Pierre Alquier

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	All	Since 2015
Citations	1040	814
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Co-authors

Nicolas ChopinProfessor of Statistics, ENSAE (Institut Polytechnique de Paris)Verified email at ensae.fr
James RidgwayCapital Fund ManagementVerified email at cfm.fr
Benjamin GuedjInria & University College LondonVerified email at inria.fr
Badr-Eddine Chérief-AbdellatifUniversity of Oxford, Department of StatisticsVerified email at stats.ox.ac.uk
Olivier WintenbergerLPSM, Sorbonne UniversityVerified email at upmc.fr
Nial FrielProfessor of Statistics, University College Dublin, COSTNET CA15109Verified email at ucd.ie
Mohamed HebiriUniversité Paris-Est -- Marne-la-ValléeVerified email at u-pem.fr
Vincent CottetENSAEVerified email at ensae.fr
Gérard BiauProfessor, Sorbonne University, ParisVerified email at upmc.fr
Richard G. EverittUniversity of WarwickVerified email at warwick.ac.uk
Xiaoyin LiAssistant Professor of Statistics, St.Cloud State UniversityVerified email at stcloudstate.edu
Paul DoukhanProfessor of mathematics, University Cergy-PontoiseVerified email at u-cergy.fr
Guillaume LecuéProfessor - ENSAE - CRESTVerified email at ensae.fr
Karim LouniciStatistics Professor, Georgia Institute of TechnologyVerified email at math.gatech.edu
Feng LiangDepartment of StatisticsVerified email at illinois.edu
Léna Careldoctorante, CREST, ENSAE, Université Paris-SaclayVerified email at ensae.fr
Katia MezianiMaitre de conférence, université Paris dauphineVerified email at ceremade.dauphine.fr
Massimiliano PontilIstituto Italiano di Tecnologia & University College LondonVerified email at iit.it
Eric GautierToulouse School of EconomicsVerified email at tse-fr.eu
Tomoyuki MorimaeYukawa Institute for Theoretical Physics, Kyoto UniversityVerified email at yukawa.kyoto-u.ac.jp

Pierre Alquier

Center for Advanced Intelligence Project (AIP), RIKEN, Tokyo

Verified email at postman.riken.jp - Homepage

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


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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	123	2016
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	90	2016
PAC-Bayesian bounds for sparse regression estimation with exponential weights P Alquier, K Lounici Electronic Journal of Statistics 5, 127-145, 2011	70	2011
Sparse single-index model P Alquier, G Biau Journal of Machine Learning Research 14 (Jan), 243-280, 2013	69	2013
Model selection for weakly dependent time series forecasting P Alquier, O Wintenberger Bernoulli 18 (3), 883-913, 2012	60	2012
PAC-Bayesian bounds for randomized empirical risk minimizers P Alquier Mathematical Methods of Statistics 17 (4), 279-304, 2008	53	2008
PAC-Bayesian Estimation and Prediction in Sparse Additive Models B Guedj, P Alquier Electronic Journal of Statistics 7, 264-291, 2013	46	2013
Concentration of tempered posteriors and of their variational approximations P Alquier, J Ridgway The Annals of Statistics 48 (3), 1475-1497, 2020	39	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	34	2018
Regret bounds for lifelong learning P Alquier, TT Mai, M Pontil Proceedings of Machine Learning Research 54, 261-269, 2017	33	2017
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	32	2019
Prediction of time series by statistical learning: general losses and fast rates P Alquier, X Li, O Wintenberger Dependence Modeling 1, 65-93, 2013	28	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	26	2015
Simpler PAC-Bayesian bounds for hostile data P Alquier, B Guedj Machine Learning 107 (5), 887–902, 2018	23	2018
Bayesian methods for low-rank matrix estimation: short survey and theoretical study P Alquier Algorithmic Learning Theory, 309-323, 2013	22	2013
Lasso, iterative feature selection and the correlation selector: Oracle inequalities and numerical performances P Alquier Electronic journal of statistics 2, 1129-1152, 2008	22	2008
Rank penalized estimation of a quantum system P Alquier, C Butucea, M Hebiri, K Meziani, T Morimae Physical Review A 88 (3), 2013	20	2013
Prediction of quantiles by statistical learning and application to GDP forecasting P Alquier, X Li 15th International Conference on Discovery Science 2012, 23-36, 2012	20	2012
Inverse problems and high-dimensional estimation: stats in the Château Summer School, August 31-September 4, 2009 P Alquier, E Gautier, G Stoltz Springer Science & Business Media, 2011	20	2011
1-Bit matrix completion: PAC-Bayesian analysis of a variational approximation V Cottet, P Alquier Machine Learning 107 (3), 579-603, 2018	18	2018

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