Lorenzo Sciandra

Simplifying Neural Networks During Training

This work proposes an NC-inspired training framework for simplifying deep networks during training, monitoring representation dynamics through the Inverse Fisher Criterion to identify both the split point between feature extraction and classification and the training stage at which simplification becomes viable.