Publications
[5] In-depth Analysis of Low-rank Matrix Factorisation in a Federated Setting.   
 C. Philippenko, K. Scaman; L. Massoulié
 Arxiv Preprint, 2024   PDF   Code  
[4] Compressed and distributed least-squares regression: convergence rates with applications to Federated Learning.
 C. Philippenko, A. Dieuleveut
 Arxiv Preprint, 2023   PDF   Code  
[3] FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings
 J. Ogier du Terrail, […] C. Philippenko, […] M. Andreux
 Accepted at NeurIPS Dataset 2022
 Arxiv Preprint, 2022   PDF   Code  
[2] Preserved central model for faster bidirectional compression in distributed settings.
 C. Philippenko, A. Dieuleveut
 Accepted at NeurIPS 2021 
 Arxiv Preprint, 2021   PDF   Code
[1] Artemis: tight convergence guarantees for bidirectional compression in federated learning.
 C. Philippenko, A. Dieuleveut
 Arxiv Preprint, 2020   PDF   Code  
