Ze-Li Guan

DASFL: Dynamic Adaptive Split Federated Learning for Heterogeneous Clients

Split Federated Learning (SFL) has emerged as a pivotal paradigm for privacy-preserving distributed training on resource-constrained edge devices by partitioning neural networks between clients and a server. A critical design choice in SFL is the split layer, which determines the computation distribution and the semant...