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Prototyping federated learning on edge computing systems

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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

    Article  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

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Acknowledgements

Prof. Yang’s work was supported in part by the National Natural Science Foundation of China (Grant No. 61602022), State Key Laboratory of Software Development Environment (SKLSDE-2018ZX-07), CCF-Tencent IAGR20180101 and the International Collaboration Project (B16001). Prof. Wang’s work was partially supported by the National Key R&D Program of China (2019YFB2101804) and the National Natural Science Foundation of China (Grant No. 61572059).

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Correspondence to Jianlei Yang.

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Yang, J., Duan, Y., Qiao, T. et al. Prototyping federated learning on edge computing systems. Front. Comput. Sci. 14, 146318 (2020). https://doi.org/10.1007/s11704-019-9237-3

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  • DOI: https://doi.org/10.1007/s11704-019-9237-3

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