Prototyping federated learning on edge computing systems

Jianlei YANG, Yixiao DUAN, Tong QIAO, Huanyu ZHOU, Jingyuan WANG, Weisheng ZHAO

PDF(326 KB)
PDF(326 KB)
Front. Comput. Sci. ›› 2020, Vol. 14 ›› Issue (6) : 146318. DOI: 10.1007/s11704-019-9237-3
LETTER

Prototyping federated learning on edge computing systems

Author information +
History +

Cite this article

Download citation ▾
Jianlei YANG, Yixiao DUAN, Tong QIAO, Huanyu ZHOU, Jingyuan WANG, Weisheng ZHAO. Prototyping federated learning on edge computing systems. Front. Comput. Sci., 2020, 14(6): 146318 https://doi.org/10.1007/s11704-019-9237-3

References

[1]
Yang Q, Liu Y, Chen T, Tong Y. Federated machine learning: concept and applications. ACM Transactions on Intelligent Systems and Technology, 2019, 10(2): 12
CrossRef Google scholar
[2]
Andrew H, Kanishka R, Rajiv M, Swaroop R, Francoise B. Federated learning for mobile keyboard prediction. 2018, arXiv preprint arXiv: 1811.03604
[3]
Keith B, Hubert E, Wolfgang G, Dzmitry H, Alex I, Vladimir I. Towards federated learning at scale: system design. 2019, arXiv preprint arXiv: 1902.01046
[4]
Chen Y, Ning Y, Huzefa R. Asynchronous online federated learning for edge devices. 2019, arXiv preprint arXiv: 1911.02134
[5]
Sun S, Chen W, Bian J, Liu X, Liu T. Slim-DP: a multi-agent system for communication-efficient distributed deep learning. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. 2018, 721–729

RIGHTS & PERMISSIONS

2019 Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature
AI Summary AI Mindmap
PDF(326 KB)

Accesses

Citations

Detail

Sections
Recommended

/