Digital AirComp-Assisted Federated Edge Learning with Adaptive Quantization-Reference-Cited by-同舟云学术

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Digital AirComp-Assisted Federated Edge Learning with Adaptive Quantization

Published:2024-05-15 Issue: Volume: Page:1-6
ISSN:
Container-title:2024 IEEE 4th International Conference on Human-Machine Systems (ICHMS)
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Author:

Kianfar Ghazaleh¹,Dmohammadi S. Jamal Seye¹,Abouei Jamshid²,Mohammadi Arash¹,Plataniotis Konstantinos N.³

Affiliation:

1. Concordia Institute of Information Systems Engineering (CIISE), Concordia University,Montreal,Canada

2. Yazd University,Dept. of Electrical Engineering,Yazd,Iran

3. University of Toronto,The Edward S. Rogers Sr. Dept. of Electrical & Computer Engineering,Canada

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10555565/10555582/10555608.pdf?arnumber=10555608

Reference17 articles.

1. Edge Learning for B5G Networks With Distributed Signal Processing: Semantic Communication, Edge Computing, and Wireless Sensing

2. FedHome: Cloud-Edge based Personalized Federated Learning for In-Home Health Monitoring

3. Federated Learning Meets Human Emotions: A Decentralized Framework for Human–Computer Interaction for IoT Applications

4. Communication-Efficient Federated Learning for Hybrid VLC/RF Indoor Systems

5. Distillation and Ordinary Federated Learning Actor-Critic Algorithms in Heterogeneous UAV-Aided Networks

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