Efficient Federated Learning in Wireless Communication Systems: A Multi-Objective Optimization Perspective-Reference-Cited by-同舟云学术

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Efficient Federated Learning in Wireless Communication Systems: A Multi-Objective Optimization Perspective

Published:2023-08-10 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/CIC International Conference on Communications in China (ICCC)
language:
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Author:

Zhou Yu¹,Zhao Xiaohui¹,Liu Xuemei²,You Lei³,Lei Lei¹

Affiliation:

1. Xi’an Jiaotong University,School of Information and Communications Engineering,Xi’an,P. R. China

2. Institute of Rail Transit, Tongji University,Shanghai,P. R. China

3. Technical University of Denmark,Department of Engineering Technology,Ballerup,Denmark

Funder

Southeast University

Natural Science Foundation of Sichuan Province

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10233255/10233122/10233536.pdf?arnumber=10233536

Reference12 articles.

1. On the performance of multiple-objective genetic local search on the 0/1 knapsack problem - a comparative experiment

2. Federated Learning in Mobile Edge Networks: A Comprehensive Survey

3. Dynamic MOPSO-Based Optimal Control for Wastewater Treatment Process

4. Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms;xiao,2017

5. Client Selection and Bandwidth Allocation in Wireless Federated Learning Networks: A Long-Term Perspective

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