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Xiaojin Zhang — most-cited papers & profile · Federated Learning
← authors
·
overview
Xiaojin Zhang
14
papers ·
14
citations ·
8
h-index
Chinese University of Hong Kong
Google Scholar ↗
Semantic Scholar ↗
OpenAlex ↗
Most-cited papers
Trading Off Privacy, Utility and Efficiency in Federated Learning
2022 · 5 citations
A Framework for Evaluating Privacy-Utility Trade-off in Vertical Federated Learning
2022 · 5 citations
Probably Approximately Correct Federated Learning
2023 · 2 citations
No Free Lunch Theorem for Security and Utility in Federated Learning
2022 · 1 citations
Deciphering the Interplay between Attack and Protection Complexity in Privacy-Preserving Federated Learning
2025
A Game-theoretic Framework for Privacy-preserving Federated Learning
2023
Towards Achieving Near-optimal Utility for Privacy-Preserving Federated Learning via Data Generation and Parameter Distortion
2023
Theoretically Principled Federated Learning for Balancing Privacy and Utility
2023
A Meta-learning Framework for Tuning Parameters of Protection Mechanisms in Trustworthy Federated Learning
2023
Toward the Tradeoffs between Privacy, Fairness and Utility in Federated Learning
2023
A Unified Learn-to-Distort-Data Framework for Privacy-Utility Trade-off in Trustworthy Federated Learning
2024
Fed-AugMix: Balancing Privacy and Utility via Data Augmentation
2024
Top co-authors
Qiang Yang
· 9
Kai Chen
· 7
Lixin Fan
· 5
Wei Chen
· 3
Mingcong Xu
· 2
Wenjie Li
· 2
Yan Kang
· 2
Anbu Huang
· 1
and Jianhua Li
· 1
Gaolei Li
· 1
Hanlin Gu
· 1
Haoyang Li
· 1
Topics
Federated Learning
Privacy
Security
Adversarial Attacks