Further results on latent discourse models and word embeddings. - Sammy Khalife; Douglas Soares Gonçalves; Youssef Allouah; Leo Liberti (J. Mach. Learn. Res., 2021)

Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity. - Youssef Allouah; Sadegh Farhadkhani; Rachid Guerraoui; Nirupam Gupta; Rafael Pinot; John Stephan (AISTATS, 2023)

On the Privacy-Robustness-Utility Trilemma in Distributed Learning. - Youssef Allouah; Rachid Guerraoui; Nirupam Gupta; Rafael Pinot; John Stephan (ICML, 2023)

Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity. - Youssef Allouah; Rachid Guerraoui; Nirupam Gupta; Rafael Pinot; Geovani Rizk (NeurIPS, 2023)

Distributed Learning with Curious and Adversarial Machines. - Youssef Allouah; Rachid Guerraoui; Nirupam Gupta; Rafael Pinot; John Stephan (CoRR, 2023)

Can Machines Learn Robustly, Privately, and Efficiently? - Youssef Allouah; Rachid Guerraoui; John Stephan (CoRR, 2023)

Robust Sparse Voting. - Youssef Allouah; Rachid Guerraoui; Lê-Nguyên Hoang; Oscar Villemaud (AISTATS, 2024)

Byzantine-Robust Federated Learning: Impact of Client Subsampling and Local Updates. - Youssef Allouah; Sadegh Farhadkhani; Rachid Guerraoui; Nirupam Gupta; Rafael Pinot; Geovani Rizk; Sasha Voitovych (ICML, 2024)

The Privacy Power of Correlated Noise in Decentralized Learning. - Youssef Allouah; Anastasia Koloskova; Aymane El Firdoussi; Martin Jaggi; Rachid Guerraoui (ICML, 2024)

Revisiting Ensembling in One-Shot Federated Learning. - Youssef Allouah; Akash Balasaheb Dhasade; Rachid Guerraoui; Nirupam Gupta; Anne-Marie Kermarrec; Rafael Pinot; Rafael Pires 001; Rishi Sharma 001 (NeurIPS, 2024)

Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients. - Youssef Allouah; Abdellah El Mrini; Rachid Guerraoui; Nirupam Gupta; Rafael Pinot (NeurIPS, 2024)

Tackling Byzantine Clients in Federated Learning. - Youssef Allouah; Sadegh Farhadkhani; Rachid Guerraoui; Nirupam Gupta; Rafael Pinot; Geovani Rizk; Sasha Voitovych (CoRR, 2024)

Boosting Robustness by Clipping Gradients in Distributed Learning. - Youssef Allouah; Rachid Guerraoui; Nirupam Gupta; Ahmed Jellouli; Geovani Rizk; John Stephan (CoRR, 2024)

Adaptive Gradient Clipping for Robust Federated Learning. - Youssef Allouah; Rachid Guerraoui; Nirupam Gupta; Ahmed Jellouli; Geovani Rizk; John Stephan (ICLR, 2025)

The Utility and Complexity of In- and Out-of-Distribution Machine Unlearning. - Youssef Allouah; Joshua Kazdan; Rachid Guerraoui; Sanmi Koyejo (ICLR, 2025)

Towards Trustworthy Federated Learning with Untrusted Participants. - Youssef Allouah; Rachid Guerraoui; John Stephan (CoRR, 2025)

Certified Unlearning for Neural Networks. - Anastasia Koloskova; Youssef Allouah; Animesh Jha; Rachid Guerraoui; Sanmi Koyejo (CoRR, 2025)

Distributional Unlearning: Forgetting Distributions, Not Just Samples. - Youssef Allouah; Rachid Guerraoui; Sanmi Koyejo (CoRR, 2025)