CPC G06N 3/082 (2013.01) [G06N 3/04 (2013.01)] | 28 Claims |
1. A processor-implemented method, comprising:
determining a pruning threshold for pruning a plurality of pre-trained weights of a first artificial neural network (ANN) model based on a function of a classification loss and a regularization loss, the regularization loss comprising a count of unpruned weights;
pruning a first set of pre-trained weights, of the plurality of pre-trained weights of the first ANN model, with a first value that is less than the pruning threshold;
adjusting a second set of pre-trained weights of the plurality of pre-trained weights of the first ANN model in response to a second value of each pre-trained weight in the second set of pre-trained weights being greater than the pruning threshold; and
generating a second ANN model based on the adjusted second set of pretrained weights.
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