LEARNING METHOD AND LEARNING DEVICE FOR NEURAL NETWORK AT ADAPTIVE LEARNING RATE, AND TESTING METHOD AND TESTING DEVICE USING THE SAME

摘要

A method for learning a neural network by adjusting a learning rate each time when an accumulated number of iterations reaches one of a first to an n-th specific values. The method includes steps of: (a) a learning device, while increasing k from 1 to (n-1), (b1) performing a k-th learning process of repeating the learning of the neural network at a k-th learning rate by using a part of the training data while the accumulated number of iterations is greater than a (k-1)-th specific value and is equal to or less than a k-th specific value, (b2) changing a k-th gamma to a (k+1)-th gamma by referring to k-th losses of the neural network which are obtained by the k-th learning process and (ii) changing a k-th learning rate to a (k+1)-th learning rate by using the (k+1)-th gamma.