John A. Hoffnagle, William D. Hinsberg, et al.
Microlithography 2003
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.
John A. Hoffnagle, William D. Hinsberg, et al.
Microlithography 2003
W.F. Cody, H.M. Gladney, et al.
SPIE Medical Imaging 1994
Satoshi Hada
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
M. Tismenetsky
International Journal of Computer Mathematics