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Motivated by the general matrix deviation inequality for i.i.d ensemble Gaussian matrix, we study its universality property. As a starting point for this problem, we show that this property holds for $\ell_{p}$-norm with $1\leq p< \infty$…

Probability · Mathematics 2023-02-28 Te-Chun Wang , Yuan-Chung Sheu

We prove a Bernstein inequality for vector-valued self-normalized martingales. We first give an alternative perspective of the corresponding sub-Gaussian bound due to Abbasi-Yadkori et al. via a PAC-Bayesian argument with Gaussian priors.…

Probability · Mathematics 2025-01-07 Ingvar Ziemann

We study convergence properties of pseudo-marginal Markov chain Monte Carlo algorithms (Andrieu and Roberts [Ann. Statist. 37 (2009) 697-725]). We find that the asymptotic variance of the pseudo-marginal algorithm is always at least as…

Probability · Mathematics 2015-03-31 Christophe Andrieu , Matti Vihola

Associated to any complex Wishart matrix $W$ of parameters $(dn,dm)$ and any linear map $\varphi:M_n(\mathbb C)\to M_n(\mathbb C)$ is the "block-modified" matrix $\tilde{W}=(id\otimes\varphi)W$. Following some previous work with Nechita, we…

Probability · Mathematics 2020-05-05 Teodor Banica

In this note, we define a Gaussian probability distribution over matrices. We prove some useful properties of this distribution, namely, the fact that marginalization, conditioning, and affine transformations preserve the matrix Gaussian…

Probability · Mathematics 2018-06-22 Shane Barratt

We consider inhomogeneous square random matrices of size $N$ with independent entries of mean 0 and finite variance. We assume that the variance profile of this matrix is doubly stochastic and has a band-like structure with an appropriately…

Probability · Mathematics 2025-08-27 Yi Han

We prove that when suitably normalized, small enough powers of the absolute value of the characteristic polynomial of random Hermitian matrices, drawn from one-cut regular unitary invariant ensembles, converge in law to Gaussian…

Probability · Mathematics 2017-09-19 Nathanaël Berestycki , Christian Webb , Mo Dick Wong

The empirical spectral distribution of Hermitian $K \times K$-block random matrices converges to a deterministic density on the real line with a potential atom at the origin as the dimension of the blocks tends to infinity. In this model…

Probability · Mathematics 2025-11-25 Markus Ebke , Torben Krüger

We study the characteristic polynomial of random permutation matrices following some measures which are invariant by conjugation, including Ewens' measures which are one-parameter deformations of the uniform distribution on the permutation…

Probability · Mathematics 2018-09-17 Valentin Bahier

We prove that there is a residual subset of the Gromov-Hausdorff space (i.e. the space of all compact metric spaces up to isometry endowed with the Gromov-Hausdorff distance) whose points enjoy several unexpected properties. In particular,…

Metric Geometry · Mathematics 2010-03-29 Joël Rouyer

We consider $N\times N$ symmetric or hermitian random matrices with independent, identically distributed entries where the probability distribution for each matrix element is given by a measure $\nu$ with a subexponential decay. We prove…

Mathematical Physics · Physics 2017-08-23 Laszlo Erdos

We pursue various restricted variable generalizations of the Chevalley-Warning theorem for low degree polynomial systems over a finite field. Our first such result involves variables restricted to Cartesian products of the Vandermonde…

Number Theory · Mathematics 2022-01-28 Anurag Bishnoi , Pete L. Clark

We study invariant boundary conditions for one dimensional discrete Gaussian Markov processes, basic toy models of spatial Markov processes in statistical mechanics. More precisely, we give a decomposition of boundary objects in a non…

Probability · Mathematics 2023-05-31 Emilien Bodiot

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

We improve and expand in two directions the theory of norms on complex matrices induced by random vectors. We first provide a simple proof of the classification of weakly unitarily invariant norms on the Hermitian matrices. We use this to…

Functional Analysis · Mathematics 2023-10-26 Ángel Chávez , Stephan Ramon Garcia , Jackson Hurley

This note demonstrates that it is possible to bound the expectation of an arbitrary norm of a random matrix drawn from the Stiefel manifold in terms of the expected norm of a standard Gaussian matrix with the same dimensions. A related…

Probability · Mathematics 2014-04-29 Joel A. Tropp

Marginal likelihood, also known as model evidence, is a fundamental quantity in Bayesian statistics. It is used for model selection using Bayes factors or for empirical Bayes tuning of prior hyper-parameters. Yet, the calculation of…

Methodology · Statistics 2024-09-04 Anindya Bhadra , Ksheera Sagar , David Rowe , Sayantan Banerjee , Jyotishka Datta

Supersymmetric domain-wall spacetimes that lift to Ricci-flat solutions of M-theory admit generalized Heisenberg (2-step nilpotent) isometry groups. These metrics may be obtained from known cohomogeneity one metrics of special holonomy by…

High Energy Physics - Theory · Physics 2009-10-07 G. W. Gibbons , H. Lu , C. N. Pope , K. S. Stelle

We show that the distribution of elements $H$ in the Hessian matrices associated with amorphous materials exhibit singularities $P(H) \sim {\lvert H \rvert}^{\gamma}$ with an exponent $\gamma < 0$, as $\lvert H \rvert \to 0$. We exploit the…

Disordered Systems and Neural Networks · Physics 2020-11-06 Vishnu V. Krishnan , Smarajit Karmakar , Kabir Ramola

We develop an operator-theoretic framework for stability and statistical concentration in nonlinear inverse problems with block-structured parameters. Under a unified set of assumptions combining blockwise Lipschitz geometry, local…

Computer Vision and Pattern Recognition · Computer Science 2026-02-11 Joe-Mei Feng , Hsin-Hsiung Kao