Guest Editorial: Special Issue on Trustworthy Federated Learning

被引：0

作者：

Yang, Qiang ^{[1
]}

Yu, Han ^{[2
]}

Teo, Sin G. ^{[3
]}

Li, Bo ^{[4
]}

Long, Guodong ^{[5
]}

Jin, Chao ^{[3
]}

Fan, Lixin ^{[6
]}

Liu, Yang ^{[7
]}

Zhang, Le ^{[8
]}

机构：

[1] Hong Kong Univ Sci & Technol, WeBank, Shenzhen 518000, Peoples R China

[2] Nanyang Technol Univ, Singapore 639798, Singapore

[3] ASTAR, Singapore 130632, Singapore

[4] Univ Chicago, Chicago, IL 60637 USA

[5] Univ Technol Sydney, Sydney, NSW 2007, Australia

[6] WeBank, Shenzhen 518000, Peoples R China

[7] Tsinghua Univ, Beijing 100084, Peoples R China

[8] Univ Elect Sci & Technol China, Chengdu 611731, Peoples R China

来源：

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS | 2025年 / 36卷 / 01期

关键词：

Special issues and sections; Trusted computing; Federated learning; General Data Protection Regulation; Artificial intelligence; Regulation; Privacy; Data privacy;

D O I：

10.1109/TNNLS.2024.3490192

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

引用

页码：5 / 5

页数：1

共 9 条

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[9]

Zhang XT, 2025, IEEE T NEUR NET LEAR, V36, P88, DOI 10.1109/TNNLS.2024.3405190

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