PracMHBench: Re-evaluating Model-Heterogeneous Federated Learning Based on Practical Edge Device Constraints

Federating heterogeneous models on edge devices with diverse resource constraints has been a notable trend in recent years. Compared to traditional federated learning (FL) that assumes an identical model architecture to cooperate, model-heterogeneous FL is more practical and flexible since the model...

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Veröffentlicht in:	2025 62nd ACM/IEEE Design Automation Conference (DAC) S. 1 - 7
Hauptverfasser:	Guo, Yuanchun, Liu, Bingyan, Sha, Yulong, Xian, Zhensheng
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 22.06.2025
Schlagworte:	Analytical models Classification algorithms Data models Design automation Federated learning Model Heterogeneity Performance evaluation Platform Statistical analysis
Online-Zugang:	Volltext
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