2 citations · 8 across the 11 of their papers we have counts for
Showing 2024 · cs.DCShow all
2 papers · 2 filters
cs.DC2024
Efficient Federated Learning Using Dynamic Update and Adaptive Pruning with Momentum on Shared Server Data
Ji Liu, Juncheng Jia, Hong Zhang +5
Despite achieving remarkable performance, Federated Learning (FL) encounters two important problems, i.e., low training efficiency and limited computational resources. In this pape…
cs.DC2024★ 2 cited
Efficient Asynchronous Federated Learning with Sparsification and Quantization
Juncheng Jia, Ji Liu, Chendi Zhou +3
While data is distributed in multiple edge devices, Federated Learning (FL) is attracting more and more attention to collaboratively train a machine learning model without transfer…