Differential Privacy-Preserving of Multi-Party Collaboration Under Federated Learning in Data Center Networks-Reference-Cited by-同舟云学术

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Differential Privacy-Preserving of Multi-Party Collaboration Under Federated Learning in Data Center Networks

Published:2023 Issue: Volume: Page:1-15
ISSN:2471-285X
Container-title:IEEE Transactions on Emerging Topics in Computational Intelligence
language:
Short-container-title:IEEE Trans. Emerg. Top. Comput. Intell.

Author:

Wang Xi¹^ORCID,Fan Weibei²^ORCID,Hu Xinzhi²^ORCID,He Jing³^ORCID,Chi Chi-Hung⁴^ORCID

Affiliation:

1. Suzhou Institute of Industrial Technology, Suzhou, Jiangsu, China

2. College of Computer, Nanjing University of Posts and Telecommunications, Nanjing, China

3. Department of Neuroscience, University of Oxford, Oxford, U.K.

4. National Digital Trust Centre, Nanyang Technological University, Singapore

Funder

National Natural Science Foundation of China

Natural Science Fund For Colleges and Universities in Jiangsu Province

Future Network Scientific Research Fund Project

Innovative Research Team Project of Suzhou Institute of Industrial Technology

Qing Lan Project of Jiangsu Province

High end Training Program for Professional Leaders of Vocational College Teachers in Jiangsu Province

2023 General Project of Philosophy and Social Sciences Research in Higher Education Institutions

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computational Mathematics,Control and Optimization,Computer Science Applications

Link

http://xplorestaging.ieee.org/ielx7/7433297/7777658/10374365.pdf?arnumber=10374365

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