Convergence-Privacy-Fairness Trade-Off in Personalized Federated Learning

Convergence-Privacy-Fairness Trade-Off in Personalized Federated Learning

Personalized federated learning (PFL), e.g., the renowned Ditto, strikes a balance between personalization and generalization by conducting federated learning (FL) to guide personalized learning (PL). While FL is unaffected by personalized model training, in Ditto, PL depends on the outcome of the F...

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Bibliographic Details
Main Authors: Xiyu Zhao, Qimei Cui, Weicai Li, Wei Ni, Ekram Hossain, Quan Z. Sheng, Xiaofeng Tao, Ping Zhang
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Transactions on Machine Learning in Communications and Networking
Subjects:
Personalized federated learning
differential privacy
convergence
fairness
Online Access:https://ieeexplore.ieee.org/document/10838599/
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