CPC G06N 3/084 (2013.01) [G06N 3/04 (2013.01)] | 20 Claims |
1. A method comprising:
determining losses of samples within an input volume that is provided to a neural network executed by a processor, during a first epoch, the losses being based on a comparison of output values of the neural network to labeled output values in a known training data set;
grouping, by the processor, the samples into subsets based on the losses;
assigning, by the processor, the subsets to operands in the neural network that represent the samples at different precisions that correspond to each of the subsets associated with a different precision; and
training the neural network by processing, by the processor, the subsets in the neural network at the different precisions during the first epoch.
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