Learning Weight Sensitivity from Entropy

Novena Agnes

Keywords: Machine Learning, Network Optimization

Abstract: Multiple network pruning methods have used connection sensitivity of each weight to prune their network. This paper proposes a meta-learning approach to learn sensitivity of weights based on their entropy, or change, during the training phase. We have experimentally shown the validity of such an approach.