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参考资料:
Tensorflow官网教程:https://www.tensorflow/federated/
联邦学(federated learning)习生态:https://cn.fedai
federated learning/联邦学习:https://daiwk.github.io/posts/dl-federated-learning.html

Federated Learning的提出

Federated Learning是由Google在2016年提出,16年期间Google有关Federated Learning提出的文章为以下3个:

Jakub Konecný, H. Brendan McMahan, Daniel Ramage, and Peter Richtárik. 2016. Federated Optimization: Distributed Machine Learning for On-Device Intelligence. CoRR abs/1610.02527 (2016). arXiv:1610.02527 http://arxiv/abs/1610. 02527

Jakub Konecný, H. Brendan McMahan, Felix X. Yu, Peter Richtárik, Ananda Theertha Suresh, and Dave Bacon. 2016. Federated Learning: Strategies for Improving Communication Efficiency. CoRR abs/1610.05492 (2016). arXiv:1610.05492 http://arxiv/abs/1610.05492

H. Brendan McMahan, Eider Moore, Daniel Ramage, a

本文标签: 联邦FederatedLearning