TRAINING A NEURAL NETWORK

Abstract: a computer implemented method of training a neural network configured to combine a set of coefficients with respective input data values. so as to train a test implementation of the neural network, sparsity is applied to one or more of the coefficients according to a sparsity parameter, the sparsity parameter indicating a level of sparsity to be applied to the set of coefficients; the test implementation of the neural network is operated on training input data using the coefficients so as to form training output data; in dependence on the training output data, assessing the accuracy of the neural network; the sparsity parameter is updated in dependence on the accuracy of the neural network; and a runtime implementation of the neural network is configured in dependence on the updated sparsity parameter.

Inventor(s): Muhammad Asad, Elia Condorelli, Cagatay Dikici

CPC Classification: G06N3/084 (Backpropagation, e.g. using gradient descent)

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