| 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 | 104 | 2019 |
| Adversarial Attacks on Linear Contextual Bandits E Garcelon *, B Roziere *, L Meunier *, J Tarbouriech, O Teytaud, ... Advances in Neural Information Processing Systems 33, 2020 | 61 | 2020 |
| 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 | 48* | 2020 |
| 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 | 43 | 2021 |
| 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 | 42 | 2019 |
| A dynamical system perspective for lipschitz neural networks L Meunier, BJ Delattre, A Araujo, A Allauzen International Conference on Machine Learning, 15484-15500, 2022 | 41 | 2022 |
| 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 | 34 | 2021 |
| 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 | 20 | 2022 |
| 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 | 12 | 2022 |
| 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 | 9 | 2020 |
| 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 | 7 | 2022 |
| 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 | 7 | 2020 |
| 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 | 6 | 2021 |
| An asymptotic test for conditional independence using analytic kernel embeddings M Scetbon, L Meunier, Y Romano International Conference on Machine Learning, 19328-19346, 2022 | 5 | 2022 |
| 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, 79293-79319, 2023 | 1 | 2023 |
| 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 | 1 | 2023 |
| 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 | 1 | 2021 |
| 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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