Fairness-Aware Federated Learning With Unreliable Links in Resource-Constrained Internet of Things-Reference-Cited by-同舟云学术

Fairness-Aware Federated Learning With Unreliable Links in Resource-Constrained Internet of Things

Published:2022-09-15 Issue:18 Volume:9 Page:17359-17371
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Li Zhidu¹^ORCID,Zhou Yujie¹^ORCID,Wu Dapeng¹^ORCID,Tang Tong¹^ORCID,Wang Ruyan¹^ORCID

Affiliation:

1. School of Communication and Information Engineering, Advanced Network and Intelligent Interconnection Technology Key Laboratory of Chongqing Education Commission of China, Key Laboratory of Ubiquitous Sensing and Networking in Chongqing, Chongqing University of Posts and Telecommunications, Chongqing, China

Funder

National Natural Science Foundation of China

China University Industry-University-Research Collaborative Innovation Fund

Natural Science Foundation of Chongqing

University Innovation Research Group of Chongqing

2019 Industrial Internet Innovation and Development Project Software Defined Industrial Internet Identification Data Management System

2020 Industrial Internet Innovation and Development Project Regional Integration Industrial Internet Public Service Platform

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/6488907/9881201/09726793.pdf?arnumber=9726793

Reference27 articles.

1. Performance Optimization of Federated Learning over Wireless Networks

2. Scheduling Policies for Federated Learning in Wireless Networks

3. Federated Learning in Unreliable and Resource-Constrained Cellular Wireless Networks

4. Distributed delayed stochastic optimization

5. Asynchronous parallel stochastic gradient for nonconvex optimization;lian;Advances in neural information processing systems,0

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