115 citations · 181 across the 4 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2025
Federated Unlearning Made Practical: Seamless Integration via Negated Pseudo-Gradients
Alessio Mora, Carlo Mazzocca, Rebecca Montanari +1
The right to be forgotten is a fundamental principle of privacy-preserving regulations and extends to Machine Learning (ML) paradigms such as Federated Learning (FL). While FL enha…
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…