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Laurent Meunier
Laurent Meunier
MILES Team, LAMSADE Université Paris Dauphine
Verified email at dauphine.eu - Homepage
Title
Cited by
Cited by
Year
Theoretical evidence for adversarial robustness through randomization
R Pinot, L Meunier, A Araujo, H Kashima, F Yger, C Gouy-Pailler, J Atif
Advances in Neural Information Processing Systems 32, 2019
942019
Adversarial Attacks on Linear Contextual Bandits
E Garcelon *, B Roziere *, L Meunier *, J Tarbouriech, O Teytaud, ...
Advances in Neural Information Processing Systems 33, 2020
542020
Advocating for Multiple Defense Strategies against Adversarial Examples
A Araujo, L Meunier, R Pinot, B Negrevergne
Workshop on Machine Learning for CyberSecurity (MLCS@ECML-PKDD), 2020
42*2020
Yet another but more efficient black-box adversarial attack: tiling and evolution strategies
L Meunier, J Atif, O Teytaud
arXiv preprint arXiv:1910.02244, 2019
402019
A dynamical system perspective for lipschitz neural networks
L Meunier, BJ Delattre, A Araujo, A Allauzen
International Conference on Machine Learning, 15484-15500, 2022
342022
Black-box optimization revisited: Improving algorithm selection wizards through massive benchmarking
L Meunier, H Rakotoarison, PK Wong, B Roziere, J Rapin, O Teytaud, ...
IEEE Transactions on Evolutionary Computation 26 (3), 490-500, 2021
322021
Mixed Nash Equilibria in the Adversarial Examples Game
L Meunier, M Scetbon, R Pinot, J Atif, Y Chevaleyre
International Conference on Machine Learning 2021, 2021
302021
On the robustness of randomized classifiers to adversarial examples
R Pinot, L Meunier, F Yger, C Gouy-Pailler, Y Chevaleyre, J Atif
Machine Learning 111 (9), 3425-3457, 2022
162022
Adversarial robustness by design through analog computing and synthetic gradients
A Cappelli, R Ohana, J Launay, L Meunier, I Poli, F Krzakala
ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022
102022
Equitable and Optimal Transport with Multiple Agents
M Scetbon *, L Meunier *, J Atif, M Cuturi
International Conference on Artificial Intelligence and Statistics, 2035-2043, 2021
10*2021
Variance Reduction for Better Sampling in Continuous Domains
L Meunier, C Doerr, J Rapin, O Teytaud
International Conference on Parallel Problem Solving from Nature (PPSN), 2020
82020
An asymptotic test for conditional independence using analytic kernel embeddings
M Scetbon, L Meunier, Y Romano
International Conference on Machine Learning, 19328-19346, 2022
72022
On averaging the best samples in evolutionary computation
L Meunier, Y Chevaleyre, J Rapin, CW Royer, O Teytaud
International Conference on Parallel Problem Solving from Nature (PPSN), 2020
72020
Ropust: improving robustness through fine-tuning with photonic processors and synthetic gradients
A Cappelli, J Launay, L Meunier, R Ohana, I Poli
arXiv preprint arXiv:2108.04217, 2021
62021
Towards consistency in adversarial classification
L Meunier, R Ettedgui, R Pinot, Y Chevaleyre, J Atif
Advances in Neural Information Processing Systems 35, 8538-8549, 2022
32022
On the Role of Randomization in Adversarially Robust Classification
L Gnecco Heredia, MS Pydi, L Meunier, B Negrevergne, Y Chevaleyre
Advances in Neural Information Processing Systems 36, 2024
12024
Asymptotic convergence rates for averaging strategies
L Meunier, I Legheraba, Y Chevaleyre, O Teytaud
Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic …, 2021
12021
On the Role of Randomization in Adversarially Robust Classification
LG Heredia, Y Chevaleyre, B Negrevergne, L Meunier, MS Pydi
Thirty-seventh Conference on Neural Information Processing Systems, 2023
2023
Randomization for adversarial robustness: the Good, the Bad and the Ugly
L Gnecco-Heredia, Y Chevaleyre, B Negrevergne, L Meunier
arXiv e-prints, arXiv: 2302.07221, 2023
2023
Randomization for adversarial robustness: the Good, the Bad and the Ugly.
LG Heredia, Y Chevaleyre, B Négrevergne, L Meunier
CoRR, 2023
2023
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