Quantized Adam with Error Feedback

29 Apr 2020Congliang ChenLi ShenHaozhi HuangQi WuWei Liu

In this paper, we present a distributed variant of adaptive stochastic gradient method for training deep neural networks in the parameter-server model. To reduce the communication cost among the workers and server, we incorporate two types of quantization schemes, i.e., gradient quantization and weight quantization, into the proposed distributed Adam... (read more)

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