pMPL: A Robust Multi-Party Learning Framework with a Privileged PartyConference on Computer and Communications Security (CCS), 2022 |
Private, Efficient, and Accurate: Protecting Models Trained by
Multi-party Learning with Differential PrivacyIEEE Symposium on Security and Privacy (IEEE S&P), 2022 |