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Neural Network Compression: Difference between revisions
→Sensitivity Methods
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# Compute sensitivity for each parameter. | # Compute sensitivity for each parameter. | ||
# Delete low-saliency parameters. | # Delete low-saliency parameters. | ||
# Continue training | # Continue training to fine-tune remaining parameters. | ||
# Repeat pruning until the number of parameters is low enough or the error is too high. | |||
Sometimes, pruning can also increase accuracy and improve generalization. | Sometimes, pruning can also increase accuracy and improve generalization. | ||