Generic variance reduction in Monte Carlo samplers
August 25, 2022 — August 25, 2022
Bayes
estimator distribution
Markov processes
Monte Carlo
probabilistic algorithms
probability
Is it meaningful to talk about “generic” Monte Carlo variance reduction strategies? Let us create this notebook and see if accretes some references.
For now there are a couple of links about optimal sample diversity. There are other strategies available, such as Rao-Blackwellisation.
1 Sample diversity
2 Rao-Blackwellisation
TBD
3 References
Mariet. 2016. “Learning and enforcing diversity with Determinantal Point Processes.”
Roberts, and Rosenthal. 2014. “Minimising MCMC Variance via Diffusion Limits, with an Application to Simulated Tempering.” Annals of Applied Probability.
Sheikh, Phielipp, and Boloni. 2022. “Maximizing Ensemble Diversity in Deep Reinforcement Learning.”