2024
Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients
NeurIPS 2024poster
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 heterogeneity between the clients’ data distributions, the model obtained through the use of FL algorithms may perform poorly on…