FedFAIM: A Model Performance-based Fair Incentive Mechanism for Federated Learning-Reference-Cited by-同舟云学术

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FedFAIM: A Model Performance-based Fair Incentive Mechanism for Federated Learning

Published:2022 Issue: Volume: Page:1-13
ISSN:2332-7790
Container-title:IEEE Transactions on Big Data
language:
Short-container-title:IEEE Trans. Big Data

Author:

Shi Zhuan¹^ORCID,Zhang Lan¹^ORCID,Yao Zhenyu²,Lyu Lingjuan³^ORCID,Chen Cen⁴,Wang Li⁵,Wang Junhao¹,Li Xiang-Yang¹^ORCID

Affiliation:

1. School of Computer Science and Technology, University of Science and Technology of China, Hefei, China

2. Department of Mathematical Sciences, University of Liverpool, Liverpool, United Kingdom

3. Sony AI

4. School of Data Science and Engineering, East China Normal University, Shanghai, China

5. AI Department, Ant Financial, Hangzhou, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Information Systems and Management,Information Systems

Link

http://xplorestaging.ieee.org/ielx7/6687317/7153538/09797864.pdf?arnumber=9797864

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2. LEA: A Leader Election Algorithm for Distributed Physical Layer Authentication;2024 IEEE Wireless Communications and Networking Conference (WCNC);2024-04-21

3. Trustworthy Federated Learning: A Comprehensive Review, Architecture, Key Challenges, and Future Research Prospects;IEEE Open Journal of the Communications Society;2024

4. IP2FL: Interpretation-Based Privacy-Preserving Federated Learning for Industrial Cyber-Physical Systems;IEEE Transactions on Industrial Cyber-Physical Systems;2024

5. Cooperative Physical Layer Authentication With Reputation-Inspired Collaborator Selection;IEEE Internet of Things Journal;2023-12-15

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