Victor Picheny

According to our database, Victor Picheny authored at least 42 papers between 2012 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

TREGO: a trust-region framework for efficient global optimization.

Youssef Diouane, Victor Picheny, Rodolphe Le Riche, Alexandre Scotto Di Perrotolo

J. Glob. Optim., May, 2023

A Game Theoretic Perspective on Bayesian Many-Objective Optimization.

Mickaël Binois, Abderrahmane Habbal, Victor Picheny

Proceedings of the Many-Criteria Optimization and Decision Analysis: State-of-the-Art, 2023

Trieste: Efficiently Exploring The Depths of Black-box Functions with TensorFlow.

Victor Picheny, Joel Berkeley, Henry B. Moss, Hrvoje Stojic, Uri Granta, Sebastian W. Ober, Artem Artemev, Khurram Ghani, Alexander Goodall, Andrei Paleyes, Sattar Vakili, Sergio Pascual-Diaz, Stratis Markou, Jixiang Qing, Nasrulloh R. B. S. Loka, Ivo Couckuyt

CoRR, 2023

Spherical Inducing Features for Orthogonally-Decoupled Gaussian Processes.

Louis C. Tiao, Vincent Dutordoir, Victor Picheny

Proceedings of the International Conference on Machine Learning, 2023

Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation.

Henry B. Moss, Sebastian W. Ober, Victor Picheny

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Fantasizing with Dual GPs in Bayesian Optimization and Active Learning.

Paul E. Chang, Prakhar Verma, S. T. John, Victor Picheny, Henry B. Moss, Arno Solin

CoRR, 2022

A penalisation method for batch multi-objective Bayesian optimisation with application in heat exchanger design.

Andrei Paleyes, Henry B. Moss, Victor Picheny, Piotr Zulawski, Felix Newman

CoRR, 2022

Information-theoretic Inducing Point Placement for High-throughput Bayesian Optimisation.

Henry B. Moss, Sebastian W. Ober, Victor Picheny

CoRR, 2022

Bayesian quantile and expectile optimisation.

Victor Picheny, Henry B. Moss, Léeonard Torossian, Nicolas Durrande

Proceedings of the Uncertainty in Artificial Intelligence, 2022

2021

Scalable Thompson Sampling using Sparse Gaussian Process Models.

Sattar Vakili, Henry B. Moss, Artem Artemev, Vincent Dutordoir, Victor Picheny

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On Information Gain and Regret Bounds in Gaussian Process Bandits.

Sattar Vakili, Kia Khezeli, Victor Picheny

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

A review on quantile regression for stochastic computer experiments.

Léonard Torossian, Victor Picheny, Robert Faivre, Aurélien Garivier

Reliab. Eng. Syst. Saf., 2020

The Kalai-Smorodinsky solution for many-objective Bayesian optimization.

Mickaël Binois, Victor Picheny, Patrick Taillandier, Abderrahmane Habbal

J. Mach. Learn. Res., 2020

Gaussian process optimization with failures: classification and convergence proof.

François Bachoc, Céline Helbert, Victor Picheny

J. Glob. Optim., 2020

Scalable Thompson Sampling using Sparse Gaussian Process Models.

Sattar Vakili, Victor Picheny, Artem Artemev

CoRR, 2020

Regret Bounds for Noise-Free Bayesian Optimization.

Sattar Vakili, Victor Picheny, Nicolas Durrande

CoRR, 2020

Bayesian Quantile and Expectile Optimisation.

Léonard Torossian, Victor Picheny, Nicolas Durrande

CoRR, 2020

Targeting solutions in Bayesian multi-objective optimization: sequential and batch versions.

David Gaudrie, Rodolphe Le Riche, Victor Picheny, Benoit Enaux, Vincent Herbert

Ann. Math. Artif. Intell., 2020

Automatic Tuning of Stochastic Gradient Descent with Bayesian Optimisation.

Victor Picheny, Vincent Dutordoir, Artem Artemev, Nicolas Durrande

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

2019

Interpretable sparse SIR for functional data.

Victor Picheny, Rémi Servien, Nathalie Villa-Vialaneix

Stat. Comput., 2019

A Bayesian optimization approach to find Nash equilibria.

Victor Picheny, Mickaël Binois, Abderrahmane Habbal

J. Glob. Optim., 2019

Ordinal Bayesian Optimisation.

Victor Picheny, Sattar Vakili, Artem Artemev

CoRR, 2019

Modeling and Optimization with Gaussian Processes in Reduced Eigenbases - Extended Version.

David Gaudrie, Rodolphe Le Riche, Victor Picheny, Benoit Enaux, Vincent Herbert

CoRR, 2019

X-Armed Bandits: Optimizing Quantiles and Other Risks.

Léonard Torossian, Aurélien Garivier, Victor Picheny

CoRR, 2019

$\mathcal{X}$-Armed Bandits: Optimizing Quantiles, CVaR and Other Risks.

Léonard Torossian, Aurélien Garivier, Victor Picheny

Proceedings of The 11th Asian Conference on Machine Learning, 2019

2018

Correction to: Inferring large graphs using ℓ₁-penalized likelihood.

Magali Champion, Victor Picheny, Matthieu Vignes

Stat. Comput., 2018

Inferring large graphs using ℓ₁ -penalized likelihood.

Magali Champion, Victor Picheny, Matthieu Vignes

Stat. Comput., 2018

Targeting Solutions in Bayesian Multi-Objective Optimization: Sequential and Parallel Versions.

David Gaudrie, Rodolphe Le Riche, Victor Picheny, Benoit Enaux, Vincent Herbert

CoRR, 2018

Budgeted Multi-Objective Optimization with a Focus on the Central Part of the Pareto Front - Extended Version.

David Gaudrie, Rodolphe Le Riche, Victor Picheny, Benoit Enaux, Vincent Herbert

CoRR, 2018

Targeting Well-Balanced Solutions in Multi-Objective Bayesian Optimization Under a Restricted Budget.

David Gaudrie, Rodolphe Le Riche, Victor Picheny, Benoit Enaux, Vincent Herbert

Proceedings of the Learning and Intelligent Optimization - 12th International Conference, 2018

2017

Comparison of Kriging-based algorithms for simulation optimization with heterogeneous noise.

Hamed Jalali, Inneke Van Nieuwenhuyse, Victor Picheny

Eur. J. Oper. Res., 2017

2016

Comment: Some Enhancements Over the Augmented Lagrangian Approach.

Victor Picheny, David Ginsbourger, Tipaluck Krityakierne

Technometrics, 2016

Bayesian optimization under mixed constraints with a slack-variable augmented Lagrangian.

Victor Picheny, Robert B. Gramacy, Stefan M. Wild, Sébastien Le Digabel

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Multiobjective optimization using Gaussian process emulators via stepwise uncertainty reduction.

Victor Picheny

Stat. Comput., 2015

2014

Fast Parallel Kriging-Based Stepwise Uncertainty Reduction With Application to the Identification of an Excursion Set.

Clément Chevalier, Julien Bect, David Ginsbourger, Emmanuel Vázquez, Victor Picheny, Yann Richet

Technometrics, 2014

Noisy kriging-based optimization methods: A unified implementation within the DiceOptim package.

Victor Picheny, David Ginsbourger

Comput. Stat. Data Anal., 2014

KrigInv: An efficient and user-friendly implementation of batch-sequential inversion strategies based on kriging.

Clément Chevalier, Victor Picheny, David Ginsbourger

Comput. Stat. Data Anal., 2014

A Stepwise uncertainty reduction approach to constrained global optimization.

Victor Picheny

Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013

Rejoinder.

Victor Picheny, David Ginsbourger, Yann Richet, Gregory Caplin

Technometrics, 2013

Quantile-Based Optimization of Noisy Computer Experiments With Tunable Precision.

Victor Picheny, David Ginsbourger, Yann Richet, Gregory Caplin

Technometrics, 2013

A Nonstationary Space-Time Gaussian Process Model for Partially Converged Simulations.

Victor Picheny, David Ginsbourger

SIAM/ASA J. Uncertain. Quantification, 2013

2012

Sequential design of computer experiments for the estimation of a probability of failure.

Julien Bect, David Ginsbourger, Ling Li, Victor Picheny, Emmanuel Vázquez

Stat. Comput., 2012