Harnessing Sparsification in Federated Learning: A Secure, Efficient, and Differentially Private Realization

Shuangqing Xu, Yifeng Zheng, Zhongyun Hua

Federated learning (FL) enables multiple clients to jointly train a model by sharing only gradient updates for aggregation instead of raw data. Due to the transmission of very high…