The paper (“ScionFL: Secure quantized aggregation for federated learning”) by Yaniv Ben-Itzhak, Helen Möllering, Benny Pinkas, Thomas Schneider, Ajith Suresh, Oleksandr Tkachenko, Shay Vargaftik, Christian Weinert, Hossein Yalame, and Avishay Yanai won the Runner-Up Distinguished Paper Award at the 2. IEEE Conference on Secure and Trustworthy Machine Learning (SaTML’24).

The paper describes how to use quantization to reduce client-server communication in secure federated learning. It emerged from an industry collaboration with VMWare Research, Aptos Labs, Technology Innovation Institute, and DFINITY Foundation within the Private AI Collaborative Research Institute.