PFL-IDGAN:Personalized Federated Learning Framework Based on Interactive Dual Generative Adversarial Networks

Exploring foci of: Frontiers in artificial intelligence and applications PFL-IDGAN:Personalized Federated Learning Framework Based on Interactive Dual Generative Adversarial Networks October 2025 • Zhigang Wang, Yan Yang, Xiaochi Hou, Junfeng Zhao Federated learning (FL) enables collaborative model training without direct data exchange, promoting privacy-preserving data utilization. To address performance degradation caused by non-independent and identically distributed (non-IID) data, Personalized Federated Learning (PFL) allows each client to learn a model tailored to its local distribution. However, real-world personalized scenarios often involve not only data heterogeneity but also model heterogeneity across clients. Existing PFL methods struggle under … Open Article Page

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