Victor Picheny

Publication Activity (10 Years)

Years Active: 2012-2023
Publications (10 Years): 37

Top Topics

Gaussian Process

Optimization Methods

Top Venues

J. Glob. Optim.

Publications

Henry B. Moss, Sebastian W. Ober, Victor Picheny
Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation. AISTATS (2023)
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
Trieste: Efficiently Exploring The Depths of Black-box Functions with TensorFlow. CoRR (2023)
Youssef Diouane, Victor Picheny, Rodolphe Le Riche, Alexandre Scotto Di Perrotolo
TREGO: a trust-region framework for efficient global optimization. J. Glob. Optim. 86 (1) (2023)
Louis C. Tiao, Vincent Dutordoir, Victor Picheny
Spherical Inducing Features for Orthogonally-Decoupled Gaussian Processes. ICML (2023)
Henry B. Moss, Sebastian W. Ober, Victor Picheny
Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation. CoRR (2023)
Louis C. Tiao, Vincent Dutordoir, Victor Picheny
Spherical Inducing Features for Orthogonally-Decoupled Gaussian Processes. CoRR (2023)
Andrei Paleyes, Henry B. Moss, Victor Picheny, Piotr Zulawski, Felix Newman
A penalisation method for batch multi-objective Bayesian optimisation with application in heat exchanger design. CoRR (2022)
Victor Picheny, Henry B. Moss, Léeonard Torossian, Nicolas Durrande
Bayesian quantile and expectile optimisation. UAI (2022)
Paul E. Chang, Prakhar Verma, St John, Victor Picheny, Henry B. Moss, Arno Solin
Fantasizing with Dual GPs in Bayesian Optimization and Active Learning. CoRR (2022)
Henry B. Moss, Sebastian W. Ober, Victor Picheny
Information-theoretic Inducing Point Placement for High-throughput Bayesian Optimisation. CoRR (2022)
Sattar Vakili, Henry B. Moss, Artem Artemev, Vincent Dutordoir, Victor Picheny
Scalable Thompson Sampling using Sparse Gaussian Process Models. NeurIPS (2021)
Sattar Vakili, Kia Khezeli, Victor Picheny
On Information Gain and Regret Bounds in Gaussian Process Bandits. AISTATS (2021)
Sattar Vakili, Victor Picheny, Artem Artemev
Scalable Thompson Sampling using Sparse Gaussian Process Models. CoRR (2020)
François Bachoc, Céline Helbert, Victor Picheny
Gaussian process optimization with failures: classification and convergence proof. J. Glob. Optim. 78 (3) (2020)
Sattar Vakili, Victor Picheny, Nicolas Durrande
Regret Bounds for Noise-Free Bayesian Optimization. CoRR (2020)
David Gaudrie, Rodolphe Le Riche, Victor Picheny, Benoit Enaux, Vincent Herbert
Targeting solutions in Bayesian multi-objective optimization: sequential and batch versions. Ann. Math. Artif. Intell. 88 (1-3) (2020)
Léonard Torossian, Victor Picheny, Nicolas Durrande
Bayesian Quantile and Expectile Optimisation. CoRR (2020)
Mickaël Binois, Victor Picheny, Patrick Taillandier, Abderrahmane Habbal
The Kalai-Smorodinsky solution for many-objective Bayesian optimization. J. Mach. Learn. Res. 21 (2020)
Victor Picheny, Vincent Dutordoir, Artem Artemev, Nicolas Durrande
Automatic Tuning of Stochastic Gradient Descent with Bayesian Optimisation. CoRR (2020)
Sattar Vakili, Kia Khezeli, Victor Picheny
On Information Gain and Regret Bounds in Gaussian Process Bandits. CoRR (2020)
Léonard Torossian, Victor Picheny, Robert Faivre, Aurélien Garivier
A review on quantile regression for stochastic computer experiments. Reliab. Eng. Syst. Saf. 201 (2020)
Victor Picheny, Vincent Dutordoir, Artem Artemev, Nicolas Durrande
Automatic Tuning of Stochastic Gradient Descent with Bayesian Optimisation. ECML/PKDD (3) (2020)
Léonard Torossian, Aurélien Garivier, Victor Picheny
$\mathcal{X}$-Armed Bandits: Optimizing Quantiles, CVaR and Other Risks. ACML (2019)
Victor Picheny, Rémi Servien, Nathalie Villa-Vialaneix
Interpretable sparse SIR for functional data. Stat. Comput. 29 (2) (2019)
Léonard Torossian, Aurélien Garivier, Victor Picheny
X-Armed Bandits: Optimizing Quantiles and Other Risks. CoRR (2019)
Léonard Torossian, Victor Picheny, Robert Faivre, Aurélien Garivier
A Review on Quantile Regression for Stochastic Computer Experiments. CoRR (2019)
Victor Picheny, Sattar Vakili, Artem Artemev
Ordinal Bayesian Optimisation. CoRR (2019)
Victor Picheny, Mickaël Binois, Abderrahmane Habbal
A Bayesian optimization approach to find Nash equilibria. J. Glob. Optim. 73 (1) (2019)
David Gaudrie, Rodolphe Le Riche, Victor Picheny, Benoit Enaux, Vincent Herbert
Modeling and Optimization with Gaussian Processes in Reduced Eigenbases - Extended Version. CoRR (2019)
David Gaudrie, Rodolphe Le Riche, Victor Picheny, Benoit Enaux, Vincent Herbert
Targeting Solutions in Bayesian Multi-Objective Optimization: Sequential and Parallel Versions. CoRR (2018)
David Gaudrie, Rodolphe Le Riche, Victor Picheny, Benoit Enaux, Vincent Herbert
Targeting Well-Balanced Solutions in Multi-Objective Bayesian Optimization Under a Restricted Budget. LION (2018)
Magali Champion, Victor Picheny, Matthieu Vignes
-penalized likelihood. Stat. Comput. 28 (6) (2018)
David Gaudrie, Rodolphe Le Riche, Victor Picheny, Benoit Enaux, Vincent Herbert
Budgeted Multi-Objective Optimization with a Focus on the Central Part of the Pareto Front - Extended Version. CoRR (2018)
Magali Champion, Victor Picheny, Matthieu Vignes
-penalized likelihood. Stat. Comput. 28 (4) (2018)
Hamed Jalali, Inneke Van Nieuwenhuyse, Victor Picheny
Comparison of Kriging-based algorithms for simulation optimization with heterogeneous noise. Eur. J. Oper. Res. 261 (1) (2017)
Victor Picheny, David Ginsbourger, Tipaluck Krityakierne
Comment: Some Enhancements Over the Augmented Lagrangian Approach. Technometrics 58 (1) (2016)
Victor Picheny, Robert B. Gramacy, Stefan M. Wild, Sébastien Le Digabel
Bayesian optimization under mixed constraints with a slack-variable augmented Lagrangian. NIPS (2016)
Victor Picheny
Multiobjective optimization using Gaussian process emulators via stepwise uncertainty reduction. Stat. Comput. 25 (6) (2015)
Clément Chevalier, Victor Picheny, David Ginsbourger
KrigInv: An efficient and user-friendly implementation of batch-sequential inversion strategies based on kriging. Comput. Stat. Data Anal. 71 (2014)
Victor Picheny, David Ginsbourger
Noisy kriging-based optimization methods: A unified implementation within the DiceOptim package. Comput. Stat. Data Anal. 71 (2014)
Clément Chevalier, Julien Bect, David Ginsbourger, Emmanuel Vázquez, Victor Picheny, Yann Richet
Fast Parallel Kriging-Based Stepwise Uncertainty Reduction With Application to the Identification of an Excursion Set. Technometrics 56 (4) (2014)
Victor Picheny
A Stepwise uncertainty reduction approach to constrained global optimization. AISTATS (2014)
Victor Picheny, David Ginsbourger, Yann Richet, Gregory Caplin
Rejoinder. Technometrics 55 (1) (2013)
Victor Picheny, David Ginsbourger, Yann Richet, Gregory Caplin
Quantile-Based Optimization of Noisy Computer Experiments With Tunable Precision. Technometrics 55 (1) (2013)
Victor Picheny, David Ginsbourger
A Nonstationary Space-Time Gaussian Process Model for Partially Converged Simulations. SIAM/ASA J. Uncertain. Quantification 1 (1) (2013)
Julien Bect, David Ginsbourger, Ling Li, Victor Picheny, Emmanuel Vázquez
Sequential design of computer experiments for the estimation of a probability of failure. Stat. Comput. 22 (3) (2012)