Edwige Cyffers

According to our database, Edwige Cyffers authored at least 15 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Limits of Personalizing Differential Privacy Budgets.

Edwige Cyffers, Juba Ziani

CoRR, May, 2026

Fedivertex: a Graph Dataset based on Decentralized Social Media.

Marc Damie, Edwige Cyffers

Proceedings of the ACM Web Conference 2026, 2026

2025

DP-MicroAdam: Private and Frugal Algorithm for Training and Fine-tuning.

Mihaela Hudisteanu, Nikita P. Kalinin, Edwige Cyffers

CoRR, November, 2025

Unified Privacy Guarantees for Decentralized Learning via Matrix Factorization.

Aurélien Bellet, Edwige Cyffers, Davide Frey, Romaric Gaudel, Dimitri Lerévérend, François Taïani

CoRR, October, 2025

Optimal Regularization for Performative Learning.

Edwige Cyffers, Alireza Mirrokni, Marco Mondelli

CoRR, October, 2025

Fedivertex: a Graph Dataset based on Decentralized Social Networks for Trustworthy Machine Learning.

Marc Damie, Edwige Cyffers

CoRR, May, 2025

Setting ε is not the Issue in Differential Privacy.

Edwige Cyffers

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

2024

Differential Privacy for Decentralized Learning. (Confidentialité différentielle pour l'apprentissage décentralisé).

Edwige Cyffers

PhD thesis, 2024

Optimal Classification under Performative Distribution Shift.

Edwige Cyffers, Muni Sreenivas Pydi, Jamal Atif, Olivier Cappé

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Privacy Attacks in Decentralized Learning.

Abdellah El Mrini, Edwige Cyffers, Aurélien Bellet

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Differentially Private Decentralized Learning with Random Walks.

Edwige Cyffers, Aurélien Bellet, Jalaj Upadhyay

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning.

Edwige Cyffers, Aurélien Bellet, Debabrota Basu

Proceedings of the International Conference on Machine Learning, 2023

2022

FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings.

Jean Ogier du Terrail, Samy-Safwan Ayed, Edwige Cyffers, Felix Grimberg, Chaoyang He, Regis Loeb, Paul Mangold, Tanguy Marchand, Othmane Marfoq, Erum Mushtaq, Boris Muzellec, Constantin Philippenko, Santiago Silva, Maria Telenczuk, Shadi Albarqouni, Salman Avestimehr, Aurélien Bellet, Aymeric Dieuleveut, Martin Jaggi, Sai Praneeth Karimireddy, Marco Lorenzi, Giovanni Neglia, Marc Tommasi, Mathieu Andreux

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging.

Edwige Cyffers, Mathieu Even, Aurélien Bellet, Laurent Massoulié

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Privacy Amplification by Decentralization.

Edwige Cyffers, Aurélien Bellet

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022