| 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 | 109 | 2019 |
| 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 | 73 | 2020 |
| 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 | 68 | 2022 |
| 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 | 57 | 2023 |
| 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 | 51* | 2020 |
| 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 | 37 | 2021 |
| 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 | 35 | 2021 |
| Byzantine machine learning: A primer R Guerraoui, N Gupta, R Pinot ACM Computing Surveys 56 (7), 1-39, 2024 | 32 | 2024 |
| 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 | 28* | 2022 |
| 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 | 27 | 2023 |
| 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 | 26 | 2021 |
| 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 | 25 | 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 | 23 | 2019 |
| 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 | 21 | 2022 |
| 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 | 17* | 2023 |
| 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, 2023 | 16 | 2023 |
| Minimum spanning tree release under differential privacy constraints R Pinot Sorbonne University, 2018 | 12 | 2018 |
| 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 | 8 | 2022 |
| Towards Practical Homomorphic Aggregation in Byzantine-Resilient Distributed Learning A Choffrut, R Guerraoui, R Pinot, R Sirdey, J Stephan, M Zuber Proceedings of the 25th International Middleware Conference, 431-444, 2024 | 6* | 2024 |
| Byzantine-Robust Federated Learning: Impact of Client Subsampling and Local Updates Y Allouah, S Farhadkhani, R Guerraoui, N Gupta, R Pinot, G Rizk, ... Forty-first International Conference on Machine Learning, 2024 | 5* | 2024 |
rachid guerraouiProfessor of Computer and Communication Systems, EPFLE-mailová adresa ověřena na: epfl.ch