Throughput-Optimal Topology Design for Cross-Silo Federated Learning. - Othmane Marfoq; Chuan Xu 002; Giovanni Neglia; Richard Vidal (NeurIPS, 2020)

Federated Multi-Task Learning under a Mixture of Distributions. - Othmane Marfoq; Giovanni Neglia; Aurélien Bellet; Laetitia Kameni; Richard Vidal (NeurIPS, 2021)

Personalized Federated Learning through Local Memorization. - Othmane Marfoq; Giovanni Neglia; Richard Vidal; Laetitia Kameni (ICML, 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 001; Regis Loeb; Paul Mangold; Tanguy Marchand; Othmane Marfoq; Erum Mushtaq; Boris Muzellec; Constantin Philippenko; et al. (NeurIPS, 2022)

Federated Learning for Data Streams. - Othmane Marfoq; Giovanni Neglia; Laetitia Kameni; Richard Vidal (AISTATS, 2023)

Tackling heterogeneity in federated learning systems. (Surmonter l'hétérogénéité dans les systèmes d'apprentissage fédéré). - Othmane Marfoq (2023)

Count-Min Sketch with Conservative Updates: Worst-Case Analysis. - Younes Ben Mazziane; Othmane Marfoq (CoRR, 2024)

A Cautionary Tale: On the Role of Reference Data in Empirical Privacy Defenses. - Caelin Kaplan; Chuan Xu 002; Othmane Marfoq; Giovanni Neglia; Anderson Santana de Oliveira (Proc. Priv. Enhancing Technol., 2024)

Federated Learning Under Heterogeneous and Correlated Client Availability. - Angelo Rodio; Francescomaria Faticanti; Othmane Marfoq; Giovanni Neglia; Emilio Leonardi (IEEE/ACM Trans. Netw., 2024)

Attribute Inference Attacks for Federated Regression Tasks. - Francesco Diana; Othmane Marfoq; Chuan Xu 002; Giovanni Neglia; Frédéric Giroire; Eoin Thomas (AAAI, 2025)

Universal and Tight Bounds on Counting Errors of Count-Min Sketch with Conservative Updates. - Younes Ben Mazziane; Othmane Marfoq (Proc. ACM Meas. Anal. Comput. Syst., 2025)