LEAN: graph-based pruning for convolutional neural networks by extracting longest chains. (arXiv:2011.06923v3 [cs.LG] UPDATED)

Neural network pruning techniques can substantially reduce the computational
cost of applying convolutional neural networks (CNNs). Common pruning methods
determine which convolutional filters to remove by ranking the filters
individually, i.e., without taking into account their interdependence. In this
paper, we advocate the viewpoint that pruning should consider the
interdependence between series of consecutive operators. We propose the
LongEst-chAiN (LEAN) method that prunes CNNs by using graph-based algorithms to
select relevant chains of convolutions. A CNN is interpreted as a …

arxiv convolutional neural networks graph graph-based lean lg networks neural networks pruning