| POSEIDON: Privacy-preserving federated neural network learning S Sav, A Pyrgelis, JR Troncoso-Pastoriza, D Froelicher, JP Bossuat, ... Network and Distributed Systems Security (NDSS) Symposium 2021, 2020 | 152 | 2020 |
| Scalable privacy-preserving distributed learning D Froelicher, JR Troncoso-Pastoriza, A Pyrgelis, S Sav, JS Sousa, ... Proceedings on Privacy Enhancing Technologies (PoPETs) 2021(2), 323-347, 2021 | 63 | 2021 |
| Privacy-preserving federated neural network learning for disease-associated cell classification S Sav, JP Bossuat, JR Troncoso-Pastoriza, M Claassen, JP Hubaux Patterns 3 (5), 2022 | 23 | 2022 |
| SIMARD: A simulated annealing based RNA design algorithm with quality pre-selection strategies S Sav, DJD Hampson, HH Tsang 2016 IEEE Symposium Series on Computational Intelligence (SSCI), 1-8, 2016 | 12 | 2016 |
| Examining the annealing schedules for RNA design algorithm HE Erhan, S Sav, S Kalashnikov, HH Tsang 2016 IEEE Congress on Evolutionary Computation (CEC), 1295-1302, 2016 | 8 | 2016 |
| Investigation of Multi-Objective Optimization criteria for RNA design DJD Hampson, S Sav, HH Tsang 2016 IEEE Symposium Series on Computational Intelligence (SSCI), 1-8, 2016 | 6 | 2016 |
| Privacy-Preserving Federated Recurrent Neural Networks S Sav, A Diaa, A Pyrgelis, JP Bossuat, JP Hubaux Proceedings on Privacy Enhancing Technologies (PoPETs) 2023(4), 500-521, 2023 | 5 | 2023 |
| System and method for privacy-preserving distributed training of machine learning models on distributed datasets D Froelicher, JR Troncoso-Pastoriza, A Pyrgelis, S Sav, JGDSE Sousa, ... US Patent App. 17/998,120, 2023 | 4 | 2023 |
| System and method for privacy-preserving distributed training of neural network models on distributed datasets S Sav, JR Troncoso-Pastoriza, A Pyrgelis, D Froelicher, JGDSE Sousa, ... US Patent App. 18/043,186, 2023 | 2 | 2023 |
| slytHErin: An Agile Framework for Encrypted Deep Neural Network Inference F Intoci, S Sav, A Pyrgelis, JP Bossuat, JR Troncoso-Pastoriza, ... International Conference on Applied Cryptography and Network Security, 359-377, 2023 | 1 | 2023 |
| How to Privately Tune Hyperparameters in Federated Learning? Insights from a Benchmark Study N Mitic, A Pyrgelis, S Sav arXiv preprint arXiv:2402.16087, 2024 | | 2024 |
| Privacy-preserving federated neural network training and inference S Sav EPFL, 2023 | | 2023 |
| Privacy-preserving computation and robust watermarking techniques for healthcare data S Sav PQDT-Global, 2018 | | 2018 |
| Efsanenin doğduğu yer: Çarşı AO Gitmez, HO Karayiğit, Hİ Görgen, K Gökyürek, S Sav Bilkent University, 0 | | |
| Group ID U13548 Affiliated authors Chatel, Sylvain G Cherubin, I Coke, K Edalatnejadkhamene, L Girod, K Gétaz, K Kireev, ... | | |
| LDS E Ayday, L Barman, I Bilogrevic, JP Bossuat, R Bouyé, ... | | |
Jean-Pierre HubauxProfessor, EPFLAdresse e-mail validée de epfl.ch
