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cs.GT2024
A Game-Theoretic Framework for Privacy-Aware Client Sampling in Federated Learning
Wenhao Yuan, Xuehe Wang
This paper aims to design a Privacy-aware Client Sampling framework in Federated learning, named FedPCS, to tackle the heterogeneous client sampling issues and improve model perfor…
cs.GT2024
QI-DPFL: Quality-Aware and Incentive-Boosted Federated Learning with Differential Privacy
Wenhao Yuan, Xuehe Wang
Federated Learning (FL) has increasingly been recognized as an innovative and secure distributed model training paradigm, aiming to coordinate multiple edge clients to collaborativ…