%0 Conference Paper %F Oral %T Bias and Variance in the Bayesian Subset Simulation Algorithm %+ Laboratoire des signaux et systèmes (L2S) %+ Méthodes d'Analyse Stochastique des Codes et Traitements Numériques (GdR MASCOT-NUM) %+ Management des Risques Industriels (EDF R&D MRI) %A Bect, Julien %A Sueur, Roman %A Vazquez, Emmanuel %F Invité %< sans comité de lecture %B 2016 SIAM Conference on Uncertainty Quantification %C Lausanne, Switzerland %8 2016-04-05 %D 2016 %Z Statistics [stat]/Computation [stat.CO]Conference papers %X 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. %G English %L hal-01377732 %U https://centralesupelec.hal.science/hal-01377732 %~ CNRS %~ UNIV-PSUD %~ SUP_LSS %~ SUP_SIGNAUX %~ CENTRALESUPELEC %~ UNIV-PARIS-SACLAY %~ UNIV-PSUD-SACLAY %~ CENTRALESUPELEC-SACLAY %~ EDF %~ GS-ENGINEERING %~ GS-COMPUTER-SCIENCE