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RecUP-FL: Reconciling Utility and Privacy in Federated Learning via
  User-configurable Privacy Defense

RecUP-FL: Reconciling Utility and Privacy in Federated Learning via User-configurable Privacy Defense

11 April 2023
Yue-li Cui
Syed Imran Ali Meerza
Zhuohang Li
Luyang Liu
Jiaxin Zhang
Jian-Dong Liu
    AAML
    FedML
ArXivPDFHTML

Papers citing "RecUP-FL: Reconciling Utility and Privacy in Federated Learning via User-configurable Privacy Defense"

3 / 3 papers shown
Title
Defending Against Gradient Inversion Attacks for Biomedical Images via Learnable Data Perturbation
Defending Against Gradient Inversion Attacks for Biomedical Images via Learnable Data Perturbation
Shiyi Jiang
F. Firouzi
Krishnendu Chakrabarty
AAML
MedIm
38
0
0
19 Mar 2025
Private Collaborative Edge Inference via Over-the-Air Computation
Private Collaborative Edge Inference via Over-the-Air Computation
Selim F. Yilmaz
Burak Hasircioglu
Li Qiao
Deniz Gunduz
FedML
48
0
0
30 Jul 2024
Meta Gradient Adversarial Attack
Meta Gradient Adversarial Attack
Zheng Yuan
Jie M. Zhang
Yunpei Jia
Chuanqi Tan
Tao Xue
Shiguang Shan
AAML
47
78
0
09 Aug 2021
1