All papers
Team Toronto around Nicolas Papernot and Adam Dziedzic won the ICLR’22 Spotlight Award for “Increasing the Cost of Model Extraction with Calibrated Proof of Work”.
ICRL’22 Spotlight Award Read More »
The University of Southern California Team around Salman Avestimehr and Murali Annavaram won the FL-AAAI ’22 Best Paper Award for “SSFL: Tackling Label Deficiency in Federated Learning via Personalized Self-Supervision“.
Best Paper Award at the FL-AAAI ’22 Read More »
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.
Best Paper Award at the ICLR 2021 Secure ML Workshop Read More »
Salman Avastimehr and his group, University of Southern California have just received the Baidu Best Paper Award at NeurIPS – SpicyFL 2020 (Workshop on Scalability, Privacy, and Security in Federated Learning) for the paper “FedML: A Research Library and Benchmark for Federated Machine Learning”
Baidu Best Paper Award at NeurIPS – SpicyFL 2020 Read More »
