From Random Matrices to Monte Carlo Integration Via Gaussian Quadrature

Abstract

We introduced in [1] a new Monte Carlo estimator that relies on determinantal point processes (DPPs). We were initially motivated by peculiar properties of results from random matrix theory. This motivation is absent from the original paper [1], so we develop it here. Then, we give a non-technical overview of the contents of [1], insisting on points that may be of interest to the statistical signal processing audience.