FFD: A Full-Stack Federated Distillation method for Heterogeneous Massive IoT Networks-Reference-Cited by-同舟云学术

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FFD: A Full-Stack Federated Distillation method for Heterogeneous Massive IoT Networks

Published:2022-10-20 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Advanced Technologies for Communications (ATC)
language:
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Author:

Nguyen Minh-Duong¹,Luong Hong-Son²,Tung-Nguyen ¹,Pham Quoc-Viet³,Do Quang Vinh¹,Hwang Won-Joo⁴

Affiliation:

1. Pusan National University,Department of Information Convergence Engineering,Busan,Republic of Korea,46241

2. Department of Autonomous Driving,Vinfast,Hanoi,Vietnam

3. Pusan National University,Korean Southeast Center for the 4th Industrial Revolution Leader Education,Busan,Republic of Korea,46241

4. Pusan National University,Department of Biomedical Convergence Engineering,Yangsan,Republic of Korea,50612

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9942959/9942960/09943034.pdf?arnumber=9943034

Reference24 articles.

1. Decentralized federated learning via mutual knowledge transfer;li;IEEE Internet of Things Journal,2021

2. SCAFFOLD: stochastic controlled averaging for on-device federated learning;karimireddy;CoRR,2019

3. Trust region policy optimization;schulman;CoRR,2015

4. Proximal policy optimization algorithms;schulman;CoRR,2017

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