2 citations · 4 across the 4 of their papers we have counts for
5 papers
PFL-MoE: Personalized Federated Learning Based on Mixture of Experts
Binbin Guo, Yuan Mei, Danyang Xiao +3
Federated learning (FL) is an emerging distributed machine learning paradigm that avoids data sharing among training nodes so as to protect data privacy. Under coordination of the…
Impact of Temporary Fork on the Evolution of Mining Pools in Blockchain Networks: An Evolutionary Game Analysis
Canhui Chen, Xu Chen, Jiangshan Yu +2
Temporary fork is a fundamental phenomenon in many blockchains with proof of work, and the analysis of temporary fork has recently drawn great attention. Different from existing ef…
Garou: An Efficient and Secure Off-Blockchain Multi-Party Payment Hub
Yongjie Ye, Weigang Wu
To mitigate the scalability problem of decentralized cryptocurrencies such as Bitcoin and Ethereum, the payment channel, which allows two parties to perform secure coin transfers w…
Boros: Secure Cross-Channel Transfers via Channel Hub
YongJie Ye, Jingjing Zhang, Weigang Wu +2
The payment channel, which allows two parties to perform micropayments without involving the blockchain, has become a promising proposal to improve the scalability of decentralized…
Exploiting Massive D2D Collaboration for Energy-Efficient Mobile Edge Computing
Xu Chen, Lingjun Pu, Lin Gao +2
In this article we propose a novel Device-to-Device (D2D) Crowd framework for 5G mobile edge computing, where a massive crowd of devices at the network edge leverage the network-as…