HADFL: Heterogeneity-aware Decentralized Federated Learning Framework

Federated learning (FL) supports training models on geographically distributed devices. However, traditional FL systems adopt a centralized synchronous strategy, putting high communication pressure and model generalization challenge. Existing optimizations on FL either fail to speedup training on he...

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Vydané v:	2021 58th ACM/IEEE Design Automation Conference (DAC) s. 1 - 6
Hlavní autori:	Cao, Jing, Lian, Zirui, Liu, Weihong, Zhu, Zongwei, Ji, Cheng
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 05.12.2021
Predmet:	Collaborative work Computational modeling Data models Design automation Distributed Training Federated Learning Heterogeneous Computing Heterogeneous networks Machine Learning Performance evaluation Training
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