Jin-Shan Lai

Proactive Federated Unlearning: Sensitivity-Guided Sparse Adaptation on Key Layers

Driven by privacy regulations, federated unlearning (FU) aims to remove the influence of specific clients or samples from a trained federated model, approximating the behavior of retraining from scratch without the target data. However, existing FU methods are largely reactive: retraining-based solutions are accurate b...