Accelerating Federated Learning via Momentum Gradient Descent

8 Oct 2019Wei LiuLi ChenYunfei ChenWenyi Zhang

Federated learning (FL) provides a communication-efficient approach to solve machine learning problems concerning distributed data, without sending raw data to a central server. However, existing works on FL only utilize first-order gradient descent (GD) and do not consider the preceding iterations to gradient update which can potentially accelerate convergence... (read more)

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