Ensemble Distillation based Adaptive Quantization for Supporting Federated Learning in Wireless Networks-Reference-Cited by-同舟云学术

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Ensemble Distillation based Adaptive Quantization for Supporting Federated Learning in Wireless Networks

Published:2022 Issue: Volume: Page:1-1
ISSN:1536-1276
Container-title:IEEE Transactions on Wireless Communications
language:
Short-container-title:IEEE Trans. Wireless Commun.

Author:

Liu Yi-Jing¹^ORCID,Feng Gang¹^ORCID,Niyato Dusit²^ORCID,Qin Shuang¹,Zhou Jianhong³^ORCID,Li Xiaoqian¹^ORCID,Xu Xinyi¹

Affiliation:

1. National Key Lab on Communications, University of Electronic Science and Technology of China, Chengdu, P. R. China

2. School of Computer Science and Engineering, Nanyang Technological University, Singapore

3. School of Computer and Software Engineering, Xihua University, Chengdu, P. R. China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Science Applications

Link

http://xplorestaging.ieee.org/ielx7/7693/4656680/09962801.pdf?arnumber=9962801

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. Communication-Efficient Personalized Federated Learning for Green Communications in IoMT;ICC 2024 - IEEE International Conference on Communications;2024-06-09

2. AQUILA: Communication Efficient Federated Learning With Adaptive Quantization in Device Selection Strategy;IEEE Transactions on Mobile Computing;2023

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