no code implementations • 30 Sep 2023 • Xiang Liu, Liangxi Liu, Feiyang Ye, Yunheng Shen, Xia Li, Linshan Jiang, Jialin Li
Efficiently aggregating trained neural networks from local clients into a global model on a server is a widely researched topic in federated learning.
no code implementations • 3 Feb 2021 • Liangxi Liu, Xi Jiang, Feng Zheng, Hong Chen, Guo-Jun Qi, Heng Huang, Ling Shao
On the client side, a prior loss that uses the global posterior probabilistic parameters delivered from the server is designed to guide the local training.