Liyinglan Liu

Bridging Model Heterogeneity in Federated Learning with Group Prototypical Alignment

FedGPA is proposed, a hierarchical framework in which clients with comparable resources and identical architectures form a group and a server mediates knowledge transfer across groups of diverse models, and at its core, the lightweight, model-agnostic Aligned Co-decision (Alco) Unit aligns class-level prototypical information across groups to bridge heterogeneous architectures.