Adaptive Gradient Methods with Dynamic Bound of Learning Rate

ICLR 2019 Liangchen LuoYuanhao XiongYan Liu

Adaptive optimization methods such as AdaGrad, RMSProp and Adam have been proposed to achieve a rapid training process with an element-wise scaling term on learning rates. Though prevailing, they are observed to generalize poorly compared with SGD or even fail to converge due to unstable and extreme learning rates... (read more)

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