2018
To Prune, or Not to Prune: Exploring the Efficacy of Pruning for Model Compression
ICLR 2018workshop
Model pruning seeks to induce sparsity in a deep neural network's various connection matrices, thereby reducing the number of nonzero-valued parameters in the model. Recent reports (Han et al., 2015; Narang et al., 2017) prune deep networks at the cost of only a marginal loss in accuracy and achieve…