Recently, over-parameterized deep networks, with increasingly more network parameters
than training samples, have dominated the performances of modern machine learning …

Abstract Spiking Neural Networks (SNNs) have recently emerged as a new generation of
low-power deep neural networks, which is suitable to be implemented on low-power …

This article does not propose any novel algorithm or new hardware for sparsity. Instead, it
aims to serve the" common good" for the increasingly prosperous Sparse Neural Network …

The rapid development of large-scale deep learning models questions the affordability of
hardware platforms, which necessitates the pruning to reduce their computational and …