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Dynamic Runtime Feature Map Pruning

Published in arXiv (Cornell University) • Dec 24, 2018
NobleIDNI9P87W30R36S44
Authors:
Tailin Liang
,
Lei Wang
,
Shi Shao-bo

Abstract

High bandwidth requirements are an obstacle for accelerating the training and inference of deep neural networks. Most previous research focuses on reducing the size of kernel maps for inference. We analyze parameter sparsity of six popular convolutional neural networks - AlexNet, MobileNet, ResNet-5...

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