7 citations · 25 across the 18 of their papers we have counts for
Showing 2023 · cs.DCShow all
3 papers · 2 filters
cs.DC2023★ 4 cited
Joint Client Assignment and UAV Route Planning for Indirect-Communication Federated Learning
Jieming Bian, Cong Shen, Jie Xu
Federated Learning (FL) is a machine learning approach that enables the creation of shared models for powerful applications while allowing data to remain on devices. This approach…
cs.DC2023★ 2 cited
Accelerating Hybrid Federated Learning Convergence under Partial Participation
Jieming Bian, Lei Wang, Kun Yang +2
Over the past few years, Federated Learning (FL) has become a popular distributed machine learning paradigm. FL involves a group of clients with decentralized data who collaborate…
cs.DC2023
Federated Learning via Indirect Server-Client Communications
Jieming Bian, Cong Shen, Jie Xu
Federated Learning (FL) is a communication-efficient and privacy-preserving distributed machine learning framework that has gained a significant amount of research attention recent…