Forget the Learning Rate, Decay Loss

27 Apr 2019 Jiakai Wei

In the usual deep neural network optimization process, the learning rate is the most important hyper parameter, which greatly affects the final convergence effect. The purpose of learning rate is to control the stepsize and gradually reduce the impact of noise on the network... (read more)

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