9 citations · 16 across the 3 of their papers we have counts for
3 papers
cs.DC2022★ 7 cited
Adaptive Control of Client Selection and Gradient Compression for Efficient Federated Learning
Zhida Jiang, Yang Xu, Hongli Xu +2
Federated learning (FL) allows multiple clients cooperatively train models without disclosing local data. However, the existing works fail to address all these practical concerns i…
cs.NI2022
Adaptive Configuration for Heterogeneous Participants in Decentralized Federated Learning
Yunming Liao, Yang Xu, Hongli Xu +2
Data generated at the network edge can be processed locally by leveraging the paradigm of edge computing (EC). Aided by EC, decentralized federated learning (DFL), which overcomes…
cs.NI2016★ 9 cited
SICS: Secure In-Cloud Service Function Chaining
Huazhe Wang, Xin Li, Yu Zhao +3
There is an increasing trend that enterprises outsource their network functions to the cloud for lower cost and ease of management. However, network function outsourcing brings thr…