6 citations · 6 across the 6 of their papers we have counts for
4 papers · 1 filter
Ordinal Bayesian Optimisation
Victor Picheny, Sattar Vakili, Artem Artemev
Bayesian optimisation is a powerful tool to solve expensive black-box problems, but fails when the stationary assumption made on the objective function is strongly violated, which…
X-Armed Bandits: Optimizing Quantiles, CVaR and Other Risks
Léonard Torossian, Aurélien Garivier, Victor Picheny
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 agricul…
The Kalai-Smorodinski solution for many-objective Bayesian optimization
Mickaël Binois, Victor Picheny, Patrick Taillandier +1
An ongoing aim of research in multiobjective Bayesian optimization is to extend its applicability to a large number of objectives. While coping with a limited budget of evaluations…
A Review on Quantile Regression for Stochastic Computer Experiments
Léonard Torossian, Victor Picheny, Robert Faivre +1
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 p…