…

Machine Learning · Statistics 2020-10-27 Ernesto Araya Valdivia

Starting from concentration of measure hypotheses on $m$ random vectors $Z_1,\ldots, Z_m$, this article provides an expression of the concentration of functionals $\phi(Z_1,\ldots, Z_m)$ where the variations of $\phi$ on each variable…

Probability · Mathematics 2023-06-27 Cosme Louart , Romain Couillet

This paper develops nonasymptotic growth and concentration bounds for a product of independent random matrices. These results sharpen and generalize recent work of Henriksen-Ward, and they are similar in spirit to the results of…

Probability · Mathematics 2020-03-12 De Huang , Jonathan Niles-Weed , Joel A. Tropp , Rachel Ward

We study the matrix discrepancy problem in the average-case setting. Given a sequence of $m \times m$ symmetric matrices $A_1,\ldots,A_n$, its discrepancy is defined as the minimal spectral norm over all signed sums $\sum_{i=1}^n x_iA_i$…

Probability · Mathematics 2025-10-07 Dmitriy Kunisky , Timm Oertel , Nicola Wengiel , Peiyuan Zhang

We establish, under a moment matching hypothesis, the local universality of the correlation functions associated with products of $M$ independent iid random matrices, as $M$ is fixed, and the sizes of the matrices tend to infinity. This…

Probability · Mathematics 2019-04-25 Phil Kopel , Sean O'Rourke , Van Vu

Matrix concentration inequalities provide information about the probability that a random matrix is close to its expectation with respect to the $l_2$ operator norm. This paper uses semigroup methods to derive sharp nonlinear matrix…

Probability · Mathematics 2021-01-08 De Huang , Joel A. Tropp

We prove Bernstein-type matrix concentration inequalities for linear combinations with matrix coefficients of binary random variables satisfying certain $\ell_\infty$-independence assumptions, complementing recent results by Kaufman, Kyng…

Probability · Mathematics 2025-04-14 Radosław Adamczak , Ioannis Kavvadias

Let ${\cal X }=XX^{\prime}$ be a random matrix associated with a centered $r$-column centered Gaussian vector $X$ with a covariance matrix $P$. In this article we compute expectations of matrix-products of the form $\prod_{1\leq i\leq…

Statistics Theory · Mathematics 2017-03-03 Pierre Del Moral , Adrian N. Bishop

We investigate concentration properties of spectral measures of Hermitian random matrices with partially dependent entries. More precisely, let $X_n$ be a Hermitian random matrix of size $n\times n$ that can be split into independent blocks…

Probability · Mathematics 2020-07-31 Bartłomiej Polaczyk

Matrix concentration inequalities give bounds for the spectral-norm deviation of a random matrix from its expected value. These results have a weak dimensional dependence that is sometimes, but not always, necessary. This paper identifies…

Probability · Mathematics 2016-08-05 Joel A. Tropp

For each $n$, let $A_n=(\sigma_{ij})$ be an $n\times n$ deterministic matrix and let $X_n=(X_{ij})$ be an $n\times n$ random matrix with i.i.d. centered entries of unit variance. We study the asymptotic behavior of the empirical spectral…

Probability · Mathematics 2020-08-03 Nicholas A. Cook , Walid Hachem , Jamal Najim , David Renfrew

We study the spectral norm of matrices M that can be factored as M=BA, where A is a random matrix with independent mean zero entries, and B is a fixed matrix. Under the (4+epsilon)-th moment assumption on the entries of A, we show that the…

Probability · Mathematics 2016-12-23 Roman Vershynin

In this short note, we study the behaviour of a product of matrices with a simultaneous renormalization. Namely, for any sequence $(A\_n)\_{n\in \mathbb{N}}$ of $d\times d$ complex matrices whose mean $A$ exists and whose norms' means are…

Dynamical Systems · Mathematics 2017-12-12 Jordan Emme , Pascal Hubert

A generalization of the Bernstein matrix concentration inequality to random tensors of general order is proposed. This generalization is based on the use of Einstein products between tensors, from which a strong link can be established…

Statistics Theory · Mathematics 2021-05-31 Z. Luo , L. Qi , Ph. L. Toint

In this paper, we study moment and concentration inequalities for the spectral norm of sums of dependent random matrices. We establish novel Rosenthal-Burkholder inequalities for discrete-time matrix local martingales,…

Probability · Mathematics 2025-11-13 Yang Peng , Yuchen Xin , Zhihua Zhang

Let $P_n$ be the $n$-step right product $A_1\cdots A_n$, where $A_1,A_2,\dots$ is a given infinite sequence of $d\times d$ matrices with nonnegative entries. In a wide range of situations, the normalized matrix product $P_n/{\Vert…

Probability · Mathematics 2014-12-30 Éric Olivier , Alain Thomas

We present some extensions of Bernstein's concentration inequality for random matrices. This inequality has become a useful and powerful tool for many problems in statistics, signal processing and theoretical computer science. The main…

Probability · Mathematics 2017-04-18 Stanislav Minsker

We consider the stochastic integrals of multivariate point processes and study their concentration phenomena. In particular, we obtain a Bernstein type of concentration inequality through Dol\'eans-Dade exponential formula and a uniform…

Probability · Mathematics 2017-03-24 Hanchao Wang , Zhengyan Lin , Zhonggen Su
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