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Privacy-preserving Federated Primal-dual Learning for Non-convex and
  Non-smooth Problems with Model Sparsification
v1v2 (latest)

Privacy-preserving Federated Primal-dual Learning for Non-convex and Non-smooth Problems with Model Sparsification

IEEE Internet of Things Journal (IEEE IoT J.), 2023
30 October 2023
Yiwei Li
Chien-Wei Huang
Shuai Wang
Chong-Yung Chi
Tony Q.S. Quek
    FedML
ArXiv (abs)PDFHTML

Papers citing "Privacy-preserving Federated Primal-dual Learning for Non-convex and Non-smooth Problems with Model Sparsification"

2 / 2 papers shown
Title
Federated Learning with Enhanced Privacy via Model Splitting and Random Client Participation
Federated Learning with Enhanced Privacy via Model Splitting and Random Client Participation
Yiwei Li
Shuai Wang
Zhuojun Tian
X. Wang
Shijian Su
FedML
88
0
0
30 Sep 2025
A Multivocal Literature Review on Privacy and Fairness in Federated
  Learning
A Multivocal Literature Review on Privacy and Fairness in Federated LearningWirtschaftsinformatik (WI), 2024
Beatrice Balbierer
Lukas Heinlein
Domenique Zipperling
Niklas Kühl
123
1
0
16 Aug 2024
1