Nicolas Flammarion

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Maksym AndriushchenkoPostdoctoral Researcher at EPFLEmail confirmado em epfl.ch
Francesco CroceEPFLEmail confirmado em cs.uni-saarland.de
Matthias HeinProfessor of Computer Science, University of TübingenEmail confirmado em uni-tuebingen.de
Francis BachInria - Ecole Normale SupérieureEmail confirmado em inria.fr
Peter BartlettProfessor, EECS and Statistics, UC BerkeleyEmail confirmado em cs.berkeley.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyEmail confirmado em cs.berkeley.edu
Scott PesmePost-Doc at Inria GrenobleEmail confirmado em inria.fr
Loucas Pillaud-VivienEcole Nationale Des PontsEmail confirmado em enpc.fr
Aditya VarrePhD student, EPFLEmail confirmado em epfl.ch
Etienne BoursierINRIA SaclayEmail confirmado em inria.fr
Yi-An MaUC San DiegoEmail confirmado em ucsd.edu
Mathieu EvenEcole Normale Supérieure, InriaEmail confirmado em ens.fr
Niladri S. ChatterjiPostdoctoral Researcher, Department of Computer Science, Stanford UniversityEmail confirmado em cs.stanford.edu
Aymeric DieuleveutProfessor, Ecole Polytechnique, FranceEmail confirmado em polytechnique.edu
Yeshwanth CherapanamjeriPostdoctoral Associate, MITEmail confirmado em berkeley.edu
Yuansi ChenSeminar for Statistics, D-MATH, ETH ZurichEmail confirmado em stat.math.ethz.ch
Chi JinAssistant Professor, Princeton UniversityEmail confirmado em princeton.edu
Adrien TaylorInria - ENS ParisEmail confirmado em inria.fr
Xiang ChengMassachusetts Institute of TechnologyEmail confirmado em berkeley.edu
Maryam FazelMoorthy Family Professor of Electrical and Computer Engineering, University of WashingtonEmail confirmado em uw.edu

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Nicolas Flammarion

EPFL

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Machine Learning Optimization Statistics


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
Square attack: a query-efficient black-box adversarial attack via random search M Andriushchenko, F Croce, N Flammarion, M Hein ECCV, 2020	1150	2020
Robustbench: a standardized adversarial robustness benchmark F Croce, M Andriushchenko, V Sehwag, E Debenedetti, N Flammarion, ... arXiv preprint arXiv:2010.09670, 2020	784	2020
Understanding and Improving Fast Adversarial Training M Andriushchenko, N Flammarion Advances in Neural Information Processing Systems, 2020	361	2020
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	237	2019
Harder, better, faster, stronger convergence rates for least-squares regression A Dieuleveut, N Flammarion, F Bach Journal of Machine Learning Research 18 (101), 1-51, 2017	181	2017
Is there an analog of Nesterov acceleration for gradient-based MCMC? YA Ma, NS Chatterji, X Cheng, N Flammarion, PL Bartlett, MI Jordan	178	2021
Towards understanding sharpness-aware minimization M Andriushchenko, N Flammarion International Conference on Machine Learning, 639-668, 2022	162	2022
From averaging to acceleration, there is only a step-size N Flammarion, F Bach Conference on learning theory, 658-695, 2015	157	2015
Averaging stochastic gradient descent on Riemannian manifolds N Tripuraneni, N Flammarion, F Bach, MI Jordan Conference On Learning Theory, 2018	123	2018
On the effectiveness of adversarial training against common corruptions K Kireev, M Andriushchenko, N Flammarion Uncertainty in Artificial Intelligence, 1012-1021, 2022	120	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	118	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	118	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	108	2018
Jailbreaking leading safety-aligned llms with simple adaptive attacks M Andriushchenko, F Croce, N Flammarion arXiv preprint arXiv:2404.02151, 2024	101	2024
Jailbreakbench: An open robustness benchmark for jailbreaking large language models P Chao, E Debenedetti, A Robey, M Andriushchenko, F Croce, V Sehwag, ... arXiv preprint arXiv:2404.01318, 2024	97	2024
Fast mean estimation with sub-Gaussian rates Y Cherapanamjeri, N Flammarion, PL Bartlett Conference on Learning Theory, 786--806, 2019	94	2019
Escaping from saddle points on Riemannian manifolds Y Sun, N Flammarion, M Fazel Advances in Neural Information Processing Systems, 7276-7286, 2019	85	2019
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	81	2022
Optimal rates of statistical seriation N Flammarion, C Mao, P Rigollet	75	2019
Gradient flow dynamics of shallow relu networks for square loss and orthogonal inputs E Boursier, L Pillaud-Vivien, N Flammarion Advances in Neural Information Processing Systems 35, 20105-20118, 2022	67	2022

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