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Pinot Rafael
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Année
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
1012019
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
632020
Byzantine machine learning made easy by resilient averaging of momentums
S Farhadkhani, R Guerraoui, N Gupta, R Pinot, J Stephan
International Conference on Machine Learning, 6246-6283, 2022
492022
Advocating for multiple defense strategies against adversarial examples
A Araujo, L Meunier, R Pinot, B Negrevergne
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2020
45*2020
Fixing by mixing: A recipe for optimal byzantine ml under heterogeneity
Y Allouah, S Farhadkhani, R Guerraoui, N Gupta, R Pinot, J Stephan
International Conference on Artificial Intelligence and Statistics, 1232-1300, 2023
362023
Mixed Nash Equilibria in the Adversarial Examples Game
L Meunier, M Scetbon, R Pinot, J Atif, Y Chevaleyre
International Conference on Machine Learning (ICML), 2021
332021
Differential Privacy and Byzantine Resilience in SGD: Do They Add Up?
R Guerraoui, N Gupta, R Pinot, S Rouault, J Stephan
ACM Symposium on Principles of Distributed Computing (PODC), 2021
262021
SPEED: secure, PrivatE, and efficient deep learning
A Grivet Sébert, R Pinot, M Zuber, C Gouy-Pailler, R Sirdey
Machine Learning 110 (4), 675-694, 2021
242021
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
202019
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
202018
On the privacy-robustness-utility trilemma in distributed learning
Y Allouah, R Guerraoui, N Gupta, R Pinot, J Stephan
International Conference on Machine Learning, 569-626, 2023
182023
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
182022
On the Impossible Safety of Large AI Models
EM El-Mhamdi, S Farhadkhani, R Guerraoui, N Gupta, LN Hoang, R Pinot, ...
arXiv preprint arXiv:2209.15259, 2022
17*2022
Byzantine machine learning: A primer
R Guerraoui, N Gupta, R Pinot
ACM Computing Surveys, 2023
142023
Minimum spanning tree release under differential privacy constraints
R Pinot
Sorbonne University, 2018
122018
Robust collaborative learning with linear gradient overhead
S Farhadkhani, R Guerraoui, N Gupta, LN Hoang, R Pinot, J Stephan
International Conference on Machine Learning, 9761-9813, 2023
112023
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
52022
Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity
Y Allouah, R Guerraoui, N Gupta, R Pinot, G Rizk
Advances in Neural Information Processing Systems 36, 2024
42024
Practical Homomorphic Aggregation for Byzantine ML
A Choffrut, R Guerraoui, R Pinot, R Sirdey, J Stephan, M Zuber
arXiv preprint arXiv:2309.05395, 2023
32023
On the Relevance of Byzantine Robust Optimization Against Data Poisoning
S Farhadkhani, R Guerraoui, N Gupta, R Pinot
arXiv preprint arXiv:2405.00491, 2024
12024
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