Benjamin Guedj

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Pierre AlquierESSECVerified email at essec.edu
John Shawe-TaylorUCLVerified email at cs.ucl.ac.uk
Gérard BiauProfessor, Sorbonne University, ParisVerified email at sorbonne-universite.fr
Felix BiggsPhD Candidate in Foundational AI at University College LondonVerified email at ucl.ac.uk
Omar RivasplataUniversity College LondonVerified email at ualberta.ca
Maxime HaddoucheInriaVerified email at inria.fr
Pascal GermainAssistant Professor, Université LavalVerified email at ift.ulaval.ca
Bhargav Srinivasa DesikanDoctoral Researcher, EPFLVerified email at epfl.ch
Antoine VendevillePhD student, University College LondonVerified email at ucl.ac.uk
Gilles GuillotCSL Behring - Global Research Data Science GroupVerified email at cslbehring.com
Zakaria MhammediMassachusetts Institute of TechnologyVerified email at mit.edu
Arthur GrettonGatsby Computational Neuroscience Unit, UCLVerified email at gatsby.ucl.ac.uk
Antonin SchrabPhD student, University College LondonVerified email at ucl.ac.uk
Maria Perez-OrtizUniversity College LondonVerified email at ucl.ac.uk
Shi ZHOUDepartment of Computer Science, University College London (UCL), UKVerified email at ucl.ac.uk
Mark HarmanResearch Scientist at Facebook & 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
Gaël LetartePhD Student, Laval UniversityVerified email at ulaval.ca
Pierre AlliezSenior Researcher, Team Leader and Head of Science, Inria Sophia Antipolis - MéditerranéeVerified email at inria.fr

Benjamin Guedj

Inria & University College London

Verified email at inria.fr - Homepage

Machine learning Deep learning Statistical learning theory Computational statistics Artificial intelligence


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	142	2019
COBRA: A combined regression strategy G Biau, A Fischer, B Guedj, JD Malley Journal of Multivariate Analysis 146, 18-28, 2016	60*	2016
Simpler PAC-Bayesian bounds for hostile data P Alquier, B Guedj Machine Learning 107 (5), 887-902, 2018	52	2018
PAC-Bayesian Estimation and Prediction in Sparse Additive Models B Guedj, P Alquier Electronic Journal of Statistics 7, 264-291, 2013	52	2013
Estimating the location and shape of hybrid zones B Guedj, G Guillot Molecular Ecology Resources 11 (6), 1119-1123, 2011	41	2011
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	34	2019
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	31	2019
PAC-Bayes un-expected Bernstein inequality Z Mhammedi, P Grünwald, B Guedj Advances in Neural Information Processing Systems 32, 2019	22	2019
PAC-Bayes unleashed: Generalisation bounds with unbounded losses M Haddouche, B Guedj, O Rivasplata, J Shawe-Taylor Entropy 23 (10), 1330, 2021	21	2021
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	18	2020
A quasi-Bayesian perspective to online clustering L Li, B Guedj, S Loustau	17*	2018
An oracle inequality for quasi-Bayesian nonnegative matrix factorization P Alquier, B Guedj Mathematical Methods of Statistics 26, 55-67, 2017	17	2017
Model Validation Using Mutated Training Labels: An Exploratory Study JM Zhang, M Harman, B Guedj, ET Barr, J Shawe-Taylor arXiv preprint arXiv:1905.10201, 2019	16*	2019
Online k-means clustering V Cohen-Addad, B Guedj, V Kanade, G Rom International Conference on Artificial Intelligence and Statistics, 1126-1134, 2021	15	2021
Stability revisited: new generalisation bounds for the leave-one-out A Celisse, B Guedj arXiv preprint arXiv:1608.06412, 2016	15	2016
Differentiable pac–bayes objectives with partially aggregated neural networks F Biggs, B Guedj Entropy 23 (10), 1280, 2021	14	2021
Pycobra: A python toolbox for ensemble learning and visualisation B Guedj, BS Desikan Journal of Machine Learning Research 18 (190), 1-5, 2018	14	2018
Still no free lunches: the price to pay for tighter PAC-Bayes bounds B Guedj, L Pujol Entropy 23 (11), 1529, 2021	13	2021
On margins and derandomisation in PAC-Bayes F Biggs, B Guedj International Conference on Artificial Intelligence and Statistics, 3709-3731, 2022	12	2022
PAC-Bayesian contrastive unsupervised representation learning K Nozawa, P Germain, B Guedj Conference on Uncertainty in Artificial Intelligence, 21-30, 2020	11	2020

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