In-depth Analysis of Low-rank Matrix Factorisation in a Federated Setting - Constantin Philippenko; Kevin Scaman; Laurent Massoulié (AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25 - March 4, 2025, Philadelphia, PA, USA, 2025)

In-depth Analysis of Low-rank Matrix Factorisation in a Federated Setting - Constantin Philippenko; Kevin Scaman; Laurent Massoulié (CoRR, 2024)

Compression bidirectionnelle pour l'apprentissage fédéré hétérogène. (Bidirectional compression for Federated Learning in a heterogeneous setting) - Constantin Philippenko (Polytechnic Institute of Paris, Palaiseau, France, 2023)

Compressed and distributed least-squares regression: convergence rates with applications to Federated Learning - Constantin Philippenko; Aymeric Dieuleveut (CoRR, 2023)

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; et al. (Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022, 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; et al. (CoRR, 2022)

Preserved central model for faster bidirectional compression in distributed settings - Constantin Philippenko; Aymeric Dieuleveut (Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual, 2021)

Preserved central model for faster bidirectional compression in distributed settings - Constantin Philippenko; Aymeric Dieuleveut (CoRR, 2021)

Artemis: tight convergence guarantees for bidirectional compression in Federated Learning - Constantin Philippenko; Aymeric Dieuleveut (CoRR, 2020)