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cs.LG2026
SFedHIFI: Fire Rate-Based Heterogeneous Information Fusion for Spiking Federated Learning
Ran Tao, Qiugang Zhan, Shantian Yang +3
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 a…
cs.LG2024
SFedCA: Credit Assignment-Based Active Client Selection Strategy for Spiking Federated Learning
Qiugang Zhan, Jinbo Cao, Xiurui Xie +3
Spiking federated learning is an emerging distributed learning paradigm that allows resource-constrained devices to train collaboratively at low power consumption without exchangin…