58 citations · 131 across the 26 of their papers we have counts for
Showing 2023 · cs.DCShow all
3 papers · 2 filters
cs.DC2023★ 1 cited
AEDFL: Efficient Asynchronous Decentralized Federated Learning with Heterogeneous Devices
Ji Liu, Tianshi Che, Yang Zhou +4
Federated Learning (FL) has achieved significant achievements recently, enabling collaborative model training on distributed data over edge devices. Iterative gradient or model exc…
cs.DC2023★ 3 cited
FedASMU: Efficient Asynchronous Federated Learning with Dynamic Staleness-aware Model Update
Ji Liu, Juncheng Jia, Tianshi Che +5
As a promising approach to deal with distributed data, Federated Learning (FL) achieves major advancements in recent years. FL enables collaborative model training by exploiting th…
cs.DC2023★ 1 cited
Distributed and Deep Vertical Federated Learning with Big Data
Ji Liu, Xuehai Zhou, Lei Mo +5
In recent years, data are typically distributed in multiple organizations while the data security is becoming increasingly important. Federated Learning (FL), which enables multipl…