Pruning and Quantization for Deep Neural Network Acceleration: A Survey

24 January 2021

Papers citing "Pruning and Quantization for Deep Neural Network Acceleration: A Survey"

7 / 7 papers shown

Title
Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression Yawei Li Shuhang Gu Christoph Mayer Luc Van Gool Radu Timofte 97 176 0 19 Mar 2020
What is the State of Neural Network Pruning? Davis W. Blalock Jose Javier Gonzalez Ortiz Jonathan Frankle John Guttag 153 910 0 06 Mar 2020
Forward and Backward Information Retention for Accurate Binary Neural Networks Haotong Qin Ruihao Gong Xianglong Liu Mingzhu Shen Ziran Wei F. Yu Jingkuan Song MQ 99 268 0 24 Sep 2019
Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers Yukuan Yang Shuang Wu Lei Deng Tianyi Yan Yuan Xie Guoqi Li MQ 67 92 0 05 Sep 2019
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 924 18,450 0 17 Apr 2017
Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights Aojun Zhou Anbang Yao Yiwen Guo Lin Xu Yurong Chen MQ 271 1,002 0 10 Feb 2017
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 229 7,406 0 03 Jul 2012