Ferhat Bozkurt

FedMCP++: Integrating Modular Expert Heads with Prototype-Guided Contrastive Distillation for Wireless Personalized Federated Learning

FedMCP++, a modular and communication-efficient personalized FL framework in which every client owns a complete private model—a lightweight convolutional backbone with a private expert head—and collaboration is carried out entirely through knowledge exchange rather than parameter exchange, is introduced.