Federated Learning Model Aggregation in Heterogenous Aerial and Space Networks-Reference-Cited by-同舟云学术

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Federated Learning Model Aggregation in Heterogenous Aerial and Space Networks

Published:2024-06-09 Issue: Volume:1 Page:1262-1267
ISSN:
Container-title:2024 IEEE International Conference on Communications Workshops (ICC Workshops)
language:
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Author:

Dong Fan¹,Abbasi Ali¹,Leung Henry¹,Wang Xin²,Zhou Jiayu³,Drew Steve¹

Affiliation:

1. University of Calgary,Department of Electrical and Software Engineering,Calgary,AB,Canada

2. University of Calgary,Department of Geomatics Engineering,Calgary,AB,Canada

3. Michigan State University,Department of Computer Science and Engineering,East Lansing,MI,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10615255/10615259/10615917.pdf?arnumber=10615917

Reference17 articles.

1. Space-Air-Ground Integrated Network: A Survey

2. Aerial Edge Computing on Orbit: A Task Offloading and Allocation Scheme

3. Communication-efficient learning of deep networks from decentralized data;McMahan,2017

4. Towards federated learning at scale: System design;Bonawitz;Proceedings of machine learning and systems,2019

5. FedLE: Federated Learning Client Selection with Lifespan Extension for Edge IoT Networks

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