A Unified DNN Weight Pruning Framework Using Reweighted Optimization Methods

To address the large model size and intensive computation requirement of deep neural networks (DNNs), weight pruning techniques have been proposed and generally fall into two categories, i.e., static regularization-based pruning and dynamic regularization-based pruning. However, the former method cu...

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Veröffentlicht in:	2021 58th ACM/IEEE Design Automation Conference (DAC) S. 493 - 498
Hauptverfasser:	Zhang, Tianyun, Ma, Xiaolong, Zhan, Zheng, Zhou, Shanglin, Ding, Caiwen, Fardad, Makan, Wang, Yanzhi
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 05.12.2021
Schlagworte:	Computational modeling Deep learning Degradation Design automation Optimization methods Training
Online-Zugang:	Volltext
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