Learning Sparse Neural Networks via Sensitivity-Driven Regularization

NeurIPS 2018 Enzo TartaglioneSkjalg LepsøyAttilio FiandrottiGianluca Francini

The ever-increasing number of parameters in deep neural networks poses challenges for memory-limited applications. Regularize-and-prune methods aim at meeting these challenges by sparsifying the network weights... (read more)

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