Forgettable Federated Linear Learning with Certified Data Unlearning

Understand

Federated Learning (FL) enables collaborative model training across distributed clients while preserving user privacy.

• Recently, Federated Unlearning (FU) has emerged to address the "right to be forgotten" and to remove the influence of poisoned or target clients without retraining the entire FL system.
• However, many FU methods require communication with retained or target clients, introduce additional security risks, or store historical models, limiting their efficiency and practicality.
• Moreover, most FU methods for deep neural networks (DNNs) lack theoretical certification due to the complexity of nonlinear models and their training dynamics.