On the variance of Schatten <i>p</i>-norm estimation with Gaussian sketching matrices

Abstract 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 in [W. Kong and G. Valiant, Spectrum estimation from samples, Ann. Statist. 45 2017, 5, 2218–2247] for the case of Gaussian random vectors and provide a sharper bound than previously available.

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Publication Details

Journal
Monte Carlo Methods and Applications
Published
2025-03-27
DOI
https://doi.org/10.1515/mcma-2025-2006
Citations
1
Primary Topic
Random Matrices and Applications
Type
article
Field-Weighted Citation Impact
2.63
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article

On the variance of Schatten p-norm estimation with Gaussian sketching matrices

Tomasz Nowicki, Vasileios Kalantzis, Yingdong Lu, Lior Horesh
1 citations
Monte Carlo Methods and Applications
Random Matrices and Applications
2.63
article

On the variance of Schatten p-norm estimation with Gaussian sketching matrices

Tomasz Nowicki, Vasileios Kalantzis, Yingdong Lu, Lior Horesh
article en
1 citations

Abstract

Abstract 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 in [W. Kong and G. Valiant, Spectrum estimation from samples, Ann. Statist. 45 2017, 5, 2218–2247] for the case of Gaussian random vectors and provide a sharper bound than previously available.

Monte Carlo Methods and ApplicationsVol. 31(2)
IBM (United States) (US)
Openalex Percentile: Top 13%
Random Matrices and Applications
2.63
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