Astraea: Self-balancing Federated Learning for Improving Classification Accuracy of Mobile Deep Learning Applications

2 Jul 2019Moming DuanDuo LiuXianzhang ChenYujuan TanJinting RenLei QiaoLiang Liang

Federated learning (FL) is a distributed deep learning method which enables multiple participants, such as mobile phones and IoT devices, to contribute a neural network model while their private training data remains in local devices. This distributed approach is promising in the edge computing system where have a large corpus of decentralized data and require high privacy... (read more)

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