Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Torossian, Léonard"'
Bayesian optimisation (BO) is widely used to optimise stochastic black box functions. While most BO approaches focus on optimising conditional expectations, many applications require risk-averse strategies and alternative criteria accounting for the
Externí odkaz:
http://arxiv.org/abs/2001.04833
We propose and analyze StoROO, an algorithm for risk optimization on stochastic black-box functions derived from StoOO. Motivated by risk-averse decision making fields like agriculture, medicine, biology or finance, we do not focus on the mean payoff
Externí odkaz:
http://arxiv.org/abs/1904.08205
We report on an empirical study of the main strategies for quantile regression in the context of stochastic computer experiments. To ensure adequate diversity, six metamodels are presented, divided into three categories based on order statistics, fun
Externí odkaz:
http://arxiv.org/abs/1901.07874
Publikováno v:
In Reliability Engineering and System Safety September 2020 201
Autor:
Torossian, Léonard
Publikováno v:
Statistics [math.ST]. MITT, 2019. English. ⟨NNT : ⟩
Statistics [math.ST]. MITT, 2019. English
Statistics [math.ST]. MITT, 2019. English
This thesis presents methods for estimation and optimization of stochastic black boxfunctions. Motivated by the necessity to take risk-averse decisions in medecine, agriculture or finance, in this study we focus our interest on indicators able to qua
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::c13159f53f9eb1f7464be0cfd50f6d05
https://hal.science/tel-03255973
https://hal.science/tel-03255973
We propose and analyze StoROO, an algorithm for risk optimization on stochastic black-box functions derived from StoOO. Motivated by risk-averse decision making fields like agriculture, medicine, biology or finance, we do not focus on the mean payoff
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______4074::9ef5a034904b262978526ea559513d72
https://hal.archives-ouvertes.fr/hal-02101647/file/quantile.pdf
https://hal.archives-ouvertes.fr/hal-02101647/file/quantile.pdf