Federated Learning with Heterogeneous Differential Privacy

no code implementations • 28 Oct 2021 • Nasser Aldaghri, Hessam Mahdavifar, Ahmad Beirami

We propose a new algorithm for FL with heterogeneous DP, named FedHDP, which employs personalization and weighted averaging at the server using the privacy choices of clients, to achieve better performance on clients' local models.

Federated Learning Privacy Preserving

Coded Machine Unlearning

no code implementations • 31 Dec 2020 • Nasser Aldaghri, Hessam Mahdavifar, Ahmad Beirami

We also present the corresponding unlearning protocol and show that it satisfies the perfect unlearning criterion.

Ensemble Learning Machine Unlearning