Pinot Rafael
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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
Robust Neural Networks using Randomized Adversarial Training
A Araujo, L Meunier, R Pinot, B Negrevergne
arXiv preprint arXiv:1903.10219, 2019
Graph-based Clustering under Differential Privacy
R Pinot, A Morvan, F Yger, C Gouy-Pailler, J Atif
Conference on Uncertainty in Artificial Intelligence (UAI), 2018
Randomization matters. how to defend against strong adversarial attacks
R Pinot, R Ettedgui, G Rizk, Y Chevaleyre, J Atif
International Conference on Machine Learning (ICML), 2020
Minimum spanning tree release under differential privacy constraints
R Pinot
Sorbonne University, 2018
A unified view on differential privacy and robustness to adversarial examples
R Pinot, F Yger, C Gouy-Pailler, J Atif
Workshop on Machine Learning for CyberSecurity (MLCS@ECML-PKDD), 2019
Advocating for Multiple Defense Strategies against Adversarial Examples
A Araujo, L Meunier, R Pinot, B Negrevergne
arXiv preprint arXiv:2012.02632, 2020
SPEED: Secure, PrivatE, and Efficient Deep learning
A Grivet Sébert, R Pinot, M Zuber, C Gouy-Pailler, R Sirdey
arXiv e-prints, arXiv: 2006.09475, 2020
On the robustness of randomized classifiers to adversarial examples
R Pinot, L Meunier, F Yger, C Gouy-Pailler, Y Chevaleyre, J Atif
arXiv preprint arXiv:2102.10875, 2021
Differential Privacy and Byzantine Resilience in SGD: Do They Add Up?
R Guerraoui, N Gupta, R Pinot, S Rouault, J Stephan
arXiv preprint arXiv:2102.08166, 2021
Mixed Nash Equilibria in the Adversarial Examples Game
L Meunier, M Scetbon, R Pinot, J Atif, Y Chevaleyre
arXiv preprint arXiv:2102.06905, 2021
Initiative face au virus. Regards croisés sur l'épidemie de Covid-19 apportés par les données sanitaires et de géolocalisation (mars à octobre 2020)
J Atif, B Cabot, O Cappé, O Mula, R Pinot
Université PSL; Inria; CNRS, 2020
On the impact of randomization on robustness in machine learning
R Pinot
Université Paris-Dauphine, PSL, 2020
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