Pierre Alquier

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Nicolas ChopinProfessor of Statistics, ENSAE (Institut Polytechnique de Paris)Verified email at ensae.fr
Badr-Eddine Chérief-AbdellatifCNRS, Sorbonne Université, Université Paris CitéVerified email at sorbonne-universite.fr
James RidgwayCapital Fund ManagementVerified email at cfm.fr
Benjamin GuedjInria and University College London (UCL)Verified email at inria.fr
Olivier WintenbergerLPSM, Sorbonne UniversityVerified email at upmc.fr
Mohamed HebiriUniversité Paris-Est -- Marne-la-ValléeVerified email at u-pem.fr
Vincent CottetENSAEVerified email at ensae.fr
Nial FrielProfessor of Statistics, University College Dublin, COSTNET CA15109Verified email at ucd.ie
The Tien MaiNTNUVerified email at ntnu.no
Paul DoukhanProfessor of mathematics, CYU Cergy UniversityVerified email at cyu.fr
Gérard BiauProfessor, Sorbonne University, ParisVerified email at sorbonne-universite.fr
Richard G. EverittUniversity of WarwickVerified email at warwick.ac.uk
Guillaume LECUEESSECVerified email at essec.edu
Xiaoyin LiSenior bioinformatics scientistVerified email at astrazeneca.com
Katia MezianiMaitre de conférence, université Paris dauphineVerified email at ceremade.dauphine.fr
Léna Careldoctorante, CREST, ENSAE, Université Paris-SaclayVerified email at ensae.fr
Karim LouniciStatistics Professor, Ecole PolytechniqueVerified email at polytechnique.edu
Mehdi BennaniGoogle DeepMindVerified email at deepmind.com
Thang DoanSnorkel AIVerified email at mail.mcgill.ca
Guillaume RabusseauAssistant Professor - Canada CIFAR AI Chair, Université de Montréal / MilaVerified email at iro.umontreal.ca

Pierre Alquier

ESSEC Business School

Verified email at essec.edu - Homepage

Statistical learning theory aggregation of estimators approximate posterior inference mathematical statistics PAC-Bayes


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
On the properties of variational approximations of Gibbs posteriors P Alquier, J Ridgway, N Chopin Journal of Machine Learning Research 17 (239), 1-41, 2016	281	2016
User-friendly introduction to PAC-Bayes bounds P Alquier Foundations and Trends® in Machine Learning 17 (2), 174-303, 2024	218*	2024
Noisy Monte Carlo: Convergence of Markov chains with approximate transition kernels P Alquier, N Friel, R Everitt, A Boland Statistics and Computing 26 (1), 29-47, 2016	171	2016
Concentration of tempered posteriors and of their variational approximations P Alquier, J Ridgway The Annals of Statistics 48 (3), 1475-1497, 2020	150	2020
Sparse single-index model P Alquier, G Biau Journal of Machine Learning Research 14 (Jan), 243-280, 2013	115	2013
PAC-Bayesian bounds for sparse regression estimation with exponential weights P Alquier, K Lounici Electronic Journal of Statistics 5, 127-145, 2011	88	2011
Model selection for weakly dependent time series forecasting P Alquier, O Wintenberger Bernoulli 18 (3), 883-913, 2012	87	2012
Simpler PAC-Bayesian bounds for hostile data P Alquier, B Guedj Machine Learning 107 (5), 887–902, 2018	85	2018
A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix T Doan, M Bennani, B Mazoure, G Rabusseau, P Alquier 24th International Conference on Artificial Intelligence and Statistics …, 2021	81	2021
Regret bounds for lifelong learning P Alquier, TT Mai, M Pontil 20th International Conference on Artificial Intelligence and Statistics, 261-269, 2017	81	2017
PAC-Bayesian bounds for randomized empirical risk minimizers P Alquier Mathematical Methods of Statistics 17, 279-304, 2008	76	2008
Estimation bounds and sharp oracle inequalities of regularized procedures with Lipschitz loss functions P Alquier, V Cottet, G Lecué The Annals of Statistics 47 (4), 2117-2144, 2019	75	2019
MMD-Bayes: Robust Bayesian Estimation via Maximum Mean Discrepancy BE Chérief-Abdellatif, P Alquier 2nd Symposium on Advances in Approximate Bayesian Inference, 1-21, 2020	73	2020
Consistency of Variational Bayes Inference for Estimation and Model Selection in Mixtures BE Chérief-Abdellatif, P Alquier Electronic Journal of Statistics 12 (2), 2995-3035, 2018	65	2018
PAC-Bayesian Estimation and Prediction in Sparse Additive Models B Guedj, P Alquier Electronic Journal of Statistics 7, 264-291, 2013	65	2013
A Bayesian Approach for Noisy Matrix Completion: Optimal Rate under General Sampling Distribution TT Mai, P Alquier Electronic Journal of Statistics 9, 823-841, 2015	59	2015
Prediction of time series by statistical learning: general losses and fast rates P Alquier, X Li, O Wintenberger Dependence Modeling 1, 65-93, 2013	51	2013
Finite sample properties of parametric MMD estimation: robustness to misspecification and dependence BE Chérief-Abdellatif, P Alquier Bernoulli 28 (1), 181-213, 2022	44	2022
1-Bit matrix completion: PAC-Bayesian analysis of a variational approximation V Cottet, P Alquier Machine Learning 107 (3), 579-603, 2018	39	2018
Bayesian methods for low-rank matrix estimation: short survey and theoretical study P Alquier 24th International Conference on Algorithmic Learning Theory, 309-323, 2013	36	2013

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