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ORCIDVictor Picheny
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2020 – today
- 2023
[j19]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): 1-23 (2023)- [c10]Henry B. Moss, Sebastian W. Ober, Victor Picheny:
Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation. AISTATS 2023: 5213-5230 - [c9]Louis C. Tiao, Vincent Dutordoir, Victor Picheny:
Spherical Inducing Features for Orthogonally-Decoupled Gaussian Processes. ICML 2023: 34143-34160 - [p1]Mickaël Binois, Abderrahmane Habbal, Victor Picheny:
A Game Theoretic Perspective on Bayesian Many-Objective Optimization. Many-Criteria Optimization and Decision Analysis 2023: 299-316 - [i17]Henry B. Moss, Sebastian W. Ober, Victor Picheny:
Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation. CoRR abs/2301.10123 (2023) - [i16]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 abs/2302.08436 (2023) - [i15]Louis C. Tiao, Vincent Dutordoir, Victor Picheny:
Spherical Inducing Features for Orthogonally-Decoupled Gaussian Processes. CoRR abs/2304.14034 (2023) - 2022
- [c8]Victor Picheny, Henry B. Moss, Léeonard Torossian, Nicolas Durrande:
Bayesian quantile and expectile optimisation. UAI 2022: 1623-1633 - [i14]Henry B. Moss, Sebastian W. Ober, Victor Picheny:
Information-theoretic Inducing Point Placement for High-throughput Bayesian Optimisation. CoRR abs/2206.02437 (2022) - [i13]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 abs/2206.13326 (2022) - [i12]Paul E. Chang, Prakhar Verma, S. T. John, Victor Picheny, Henry B. Moss, Arno Solin:
Fantasizing with Dual GPs in Bayesian Optimization and Active Learning. CoRR abs/2211.01053 (2022) - 2021
- [c7]Sattar Vakili, Kia Khezeli, Victor Picheny:
On Information Gain and Regret Bounds in Gaussian Process Bandits. AISTATS 2021: 82-90 - [c6]Sattar Vakili, Henry B. Moss, Artem Artemev, Vincent Dutordoir, Victor Picheny:
Scalable Thompson Sampling using Sparse Gaussian Process Models. NeurIPS 2021: 5631-5643 - 2020
- [j18]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): 187-212 (2020) - [j17]François Bachoc, Céline Helbert, Victor Picheny:
Gaussian process optimization with failures: classification and convergence proof. J. Glob. Optim. 78(3): 483-506 (2020) - [j16]Mickaël Binois, Victor Picheny, Patrick Taillandier, Abderrahmane Habbal:
The Kalai-Smorodinsky solution for many-objective Bayesian optimization. J. Mach. Learn. Res. 21: 150:1-150:42 (2020) - [j15]Léonard Torossian, Victor Picheny, Robert Faivre, Aurélien Garivier:
A review on quantile regression for stochastic computer experiments. Reliab. Eng. Syst. Saf. 201: 106858 (2020) - [c5]Victor Picheny, Vincent Dutordoir, Artem Artemev, Nicolas Durrande:
Automatic Tuning of Stochastic Gradient Descent with Bayesian Optimisation. ECML/PKDD (3) 2020: 431-446 - [i11]Léonard Torossian, Victor Picheny, Nicolas Durrande:
Bayesian Quantile and Expectile Optimisation. CoRR abs/2001.04833 (2020) - [i10]Sattar Vakili, Victor Picheny, Nicolas Durrande:
Regret Bounds for Noise-Free Bayesian Optimization. CoRR abs/2002.05096 (2020) - [i9]Sattar Vakili, Victor Picheny, Artem Artemev:
Scalable Thompson Sampling using Sparse Gaussian Process Models. CoRR abs/2006.05356 (2020) - [i8]Victor Picheny, Vincent Dutordoir, Artem Artemev, Nicolas Durrande:
Automatic Tuning of Stochastic Gradient Descent with Bayesian Optimisation. CoRR abs/2006.14376 (2020) - [i7]Sattar Vakili, Kia Khezeli, Victor Picheny:
On Information Gain and Regret Bounds in Gaussian Process Bandits. CoRR abs/2009.06966 (2020)
2010 – 2019
- 2019
- [j14]Victor Picheny, Mickaël Binois, Abderrahmane Habbal:
A Bayesian optimization approach to find Nash equilibria. J. Glob. Optim. 73(1): 171-192 (2019) - [j13]Victor Picheny, Rémi Servien, Nathalie Villa-Vialaneix:
Interpretable sparse SIR for functional data. Stat. Comput. 29(2): 255-267 (2019) - [c4]Léonard Torossian, Aurélien Garivier, Victor Picheny:
$\mathcal{X}$-Armed Bandits: Optimizing Quantiles, CVaR and Other Risks. ACML 2019: 252-267 - [i6]Léonard Torossian, Victor Picheny, Robert Faivre, Aurélien Garivier:
A Review on Quantile Regression for Stochastic Computer Experiments. CoRR abs/1901.07874 (2019) - [i5]Léonard Torossian, Aurélien Garivier, Victor Picheny:
X-Armed Bandits: Optimizing Quantiles and Other Risks. CoRR abs/1904.08205 (2019) - [i4]David Gaudrie, Rodolphe Le Riche, Victor Picheny, Benoit Enaux, Vincent Herbert:
Modeling and Optimization with Gaussian Processes in Reduced Eigenbases - Extended Version. CoRR abs/1908.11272 (2019) - [i3]Victor Picheny, Sattar Vakili, Artem Artemev:
Ordinal Bayesian Optimisation. CoRR abs/1912.02493 (2019) - 2018
- [j12]Magali Champion, Victor Picheny, Matthieu Vignes:
Inferring large graphs using ℓ1 -penalized likelihood. Stat. Comput. 28(4): 905-921 (2018) - [j11]Magali Champion, Victor Picheny, Matthieu Vignes:
Correction to: Inferring large graphs using ℓ1-penalized likelihood. Stat. Comput. 28(6): 1231 (2018) - [c3]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: 175-179 - [i2]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 abs/1809.10482 (2018) - [i1]David Gaudrie, Rodolphe Le Riche, Victor Picheny, Benoit Enaux, Vincent Herbert:
Targeting Solutions in Bayesian Multi-Objective Optimization: Sequential and Parallel Versions. CoRR abs/1811.03862 (2018) - 2017
- [j10]Hamed Jalali, Inneke Van Nieuwenhuyse, Victor Picheny:
Comparison of Kriging-based algorithms for simulation optimization with heterogeneous noise. Eur. J. Oper. Res. 261(1): 279-301 (2017) - 2016
- [j9]Victor Picheny, David Ginsbourger, Tipaluck Krityakierne:
Comment: Some Enhancements Over the Augmented Lagrangian Approach. Technometrics 58(1): 17-21 (2016) - [c2]Victor Picheny, Robert B. Gramacy, Stefan M. Wild, Sébastien Le Digabel:
Bayesian optimization under mixed constraints with a slack-variable augmented Lagrangian. NIPS 2016: 1435-1443 - 2015
- [j8]Victor Picheny:
Multiobjective optimization using Gaussian process emulators via stepwise uncertainty reduction. Stat. Comput. 25(6): 1265-1280 (2015) - 2014
- [j7]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: 1021-1034 (2014) - [j6]Victor Picheny, David Ginsbourger:
Noisy kriging-based optimization methods: A unified implementation within the DiceOptim package. Comput. Stat. Data Anal. 71: 1035-1053 (2014) - [j5]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): 455-465 (2014) - [c1]Victor Picheny:
A Stepwise uncertainty reduction approach to constrained global optimization. AISTATS 2014: 787-795 - 2013
- [j4]Victor Picheny, David Ginsbourger:
A Nonstationary Space-Time Gaussian Process Model for Partially Converged Simulations. SIAM/ASA J. Uncertain. Quantification 1(1): 57-78 (2013) - [j3]Victor Picheny, David Ginsbourger, Yann Richet, Gregory Caplin:
Quantile-Based Optimization of Noisy Computer Experiments With Tunable Precision. Technometrics 55(1): 2-13 (2013) - [j2]Victor Picheny, David Ginsbourger, Yann Richet, Gregory Caplin:
Rejoinder. Technometrics 55(1): 31-36 (2013) - 2012
- [j1]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): 773-793 (2012)
Coauthor Index
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