Compressed Sensing-Based Practical and Efficient Privacy-Preserving Federated Learning-Reference-Cited by-同舟云学术

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Compressed Sensing-Based Practical and Efficient Privacy-Preserving Federated Learning

Published:2023 Issue: Volume: Page:1-1
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Chen Siguang¹^ORCID,Miao Yifeng¹,Li Xue²^ORCID,Zhao Chuanxin³^ORCID

Affiliation:

1. Siguang Chen and Yifeng Miao with the School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, China

2. Department of Dermatology, Women’s Hospital of Nanjing Medical University (Nanjing Maternity and Child Health Care Hospital), Nanjing, China

3. School of Computer and Information, Anhui Normal University, Wuhu, China

Funder

National Natural Science Foundation of China

1311 Talents Plan of NJUPT

333 High-level Talents Training Project of Jiangsu Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/6488907/6702522/10342861.pdf?arnumber=10342861

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1. A Multi-Dimensional Reverse Auction Mechanism for Volatile Federated Learning in the Mobile Edge Computing Systems;Electronics;2024-08-09

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