Guaranteeing Data Privacy in Federated Unlearning With Dynamic User Participation
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DOI: 10.1109/tdsc.2024.3476533
Abstract: Federated Unlearning (FU) is gaining prominence for its capability to eliminate influences of specific users’ data from trained global Federated Learning (FL) models. A straightforward FU method involves removing the unlearned user-specified data and subsequently… read more here.
Keywords: unlearning efficiency; privacy; federated unlearning; user participation ... See more keywords