Simple Norm Bounds for Polynomial Random Matrices via Decoupling

Fuente: arXiv
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Autores principales: Tulsiani, Madhur, Wu, June
Formato: Preprint
Publicado: 2024
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author Tulsiani, Madhur
Wu, June
author_facet Tulsiani, Madhur
Wu, June
contents We present a new method for obtaining norm bounds for random matrices, where each entry is a low-degree polynomial in an underlying set of independent real-valued random variables. Such matrices arise in a variety of settings in the analysis of spectral and optimization algorithms, which require understanding the spectrum of a random matrix depending on data obtained as independent samples. Using ideas of decoupling and linearization from analysis, we show a simple way of expressing norm bounds for such matrices, in terms of matrices of lower-degree polynomials corresponding to derivatives. Iterating this method gives a simple bound with an elementary proof, which can recover many bounds previously required more involved techniques.
format Preprint
id arxiv_https___arxiv_org_abs_2412_07936
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Simple Norm Bounds for Polynomial Random Matrices via Decoupling
Tulsiani, Madhur
Wu, June
Probability
Computational Complexity
We present a new method for obtaining norm bounds for random matrices, where each entry is a low-degree polynomial in an underlying set of independent real-valued random variables. Such matrices arise in a variety of settings in the analysis of spectral and optimization algorithms, which require understanding the spectrum of a random matrix depending on data obtained as independent samples. Using ideas of decoupling and linearization from analysis, we show a simple way of expressing norm bounds for such matrices, in terms of matrices of lower-degree polynomials corresponding to derivatives. Iterating this method gives a simple bound with an elementary proof, which can recover many bounds previously required more involved techniques.
title Simple Norm Bounds for Polynomial Random Matrices via Decoupling
topic Probability
Computational Complexity
url https://arxiv.org/abs/2412.07936