On The Variance of Schatten $p$-Norm Estimation with Gaussian Sketching Matrices

Fuente: arXiv
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Main Authors: Horesh, Lior, Kalantzis, Vasileios, Lu, Yingdong, Nowicki, Tomasz
Format: Preprint
Published: 2024
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author Horesh, Lior
Kalantzis, Vasileios
Lu, Yingdong
Nowicki, Tomasz
author_facet Horesh, Lior
Kalantzis, Vasileios
Lu, Yingdong
Nowicki, Tomasz
contents Monte Carlo matrix trace estimation is a popular randomized technique to estimate the trace of implicitly-defined matrices via averaging quadratic forms across several observations of a random vector. The most common approach to analyze the quality of such estimators is to consider the variance over the total number of observations. In this paper we present a procedure to compute the variance of the estimator proposed by Kong and Valiant [Ann. Statist. 45 (5), pp. 2218 - 2247] for the case of Gaussian random vectors and provide a sharper bound than previously available.
format Preprint
id arxiv_https___arxiv_org_abs_2410_16455
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle On The Variance of Schatten $p$-Norm Estimation with Gaussian Sketching Matrices
Horesh, Lior
Kalantzis, Vasileios
Lu, Yingdong
Nowicki, Tomasz
Statistics Theory
Numerical Analysis
Probability
60-08, 65C05, 65F35
Monte Carlo matrix trace estimation is a popular randomized technique to estimate the trace of implicitly-defined matrices via averaging quadratic forms across several observations of a random vector. The most common approach to analyze the quality of such estimators is to consider the variance over the total number of observations. In this paper we present a procedure to compute the variance of the estimator proposed by Kong and Valiant [Ann. Statist. 45 (5), pp. 2218 - 2247] for the case of Gaussian random vectors and provide a sharper bound than previously available.
title On The Variance of Schatten $p$-Norm Estimation with Gaussian Sketching Matrices
topic Statistics Theory
Numerical Analysis
Probability
60-08, 65C05, 65F35
url https://arxiv.org/abs/2410.16455