Nicolas Flammarion

Cited by

	All	Since 2018
Citations	2385	2315
h-index	21	21
i10-index	27	27

940

470

235

705

2016201720182019202020212022202321 35 65 117 233 534 925 417

Public access

View all

11 articles

0 articles

available

not available

Based on funding mandates

Co-authors

Maksym AndriushchenkoPhD student at EPFLVerified email at epfl.ch
Francis BachInria - Ecole Normale SupérieureVerified email at inria.fr
Peter BartlettProfessor, EECS and Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Matthias HeinProfessor of Computer Science, University of TübingenVerified email at uni-tuebingen.de
Francesco CroceUniversity of TübingenVerified email at cs.uni-saarland.de
Yi-An MaUC San DiegoVerified email at ucsd.edu
Loucas Pillaud-VivienCourant Institute of Mathematics, NYU / Flatiron Institute, New YorkVerified email at flatironinstitute.org
Scott PesmePhD at EPFLVerified email at epfl.ch
Niladri S. ChatterjiPostdoctoral Researcher, Department of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
Aymeric DieuleveutAssistant Professor, Ecole Polytechnique, FranceVerified email at polytechnique.edu
Wenlong MouUC BerkeleyVerified email at eecs.berkeley.edu
Yeshwanth CherapanamjeriPh.D Student, UC BerkeleyVerified email at berkeley.edu
Yuansi ChenDepartment of Statistical Science, Duke UniversityVerified email at duke.edu
Chi JinAssistant Professor, Princeton UniversityVerified email at princeton.edu
Etienne BoursierINRIA SaclayVerified email at inria.fr
Xiang ChengUC BerkeleyVerified email at berkeley.edu
Aditya VarrePhD student, EPFLVerified email at epfl.ch
Adrien TaylorInria - ENS ParisVerified email at inria.fr
Mathieu EvenEcole Normale Supérieure, InriaVerified email at ens.fr

Nicolas Flammarion

EPFL

Verified email at epfl.ch - Homepage

Machine Learning Optimization Statistics


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Square attack: a query-efficient black-box adversarial attack via random search M Andriushchenko, F Croce, N Flammarion, M Hein ECCV, 2020	565	2020
Robustbench: a standardized adversarial robustness benchmark F Croce, M Andriushchenko, V Sehwag, E Debenedetti, N Flammarion, ... arXiv preprint arXiv:2010.09670, 2020	300	2020
Understanding and Improving Fast Adversarial Training M Andriushchenko, N Flammarion Advances in Neural Information Processing Systems, 2020	182	2020
From averaging to acceleration, there is only a step-size N Flammarion, F Bach Conference on Learning Theory, 658-695, 2015	141	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	138	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	138	2017
Is there an analog of Nesterov acceleration for gradient-based MCMC? YA Ma, NS Chatterji, X Cheng, N Flammarion, PL Bartlett, MI Jordan	111	2021
Averaging stochastic gradient descent on Riemannian manifolds N Tripuraneni, N Flammarion, F Bach, MI Jordan Conference On Learning Theory, 2018	94	2018
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	90	2018
Optimal rates of statistical seriation N Flammarion, C Mao, P Rigollet	66	2019
Fast mean estimation with sub-Gaussian rates Y Cherapanamjeri, N Flammarion, PL Bartlett Conference on Learning Theory, 786--806, 2019	63	2019
Escaping from saddle points on Riemannian manifolds Y Sun, N Flammarion, M Fazel Advances in Neural Information Processing Systems, 7276-7286, 2019	57	2019
On the effectiveness of adversarial training against common corruptions K Kireev, M Andriushchenko, N Flammarion Uncertainty in Artificial Intelligence, 1012-1021, 2022	46	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	44	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	41	2021
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	38	2022
Towards understanding sharpness-aware minimization M Andriushchenko, N Flammarion International Conference on Machine Learning, 639-668, 2022	37	2022
Optimal robust linear regression in nearly linear time Y Cherapanamjeri, E Aras, N Tripuraneni, MI Jordan, N Flammarion, ... arXiv preprint arXiv:2007.08137, 2020	33	2020
Stochastic Composite Least-Squares Regression with convergence rate O (1/n) N Flammarion, F Bach Conference on Learning Theory, 831--875, 2017	28	2017
Online Robust Regression via SGD on the l1 loss S Pesme, N Flammarion Advances in Neural Information Processing Systems, 2020	22	2020

The system can't perform the operation now. Try again later.

Articles 1–20

Citations per year

Duplicate citations

Merged citations

Add co-authorsCo-authors

Follow

Cited by

Co-authors