Amir Ali Ahmadi, RaphaΓ«l M. Jungers, et al.
SICON
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.
Amir Ali Ahmadi, RaphaΓ«l M. Jungers, et al.
SICON
Salvatore Certo, Anh Pham, et al.
Quantum Machine Intelligence
Mario Blaum, John L. Fan, et al.
IEEE International Symposium on Information Theory - Proceedings
Michael E. Henderson
International Journal of Bifurcation and Chaos in Applied Sciences and Engineering