Matrix concentration inequalities for dependent binary random variables

Fuente: arXiv
Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Adamczak, Radosław, Kavvadias, Ioannis
Format: Preprint
Veröffentlicht: 2025
Schlagworte:
Online-Zugang:
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866916685421740032
author Adamczak, Radosław
Kavvadias, Ioannis
author_facet Adamczak, Radosław
Kavvadias, Ioannis
contents 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 and Solda. For random variables with the Stochastic Covering Property or Strong Rayleigh Property we prove estimates for general functions satisfying certain direction aware matrix bounded difference inequalities, generalizing and strengthening earlier estimates by the first-named author and Polaczyk. We also demonstrate a general decoupling inequality for a class of Banach-space valued quadratic forms in negatively associated random variables and combine it with the matrix Bernstein inequality to generalize results by Tropp, Chrétien and Darses, and Ruetz and Schnass, concerning the operator norm of a random submatrix of a deterministic matrix, drawn by uniform sampling without replacements or rejective sampling, to submatrices given by general Strong Rayleigh sampling schemes.
format Preprint
id arxiv_https___arxiv_org_abs_2504_08138
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Matrix concentration inequalities for dependent binary random variables
Adamczak, Radosław
Kavvadias, Ioannis
Probability
Discrete Mathematics
Functional Analysis
60E15, 60B20
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 and Solda. For random variables with the Stochastic Covering Property or Strong Rayleigh Property we prove estimates for general functions satisfying certain direction aware matrix bounded difference inequalities, generalizing and strengthening earlier estimates by the first-named author and Polaczyk. We also demonstrate a general decoupling inequality for a class of Banach-space valued quadratic forms in negatively associated random variables and combine it with the matrix Bernstein inequality to generalize results by Tropp, Chrétien and Darses, and Ruetz and Schnass, concerning the operator norm of a random submatrix of a deterministic matrix, drawn by uniform sampling without replacements or rejective sampling, to submatrices given by general Strong Rayleigh sampling schemes.
title Matrix concentration inequalities for dependent binary random variables
topic Probability
Discrete Mathematics
Functional Analysis
60E15, 60B20
url https://arxiv.org/abs/2504.08138