FedRelay: Federated Relay Learning for 6G Mobile Edge Intelligence
Author:
Affiliation:
1. School of Automation, Guangdong University of Technology, Guangzhou, China
2. The Chinese University of Hong Kong, Hong Kong, China
3. State Key Laboratory of Internet of Things for Smart City, University of Macau, Macau, China
Funder
National Key R&D Program of China
National Natural Science Foundation of China
Science and Technology Development Fund of Macau SAR
FDCT-MOST Joint Project
Basic and Applied Basic Research Foundation of Guangdong Province
Fundo para o Desenvolvimento das Ciências e da Tecnologia
Guangdong-Macau Joint Laboratory for Advanced and Intelligent Computing
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Aerospace Engineering,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/25/10104191/09964279.pdf?arnumber=9964279
Reference49 articles.
1. FedGreen: Federated Learning with Fine-Grained Gradient Compression for Green Mobile Edge Computing
2. Efficient Federated Learning Algorithm for Resource Allocation in Wireless IoT Networks
3. Multi-Stage Hybrid Federated Learning Over Large-Scale D2D-Enabled Fog Networks
4. Communication-Efficient and Cross-Chain Empowered Federated Learning for Artificial Intelligence of Things
5. Toward Energy-Efficient Distributed Federated Learning for 6G Networks
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