Prototyping federated learning on edge computing systems

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

Front. Comput. Sci. ›› 2020, Vol. 14 ›› Issue (6) : 146318

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Front. Comput. Sci. ›› 2020, Vol. 14 ›› Issue (6) : 146318 DOI: 10.1007/s11704-019-9237-3
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Prototyping federated learning on edge computing systems

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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 DOI:10.1007/s11704-019-9237-3

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References

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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

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Andrew H, Kanishka R, Rajiv M, Swaroop R, Francoise B. Federated learning for mobile keyboard prediction. 2018, arXiv preprint arXiv: 1811.03604

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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

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Chen Y, Ning Y, Huzefa R. Asynchronous online federated learning for edge devices. 2019, arXiv preprint arXiv: 1911.02134

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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

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