Best Paper Award at the ICLR 2021 Secure ML Workshop

 

Tian Li, Shengyuan Hu, Ahmad Beirami and Virginia Smith (CMU) won a Best Paper Award at the ICLR 2021 for „Ditto: Fair and Robust Federated Learning Through Personalization”. Fairness and robustness are two important concerns for federated learning systems. In this work, they identify that robustness to data and model poisoning attacks and fairness, measured as the uniformity of performance across devices, are competing constraints in statistically heterogeneous networks.