A Quadrature Rule combining Control Variates and Adaptive Importance Sampling. (arXiv:2205.11890v2 [stat.ML] UPDATED)

Driven by several successful applications such as in stochastic gradient
descent or in Bayesian computation, control variates have become a major tool
for Monte Carlo integration. However, standard methods do not allow the
distribution of the particles to evolve during the algorithm, as is the case in
sequential simulation methods. Within the standard adaptive importance sampling
framework, a simple weighted least squares approach is proposed to improve the
procedure with control variates. The procedure takes the form of a quadrature …

arxiv importance sampling