Distributed Machine Learning for Multiuser Mobile Edge Computing Systems
Author:
Affiliation:
1. School of Computer Science, Guangzhou University, Guangzhou, China
2. Provincial Key Lab of Information Coding and Transmission, Southwest Jiaotong University, Chengdu, China
3. Aristotle University of Thessaloniki, Thessaloniki, Greece
Funder
National Natural Science Foundation of China
Natural Science Foundation of Guangdong Province
Research Program of Guangzhou University
National Key R&D Program of China
Fundamental Research Funds for the Central Universities
National Mobile Communications Research Laboratory
Southeast University
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Signal Processing
Link
http://xplorestaging.ieee.org/ielx7/4200690/9776585/09670674.pdf?arnumber=9670674
Reference35 articles.
1. Energy-Latency Tradeoff for Dynamic Computation Offloading in Vehicular Fog Computing
2. FedParking: A Federated Learning Based Parking Space Estimation With Parked Vehicle Assisted Edge Computing
3. System Optimization of Federated Learning Networks With a Constrained Latency
4. Toward Resource-Efficient Federated Learning in Mobile Edge Computing
5. Artificial-Noise-Aided Transmission in Multi-Antenna Relay Wiretap Channels With Spatially Random Eavesdroppers
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