Web: http://arxiv.org/abs/2110.00532

June 24, 2022, 1:11 a.m. | Belhal Karimi, Ping Li, Xiaoyun Li

cs.LG updates on arXiv.org arxiv.org

In the emerging paradigm of Federated Learning (FL), large amount of clients
such as mobile devices are used to train possibly high-dimensional models on
their respective data. Combining (dimension-wise) adaptive gradient methods
(e.g. Adam, AMSGrad) with FL has been an active direction, which is shown to
outperform traditional SGD based FL in many cases. In this paper, we focus on
the problem of training federated deep neural networks, and propose a novel FL
framework which further introduces layer-wise adaptivity to …

arxiv federated learning learning lg

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