AutoLR: An Evolutionary Approach to Learning Rate Policies
genetic and evolutionary computation conference, pp. 672-680, 2020.
The choice of a proper learning rate is paramount for good Artificial Neural Network training and performance. In the past, one had to rely on experience and trial-and-error to find an adequate learning rate. Presently, a plethora of state of the art automatic methods exist that make the search for a good learning rate easier. While the...More
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