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.
Authors
- Tomasz Nowicki (ORCID: https://orcid.org/0000-0002-8260-0231)
- Vasileios Kalantzis (ORCID: https://orcid.org/0000-0003-1474-8995)
- Yingdong Lu (ORCID: https://orcid.org/0000-0002-3672-0865)
- Lior Horesh (ORCID: https://orcid.org/0000-0001-6350-0238)
Institutions
- IBM (United States) (US)
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