Shantian Yang

SFedHIFI: Fire Rate-Based Heterogeneous Information Fusion for Spiking Federated Learning

Spiking Federated Learning (SFL) has been widely studied with the energy efficiency of Spiking Neural Networks (SNNs). However, existing SFL methods require model homogeneity and assume all clients have sufficient computational resources, resulting in the exclusion of some resource-constrained clien