Nicolas Flammarion

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Maksym AndriushchenkoPhD student at EPFLAdresse e-mail validée de epfl.ch
Francis BachInria - Ecole Normale SupérieureAdresse e-mail validée de inria.fr
Peter BartlettProfessor, EECS and Statistics, UC BerkeleyAdresse e-mail validée de cs.berkeley.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyAdresse e-mail validée de cs.berkeley.edu
Matthias HeinProfessor of Computer Science, University of TübingenAdresse e-mail validée de uni-tuebingen.de
Francesco CroceUniversity of TübingenAdresse e-mail validée de cs.uni-saarland.de
Yi-An MaUC San DiegoAdresse e-mail validée de ucsd.edu
Loucas Pillaud-VivienEcole Polytechnique de Lausanne, EPFLAdresse e-mail validée de epfl.ch
Niladri S. ChatterjiPostdoctoral Researcher, Department of Computer Science, Stanford UniversityAdresse e-mail validée de cs.stanford.edu
Aymeric DieuleveutAssistant Professor, Ecole Polytechnique, FranceAdresse e-mail validée de polytechnique.edu
Nilesh TripuraneniUC BerkeleyAdresse e-mail validée de berkeley.edu
Scott PesmePhD student, EPFLAdresse e-mail validée de epfl.ch
Wenlong MouUC BerkeleyAdresse e-mail validée de eecs.berkeley.edu
Martin WainwrightProfessor of EECS and Statistics, UC BerkeleyAdresse e-mail validée de berkeley.edu
Yeshwanth CherapanamjeriPh.D Student, UC BerkeleyAdresse e-mail validée de berkeley.edu
Yuansi ChenDepartment of Statistical Science, Duke UniversityAdresse e-mail validée de duke.edu
Chi JinAssistant Professor, Princeton UniversityAdresse e-mail validée de princeton.edu
Xiang ChengUC BerkeleyAdresse e-mail validée de berkeley.edu
Aditya VarrePhD student, EPFLAdresse e-mail validée de epfl.ch
Philippe RigolletMassachusetts Institute of TechnologyAdresse e-mail validée de math.mit.edu

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Nicolas Flammarion

EPFL

Adresse e-mail validée de epfl.ch - Page d'accueil

Machine Learning Optimization Statistics


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Square attack: a query-efficient black-box adversarial attack via random search M Andriushchenko, F Croce, N Flammarion, M Hein ECCV, 2020	432	2020
Robustbench: a standardized adversarial robustness benchmark F Croce, M Andriushchenko, V Sehwag, E Debenedetti, N Flammarion, ... arXiv preprint arXiv:2010.09670, 2020	237	2020
Understanding and Improving Fast Adversarial Training M Andriushchenko, N Flammarion Advances in Neural Information Processing Systems, 2020	141	2020
From averaging to acceleration, there is only a step-size N Flammarion, F Bach Conference on Learning Theory, 658-695, 2015	139	2015
Sampling can be faster than optimization YA Ma, Y Chen, C Jin, N Flammarion, MI Jordan Proceedings of the National Academy of Sciences 116 (42), 20881-20885, 2019	129	2019
Harder, better, faster, stronger convergence rates for least-squares regression A Dieuleveut, N Flammarion, F Bach The Journal of Machine Learning Research 18 (1), 3520-3570, 2017	129	2017
Is there an analog of Nesterov acceleration for gradient-based MCMC? YA Ma, NS Chatterji, X Cheng, N Flammarion, PL Bartlett, MI Jordan	103	2021
On the theory of variance reduction for stochastic gradient Monte Carlo NS Chatterji, N Flammarion, YA Ma, PL Bartlett, MI Jordan International Conference on Machine Learning, 764--773, 2018	86	2018
Averaging stochastic gradient descent on Riemannian manifolds N Tripuraneni, N Flammarion, F Bach, MI Jordan Conference On Learning Theory, 2018	86	2018
Optimal rates of statistical seriation N Flammarion, C Mao, P Rigollet	62	2019
Fast mean estimation with sub-Gaussian rates Y Cherapanamjeri, N Flammarion, PL Bartlett Conference on Learning Theory, 786--806, 2019	56	2019
Escaping from saddle points on Riemannian manifolds Y Sun, N Flammarion, M Fazel Advances in Neural Information Processing Systems, 7276-7286, 2019	53	2019
On the effectiveness of adversarial training against common corruptions K Kireev, M Andriushchenko, N Flammarion Uncertainty in Artificial Intelligence, 1012-1021, 2022	39	2022
Improved bounds for discretization of Langevin diffusions: Near-optimal rates without convexity W Mou, N Flammarion, MJ Wainwright, PL Bartlett Bernoulli 28 (3), 1577-1601, 2022	34	2022
Sparse-rs: a versatile framework for query-efficient sparse black-box adversarial attacks F Croce, M Andriushchenko, ND Singh, N Flammarion, M Hein Proceedings of the AAAI Conference on Artificial Intelligence 36 (6), 6437-6445, 2022	34	2022
Implicit bias of sgd for diagonal linear networks: a provable benefit of stochasticity S Pesme, L Pillaud-Vivien, N Flammarion Advances in Neural Information Processing Systems 34, 29218-29230, 2021	29	2021
Optimal robust linear regression in nearly linear time Y Cherapanamjeri, E Aras, N Tripuraneni, MI Jordan, N Flammarion, ... arXiv preprint arXiv:2007.08137, 2020	27	2020
Stochastic Composite Least-Squares Regression with convergence rate O (1/n) N Flammarion, F Bach Conference on Learning Theory, 831--875, 2017	26	2017
Robust discriminative clustering with sparse regularizers N Flammarion, B Palaniappan, F Bach The Journal of Machine Learning Research 18 (1), 2764-2813, 2017	21	2017
Online Robust Regression via SGD on the l1 loss S Pesme, N Flammarion Advances in Neural Information Processing Systems, 2020	18	2020

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