Joint Bandwidth Allocation, Computation Control, and Device Scheduling for Federated Learning with Energy Harvesting Devices-Reference-Cited by-同舟云学术

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Joint Bandwidth Allocation, Computation Control, and Device Scheduling for Federated Learning with Energy Harvesting Devices

Published:2022-10-31 Issue: Volume: Page:
ISSN:
Container-title:2022 56th Asilomar Conference on Signals, Systems, and Computers
language:
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Author:

Zeng Li¹,Wen Dingzhu¹,Zhu Guangxu²,You Changsheng³,Chen Qimei⁴,Shi Yuanming¹

Affiliation:

1. School of Information Science and Technology, ShanghaiTech University,Shanghai,China

2. Shenzhen Research Institute of Big Data,Shenzhen,China

3. Southern University of Science and Technology,Department of Electronic and Electrical Engineering,Shenzhen,China

4. School of Electronic Information, Wuhan University,Wuhan,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10051833/10051818/10051949.pdf?arnumber=10051949

Reference12 articles.

1. Federated Learning Over Energy Harvesting Wireless Networks

2. Energy Harvesting Wireless Communications: A Review of Recent Advances

3. Age of Information in Energy Harvesting Aided Massive Multiple Access Networks

4. On Federated Learning with Energy Harvesting Clients

5. Machine Learning at the Wireless Edge: Distributed Stochastic Gradient Descent Over-the-Air

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Accelerating Wireless Federated Learning With Adaptive Scheduling Over Heterogeneous Devices;IEEE Internet of Things Journal;2024-01-15

2. Federated Learning With Energy Harvesting Devices;IEEE Transactions on Green Communications and Networking;2023

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