Abstract : The Bayesian Subset Simulation (BSS) algorithm is a recently proposed approach, based on Sequential Monte Carlo simulation and Gaussian process modeling, for the estimation of the probability that $f(X)$ exceeds some thresold $u$ when $f$ is expensive to evaluate and $P(f(X)>u)$ is small. We discuss in this talk the bias an variance of the BSS algorithm, and propose a variant where the bias-variance trade-off is automatically tuned.
https://hal-centralesupelec.archives-ouvertes.fr/hal-01377732
Contributor : Julien Bect
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Submitted on : Friday, October 7, 2016 - 2:59:35 PM
Last modification on : Friday, December 20, 2019 - 11:48:04 AM
