FedVQCS: Federated Learning via Vector Quantized Compressed Sensing-Reference-Cited by-同舟云学术

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FedVQCS: Federated Learning via Vector Quantized Compressed Sensing

Published:2023 Issue: Volume: Page:1-1
ISSN:1536-1276
Container-title:IEEE Transactions on Wireless Communications
language:
Short-container-title:IEEE Trans. Wireless Commun.

Author:

Oh Yongjeong¹,Jeon Yo-Seb¹^ORCID,Chen Mingzhe²^ORCID,Saad Walid³^ORCID

Affiliation:

1. Department of Electrical Engineering, POSTECH, Pohang, Gyeongbuk, Republic of Korea

2. Department of Electrical and Computer Engineering and Institute for Data Science and Computing, University of Miami, Coral Gables, FL, USA

3. Wireless@VT, Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA, USA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Science Applications

Link

http://xplorestaging.ieee.org/ielx7/7693/4656680/10181115.pdf?arnumber=10181115

Cited by 3 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. Comprehensive Study of Compression and Texture Integration for Digital Imaging and Communications in Medicine Data Analysis;Technologies;2024-01-24

2. Energy Minimization for Federated Learning Based Radio Map Construction;IEEE Transactions on Machine Learning in Communications and Networking;2024

3. Tighter Regret Analysis and Optimization of Online Federated Learning;IEEE Transactions on Pattern Analysis and Machine Intelligence;2023-12

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