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cs.LG2025
FedUP: Efficient Pruning-based Federated Unlearning for Model Poisoning Attacks
Nicolò Romandini, Cristian Borcea, Rebecca Montanari +1
Federated Learning (FL) can be vulnerable to attacks, such as model poisoning, where adversaries send malicious local weights to compromise the global model. Federated Unlearning (…
cs.LG2024★ 64 cited
Federated Unlearning: A Survey on Methods, Design Guidelines, and Evaluation Metrics
Nicolò Romandini, Alessio Mora, Carlo Mazzocca +2
Federated learning (FL) enables collaborative training of a machine learning (ML) model across multiple parties, facilitating the preservation of users' and institutions' privacy b…