HADFL: Heterogeneity-aware decentralized federated learning framework

J Cao, Z Lian, W Liu, Z Zhu, C Ji - 2021 58th ACM/IEEE Design …, 2021 - ieeexplore.ieee.org
Federated learning (FL) supports training models on geographically distributed devices.
However, traditional FL systems adopt a centralized synchronous strategy, putting high …
被引用次数：19 相关文章

HADFL: Heterogeneity-aware Decentralized Federated Learning Framework

J Cao, Z Lian, W Liu, Z Zhu, C Ji - 2021 58th ACM/IEEE Design …, 2021 - dl.acm.org
Federated learning (FL) supports training models on geographically distributed devices.
However, traditional FL systems adopt a centralized synchronous strategy, putting high …

HADFL: Heterogeneity-aware Decentralized Federated Learning Framework

J Cao, Z Lian, W Liu, Z Zhu, C Ji - arXiv preprint arXiv:2111.08274, 2021 - arxiv.org
Federated learning (FL) supports training models on geographically distributed devices.
However, traditional FL systems adopt a centralized synchronous strategy, putting high …

HADFL: Heterogeneity-aware Decentralized Federated Learning Framework

J Cao, Z Lian, W Liu, Z Zhu, C Ji - arXiv e-prints, 2021 - ui.adsabs.harvard.edu
Federated learning (FL) supports training models on geographically distributed devices.
However, traditional FL systems adopt a centralized synchronous strategy, putting high …