Towards Energy Efficient Federated Learning over 5G+ Mobile Devices

Towards Energy Efficient Federated Learning over 5G+ Mobile Devices

The continuous convergence of machine learning algorithms, 5G and beyond (5G+) wireless communications, and artificial intelligence (AI) hardware implementation hastens the birth of federated learning (FL) over 5G+ mobile devices, which pushes AI functions to mobile devices and initiates a new era o...

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Bibliographic Details
Main Authors: Chen, R. (Author), Fang, Y. (Author), Li, L. (Author), Pan, M. (Author), Prakash, P. (Author), Shi, D. (Author)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2022
Subjects:
5G mobile communication
5G mobile communication systems
Artificial intelligence
Computational modeling
Computational modelling
Computer graphics
Computer graphics equipment
Economic and social effects
Energy consumption
Energy efficiency
Energy efficient
Energy utilization
Energy-consumption
Graphics processing unit
Hardware implementations
Learning algorithms
Learning systems
Machine learning algorithms
Mobile handsets
Overall energy efficiency
Program processors
Quantization (signal)
Trade off
Training
Wireless communication
Wireless communications
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