FairDPFL-SCS: Fair Dynamic Personalized Federated Learning with strategic client selection for improved accuracy and fairness

Fahad Sabah, Yuwen Chen, Zhen Yang, Abdul Raheem, Muhammad Azam, Nadeem Ahmad, Raheem Sarwar

Abstract: Highlights•A Fair Dynamic Personalized Federated Learning with Strategic Client Selection (FairDPFL-SCS) is proposed.•This research work provides a comprehensive analysis and categorization of related works with their pros and cons.•The FairDPFL-SCS model is a lightweight dynamic model which can be used for greater practicability.•This research work addresses non-IIDness issue in PFL with improved fairness and accuracy.