François Bachoc

53 papers A* 5A 3Journal 44Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Block-Additive Gaussian Processes under Monotonicity Constraints. Stat. Comput. Mathis Deronzier, Andrés F. López-Lopera, François Bachoc, Olivier Roustant, Jérémy Rohmer
2025	A*	`conf`	A Parametric Contextual Online Learning Theory of Brokerage. ICML François Bachoc, Tommaso Cesari, Roberto Colomboni
2025	A	`conf`	A Tight Regret Analysis of Non-Parametric Repeated Contextual Brokerage. AISTATS François Bachoc, Tommaso Cesari, Roberto Colomboni
2025	J	`jnl`	A Tight Regret Analysis of Non-Parametric Repeated Contextual Brokerage. CoRR François Bachoc, Tommaso Cesari, Roberto Colomboni
2025	J	`jnl`	Covariance parameter estimation of Gaussian processes with approximated functional inputs. J. Multivar. Anal. Lucas Reding, Andrés F. López-Lopera, François Bachoc
2025	J	`jnl`	Error Bounds for a Kernel-Based Constrained Optimal Smoothing Approximation. SIAM/ASA J. Uncertain. Quantification Laurence Grammont, François Bachoc, Andrés F. López-Lopera
2025	J	`jnl`	Stochastic Bandits for Crowdsourcing and Multi-Platform Autobidding. CoRR François Bachoc, Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni
2025	J	`jnl`	When majority rules, minority loses: bias amplification of gradient descent. CoRR François Bachoc, Jérôme Bolte, Ryan Boustany, Jean-Michel Loubes
2024	J	`jnl`	A Contextual Online Learning Theory of Brokerage. CoRR François Bachoc, Tommaso Cesari, Roberto Colomboni
2024	J	`jnl`	A Theoretical Framework for Zeroth-Order Budget Convex Optimization. Trans. Mach. Learn. Res. François Bachoc, Tommaso Cesari, Roberto Colomboni, Andrea Paudice
2024	A*	`conf`	Fair Online Bilateral Trade. NeurIPS François Bachoc, Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni
2024	J	`jnl`	Fair Online Bilateral Trade. CoRR François Bachoc, Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni
2024	J	`jnl`	Geometry-induced Implicit Regularization in Deep ReLU Neural Networks. CoRR Joachim Bona-Pellissier, François Malgouyres, François Bachoc
2024	J	`jnl`	Variational autoencoder with weighted samples for high-dimensional non-parametric adaptive importance sampling. Trans. Mach. Learn. Res. Julien Demange-Chryst, François Bachoc, Jérôme Morio, Timothé Krauth
2024	J	`jnl`	funGp: An J. Stat. Softw. José Betancourt, François Bachoc, Thierry Klein, Déborah Idier, Jérémy Rohmer, Yves Deville
2023	J	`jnl`	Efficient estimation of multiple expectations with the same sample by adaptive importance sampling and control variates. Stat. Comput. Julien Demange-Chryst, François Bachoc, Jérôme Morio
2023	A	`conf`	Gaussian Processes on Distributions based on Regularized Optimal Transport. AISTATS François Bachoc, Louis Béthune, Alberto González-Sanz, Jean-Michel Loubes
2023	J	`jnl`	Parameter identifiability of a deep feedforward ReLU neural network. Mach. Learn. Joachim Bona-Pellissier, François Bachoc, François Malgouyres
2023	J	`jnl`	Variational autoencoder with weighted samples for high-dimensional non-parametric adaptive importance sampling. CoRR Julien Demange-Chryst, François Bachoc, Jérôme Morio, Timothé Krauth
2022	J	`jnl`	A Near-Optimal Algorithm for Univariate Zeroth-Order Budget Convex Optimization. CoRR François Bachoc, Tommaso Cesari, Roberto Colomboni, Andrea Paudice
2022	J	`jnl`	Block-Diagonal Covariance Estimation and Application to the Shapley Effects in Sensitivity Analysis. SIAM/ASA J. Uncertain. Quantification Baptiste Broto, François Bachoc, Laura Clouvel, Jean-Marc Martinez
2022	J	`jnl`	Gaussian Processes on Distributions based on Regularized Optimal Transport. CoRR François Bachoc, Louis Béthune, Alberto González-Sanz, Jean-Michel Loubes
2022	A*	`conf`	High-dimensional Additive Gaussian Processes under Monotonicity Constraints. NeurIPS Andrés F. López-Lopera, François Bachoc, Olivier Roustant
2022	J	`jnl`	High-dimensional additive Gaussian processes under monotonicity constraints. CoRR Andrés F. López-Lopera, François Bachoc, Olivier Roustant
2022	A*	`conf`	Local Identifiability of Deep ReLU Neural Networks: the Theory. NeurIPS Joachim Bona-Pellissier, François Malgouyres, François Bachoc
2022	J	`jnl`	Multioutput Gaussian processes with functional data: A study on coastal flood hazard assessment. Reliab. Eng. Syst. Saf. Andrés F. López-Lopera, Déborah Idier, Jérémy Rohmer, François Bachoc
2022	J	`jnl`	Regret Analysis of Dyadic Search. CoRR François Bachoc, Tommaso Cesari, Roberto Colomboni, Andrea Paudice
2022	J	`jnl`	Sequential Construction and Dimension Reduction of Gaussian Processes Under Inequality Constraints. SIAM J. Math. Data Sci. François Bachoc, Andrés F. López-Lopera, Olivier Roustant
2021	J	`jnl`	Bayesian regression and classification using Gaussian process priors indexed by probability density functions. Inf. Sci. Anis Fradi, Yan Feunteun, Chafik Samir, M. Baklouti, François Bachoc, Jean-Michel Loubes
2021	J	`jnl`	Gaussian Linear Approximation for the Estimation of the Shapley Effects. SIAM/ASA J. Uncertain. Quantification Baptiste Broto, François Bachoc, Marine Depecker, Jean-Marc Martinez
2021	A*	`conf`	Instance-Dependent Bounds for Zeroth-order Lipschitz Optimization with Error Certificates. NeurIPS François Bachoc, Tommaso Cesari, Sébastien Gerchinovitz
2021	J	`jnl`	Instance-Dependent Bounds for Zeroth-order Lipschitz Optimization with Error Certificates. CoRR François Bachoc, Tommaso Renato Cesari, Sébastien Gerchinovitz
2021	A	`conf`	The Sample Complexity of Level Set Approximation. AISTATS François Bachoc, Tommaso Cesari, Sébastien Gerchinovitz
2020	J	`jnl`	Gaussian process metamodeling of functional-input code for coastal flood hazard assessment. Reliab. Eng. Syst. Saf. José Betancourt, François Bachoc, Thierry Klein, Déborah Idier, Rodrigo Pedreros, Jérémy Rohmer
2020	J	`jnl`	Gaussian process optimization with failures: classification and convergence proof. J. Glob. Optim. François Bachoc, Céline Helbert, Victor Picheny
2020	J	`jnl`	Multi-Output Gaussian Processes with Functional Data: A Study on Coastal Flood Hazard Assessment. CoRR Andrés F. López-Lopera, Déborah Idier, Jérémy Rohmer, François Bachoc
2020	J	`jnl`	Variance Reduction for Estimation of Shapley Effects and Adaptation to Unknown Input Distribution. SIAM/ASA J. Uncertain. Quantification Baptiste Broto, François Bachoc, Marine Depecker
2019	J	`jnl`	Approximating Gaussian Process Emulators with Linear Inequality Constraints and Noisy Observations via MC and MCMC. CoRR Andrés F. López-Lopera, François Bachoc, Nicolas Durrande, Olivier Roustant
2019	J	`jnl`	Composite likelihood estimation for a Gaussian process under fixed domain asymptotics. J. Multivar. Anal. François Bachoc, Moreno Bevilacqua, Daira Velandia
2019	J	`jnl`	Gaussian Process-Based Dimension Reduction for Goal-Oriented Sequential Design. SIAM/ASA J. Uncertain. Quantification Malek Ben Salem, François Bachoc, Olivier Roustant, Fabrice Gamboa, Lionel Tomaso
2019	—	`conf`	Learning a Gaussian Process Model on the Riemannian Manifold of Non-decreasing Distribution Functions. PRICAI (2) Chafik Samir, Jean-Michel Loubes, Anne-Françoise Yao, François Bachoc
2019	J	`jnl`	Rate of convergence for geometric inference based on the empirical Christoffel function. CoRR Mai Trang Vu, François Bachoc, Edouard Pauwels
2019	J	`jnl`	Sensitivity indices for independent groups of variables. Math. Comput. Simul. Baptiste Broto, François Bachoc, Marine Depecker, Jean-Marc Martinez
2018	J	`jnl`	A Gaussian Process Regression Model for Distribution Inputs. IEEE Trans. Inf. Theory François Bachoc, Fabrice Gamboa, Jean-Michel Loubes, Nil Venet
2018	J	`jnl`	Entropic Variable Boosting for Explainability and Interpretability in Machine Learning. CoRR François Bachoc, Fabrice Gamboa, Jean-Michel Loubes, Laurent Risser
2018	J	`jnl`	Finite-Dimensional Gaussian Approximation with Linear Inequality Constraints. SIAM/ASA J. Uncertain. Quantification Andrés F. López-Lopera, François Bachoc, Nicolas Durrande, Olivier Roustant
2018	J	`jnl`	Nested Kriging predictions for datasets with a large number of observations. Stat. Comput. Didier Rullière, Nicolas Durrande, François Bachoc, Clément Chevalier
2017	J	`jnl`	Cross-validation estimation of covariance parameters under fixed-domain asymptotics. J. Multivar. Anal. François Bachoc, Agnès Lagnoux, Thi Mong Ngoc Nguyen
2017	J	`jnl`	Finite-dimensional Gaussian approximation with linear inequality constraints. CoRR Andrés F. López-Lopera, François Bachoc, Nicolas Durrande, Olivier Roustant
2017	J	`jnl`	Optimal configurations of lines and a statistical application. Adv. Comput. Math. François Bachoc, Martin Ehler, Manuel Gräf
2016	J	`jnl`	Asymptotic properties of multivariate tapering for estimation and prediction. J. Multivar. Anal. Reinhard Furrer, François Bachoc, Juan Du
2014	J	`jnl`	Asymptotic analysis of the role of spatial sampling for covariance parameter estimation of Gaussian processes. J. Multivar. Anal. François Bachoc
2013	J	`jnl`	Cross Validation and Maximum Likelihood estimations of hyper-parameters of Gaussian processes with model misspecification. Comput. Stat. Data Anal. François Bachoc