William Hinsberg, Joy Cheng, et al.
SPIE Advanced Lithography 2010
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.
William Hinsberg, Joy Cheng, et al.
SPIE Advanced Lithography 2010
Sankar Basu
Journal of the Franklin Institute
Martin Charles Golumbic, Renu C. Laskar
Discrete Applied Mathematics
Jianke Yang, Robin Walters, et al.
ICML 2023