Adam算法和Learning rate decay Adam算法. Adam算法可以加快深度神经网络的训练的速度，它实际上是结合了exponentially weighted average算法和RMSprop算法，实际训练过程如下图所示：
The objective was to study the affect of flue gas temperature and moisture, (relative humidity, There is little support from the experimental data to indicate that this rate of increase will subside. Carlfjord, Adam; Gustavsson, Henrik The thermal decomposition of methyl and ethyl formates has been extensively studied
2. tf.train.exponential_decay 사용법. There is absolutely no reason why Adam and learning rate decay can't be used together. Note that in the paper they use the standard decay tricks for proof of convergence. If you don't want to try that, then you can switch from Adam to SGD with decay in the middle of learning, as done for example in Google's NMT paper.
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Diao, M., Leonard, D., & Sing, T. F. (2017).
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if self.initial_decay > 0: lr = lr * (1. / (1. + self.decay * K.cast(self.iterations,K.dtype(self.decay)))) 写为数学表达式的形式为：.
learning rate decay在训练神经网络的时候，通常在训练刚开始的时候使用较大的learning rate， 随着训练的进行，我们会慢慢的减小learning rate。对于这种常用的训练策略，tensorflow 也提供了相应的API让我们可以更简单的将这个方法应用到我们训练网络的过程中。
Hello, I am waiting to use some modified DeepSpeech code on a GPU and wanted to know if anyone has implemented learning rate decay to the Adam Optimizer already before I begin training. Does anyone have reasons they wouldn’t want to do this? My code block is below.
+ self.decay * K.cast(self.iterations,K.dtype(self.decay)))) 写为数学表达式的形式为：. 为了更好的观察学习率的衰减情况，我们将学习率lr的衰减过程画出来，lr取0.01，decay取0.01. lr=0.01,decacy=0.0001,iterations=500. Adam class.
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2019年10月24日 Momentum.Optimizer需要配合lr decay； 选用tf.train.Adam.Optimizer不需要lr decay。 但是关于Adam是否需要做learning rate decay有很多说法
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