3 papers
cs.LG2025
Robust and Efficient Collaborative Learning
Abdellah El Mrini, Sadegh Farhadkhan, Rachid Guerraoui
Collaborative machine learning is challenged by training-time adversarial behaviors. Existing approaches to tolerate such behaviors either rely on a central server or induce high c…
cs.LG2024
Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients
Youssef Allouah, Abdellah El Mrini, Rachid Guerraoui +2
Federated learning (FL) is an appealing paradigm that allows a group of machines (a.k.a. clients) to learn collectively while keeping their data local. However, due to the heteroge…
cs.LG2024
Privacy Attacks in Decentralized Learning
Abdellah El Mrini, Edwige Cyffers, Aurélien Bellet
Decentralized Gradient Descent (D-GD) allows a set of users to perform collaborative learning without sharing their data by iteratively averaging local model updates with their nei…