Decentralized P2P Federated Learning for Privacy-Preserving and Resilient Mobile Robotic Systems-Reference-Cited by-同舟云学术

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Decentralized P2P Federated Learning for Privacy-Preserving and Resilient Mobile Robotic Systems

Published:2023-04 Issue:2 Volume:30 Page:82-89
ISSN:1536-1284
Container-title:IEEE Wireless Communications
language:
Short-container-title:IEEE Wireless Commun.

Author:

Zhou Xiaokang¹,Liang Wei²,Wang Kevin I-Kai³,Yan Zheng⁴,Yang Laurence T.⁵,Wei Wei⁶,Ma Jianhua⁷,Jin Qun⁸

Affiliation:

1. Shiga University,Japan

2. Hunan University of Technology and Business,China

3. University of Auckland,New Zealand

4. Xidian University,China

5. St. Francis Xavier University,Canada

6. Xi'an University of Technology,China

7. Hosei University,Japan

8. Waseda University,Japan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications

Link

http://xplorestaging.ieee.org/ielx7/7742/10104586/10105168.pdf?arnumber=10105168

Reference15 articles.

1. Privacy-Preserving Cost-Sensitive Learning

2. Efficient and Secure Skyline Queries over Vertical Data Federation

3. Secret key generation exploiting channel characteristics in wireless communications

4. Pain-FL: Personalized Privacy-Preserving Incentive for Federated Learning

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