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Federated Learning enables mobile devices to collaboratively learn a shared inference model while keeping all the training data on a user's device, decoupling the ability to do machine learning from the need to store the data in the cloud.
K. V. Mardia and P. E. Jupp, Directional statistics . John Wiley & Sons, 2009, vol. 494
2009
Earlier work this paper cites.
A. Krizhevsky, “Learning multiple layers of features from tiny images,” Tech. Rep., 2009
2009
Earlier work this paper cites.
Y. Lyubarskii and R. Vershynin, “Uncertainty principles and vector quantization,” IEEE Transactions on Information Theory , vol. 56, no. 7, pp. 3491–3501, 2010
2010
Earlier work this paper cites.
K. J. Horadam, Hadamard matrices and their applications . Princeton university press, 2012
2012
Earlier work this paper cites.
2015
Cited alongside, same era.
2016
Cited alongside, same era.
A. T. Suresh, F. X. Yu, H. B. McMahan, and S. Kumar, “Distributed mean estimation with limited communication,” in International Conference on Machine Learning , 2017
2017
Cited alongside, same era.
K. Bonawitz, V. Ivanov, B. Kreuter, A. Marcedone, H. B. McMahan, S. Patel, D. Ramage, A. Segal, and K. Seth, “Practical secure aggregation for privacy-preserving machine learning,” in Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security . ACM, 2017, pp. 1175–1191
2017
Cited alongside, same era.
B. McMahan, E. Moore, D. Ramage, S. Hampson, and B. A. y Arcas, “Communication-efficient learning of deep networks from decentralized data,” in Artificial Intelligence and Statistics , 2017, pp. 1273–1282
2017
Later among the works it cites.
2018
Later among the works it cites.
R. Vershynin, High-dimensional probability: An introduction with applications in data science . Cambridge University Press, 2018, vol. 47
2018
Later among the works it cites.
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