Benjamin Guedj

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Maxime HaddoucheInriaVerified email at inria.fr
John Shawe-TaylorUCLVerified email at cs.ucl.ac.uk
Pierre AlquierESSEC Business SchoolVerified email at essec.edu
Felix BiggsPhD Candidate in Foundational AI at University College LondonVerified email at ucl.ac.uk
Gérard BiauProfessor, Sorbonne University, ParisVerified email at sorbonne-universite.fr
Arthur GrettonGatsby Computational Neuroscience Unit and Google DeepmindVerified email at gatsby.ucl.ac.uk
Pascal GermainAssistant Professor, Université LavalVerified email at ift.ulaval.ca
Antoine VendevilleUniversity College LondonVerified email at ucl.ac.uk
Antonin SchrabPhD student, University College LondonVerified email at ucl.ac.uk
Zakaria MhammediMassachusetts Institute of TechnologyVerified email at mit.edu
Maria Perez-OrtizAssociate Professor, University College LondonVerified email at ucl.ac.uk
Shi ZHOUDepartment of Computer Science, University College London (UCL), UKVerified email at ucl.ac.uk
Gilles GuillotCSL Behring & Swiss Institute for Translational and Entrepreneurial MedicineVerified email at cslbehring.com
Mélisande AlbertINSA de ToulouseVerified email at insa-toulouse.fr
Béatrice Laurent,INSA de Toulouse, Institut de Mathématiques de Toulouse et ANITIVerified email at insa-toulouse.fr
Mark HarmanResearch Scientist at Meta & Professor of Software Engineering at UCLVerified email at ucl.ac.uk
Earl T. BarrProfessor, University College LondonVerified email at ucl.ac.uk
Jie M. ZhangLecturer (Assistant Professor), King's College LondonVerified email at kcl.ac.uk
Bhargav Srinivasa DesikanSenior Research Fellow, IPPRVerified email at ippr.org
Gaël LetartePhD Student, Laval UniversityVerified email at ulaval.ca

Benjamin Guedj

Inria and University College London (UCL)

Verified email at inria.fr - Homepage

Machine learning Deep learning Statistical learning theory Computational statistics AI


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
A Primer on PAC-Bayesian Learning B Guedj, J Shawe-Taylor ICML 2019, 2019	200	2019
Simpler PAC-Bayesian bounds for hostile data P Alquier, B Guedj Machine Learning 107 (5), 887-902, 2018	69	2018
COBRA: A combined regression strategy G Biau, A Fischer, B Guedj, JD Malley Journal of Multivariate Analysis 146, 18-28, 2016	63*	2016
PAC-Bayesian Estimation and Prediction in Sparse Additive Models B Guedj, P Alquier Electronic Journal of Statistics 7, 264-291, 2013	58	2013
Dichotomize and generalize: PAC-Bayesian binary activated deep neural networks G Letarte, P Germain, B Guedj, F Laviolette Advances in Neural Information Processing Systems 32, 2019	54	2019
PAC-Bayes un-expected Bernstein inequality Z Mhammedi, P Grünwald, B Guedj Advances in Neural Information Processing Systems 32, 2019	42	2019
Estimating the location and shape of hybrid zones B Guedj, G Guillot Molecular Ecology Resources 11 (6), 1119-1123, 2011	42	2011
Attributing and referencing (research) software: Best practices and outlook from Inria P Alliez, R Di Cosmo, B Guedj, A Girault, MS Hacid, A Legrand, N Rougier Computing in Science & Engineering 22 (1), 39-52, 2019	39	2019
PAC-Bayes unleashed: Generalisation bounds with unbounded losses M Haddouche, B Guedj, O Rivasplata, J Shawe-Taylor Entropy 23 (10), 1330, 2021	38	2021
Online k-means clustering V Cohen-Addad, B Guedj, V Kanade, G Rom International Conference on Artificial Intelligence and Statistics, 1126-1134, 2021	30	2021
Differentiable pac–bayes objectives with partially aggregated neural networks F Biggs, B Guedj Entropy 23 (10), 1280, 2021	28	2021
MMD aggregated two-sample test A Schrab, I Kim, M Albert, B Laurent, B Guedj, A Gretton Journal of Machine Learning Research (JMLR) 24, 2023	22	2023
Pac-bayesian bound for the conditional value at risk Z Mhammedi, B Guedj, RC Williamson Advances in Neural Information Processing Systems 33, 17919-17930, 2020	22	2020
Model validation using mutated training labels: An exploratory study JM Zhang, M Harman, B Guedj, ET Barr, J Shawe-Taylor Neurocomputing 539, 126116, 2023	21*	2023
On margins and derandomisation in PAC-Bayes F Biggs, B Guedj International Conference on Artificial Intelligence and Statistics, 3709-3731, 2022	21	2022
A quasi-Bayesian perspective to online clustering L Li, B Guedj, S Loustau	21*	2018
Learning PAC-Bayes priors for probabilistic neural networks M Perez-Ortiz, O Rivasplata, B Guedj, M Gleeson, J Zhang, ... arXiv preprint arXiv:2109.10304, 2021	20	2021
PAC-Bayesian contrastive unsupervised representation learning K Nozawa, P Germain, B Guedj Conference on Uncertainty in Artificial Intelligence, 21-30, 2020	20	2020
Stability revisited: new generalisation bounds for the leave-one-out A Celisse, B Guedj arXiv preprint arXiv:1608.06412, 2016	20	2016
An oracle inequality for quasi-Bayesian nonnegative matrix factorization P Alquier, B Guedj Mathematical Methods of Statistics 26, 55-67, 2017	19	2017

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