HybridCom: Improve Federated Learning Efficiency on Unstable Data
ICC（2024）
关键词
Federated Learning,Data Distribution,Changes In Distribution,Global Model,Data Privacy,Global Data,Global Distribution,Communication Resources,Client-side,Advances In Recent Years,Client Data,Federated Learning Framework,Client Participation,Federation,Gaussian Noise,Random Selection,Average Accuracy,Kernel Function,Changes In Data,Updated Model,Global Gradient,Server Side,Probability Of Participation,Limited Communication Resources,Inference Accuracy,Communication Overhead,Noise Intensity,Global Update,Absolute Indication,Concept Drift
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