Bayesian Quantile and Expectile Optimisation

no code implementations • 12 Jan 2020 • Victor Picheny, Henry Moss, Léonard Torossian, Nicolas Durrande

In this paper, we propose new variational models for Bayesian quantile and expectile regression that are well-suited for heteroscedastic noise settings.

Bayesian Optimisation Gaussian Processes +1

X-Armed Bandits: Optimizing Quantiles, CVaR and Other Risks

no code implementations • 17 Apr 2019 • Léonard Torossian, Aurélien Garivier, Victor Picheny

We finally present numerical experiments that show a dramatic impact of tight bounds for the optimization of quantiles and CVaR.

Decision Making

A Review on Quantile Regression for Stochastic Computer Experiments

no code implementations • 23 Jan 2019 • Léonard Torossian, Victor Picheny, Robert Faivre, Aurélien Garivier

We report on an empirical study of the main strategies for quantile regression in the context of stochastic computer experiments.

Diversity quantile regression