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Pruning has become a very powerful and effective technique to compress and accelerate modern neural networks.
Optimal brain damage
Yann LeCun, John S Denker, and Sara A Solla · 1990
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Second order derivatives for network pruning: Optimal brain surgeon
Babak Hassibi and David G Stork · 1993
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Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Speech recognition with deep recurrent neural networks
Alex Graves, Abdel-rahman Mohamed, and Geoffrey Hinton · 2013
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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Text understanding from scratch
Xiang Zhang and Yann LeCun · 2015
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Learning both weights and connections for efficient neural network
Song Han, Jeff Pool, John Tran, and William Dally · 2015
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Song Han, Huizi Mao, and William J Dally · 2015
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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Deep predictive coding networks for video prediction and unsupervised learning
William Lotter, Gabriel Kreiman, and David Cox · 2016
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Pruning filters for efficient convnets
Hao Li, Asim Kadav, Igor Durdanovic, Hanan Samet, and Hans Peter Graf · 2016
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Rethinking the inception architecture for computer vision
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, and Zbigniew Wojna · 2016
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Fast convnets using group-wise brain damage
Vadim Lebedev and Victor Lempitsky · 2016
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Learning structured sparsity in deep neural networks
Wei Wen, Chunpeng Wu, Yandan Wang, Yiran Chen, and Hai Li · 2016
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Dynamic network surgery for efficient dnns
Yiwen Guo, Anbang Yao, and Yurong Chen · 2016
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Eie: efficient inference engine on compressed deep neural network
Song Han, Xingyu Liu, Huizi Mao, Jing Pu, Ardavan Pedram, Mark A Horowitz, and William J Dally · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Channel pruning for accelerating very deep neural networks
Yihui He, Xiangyu Zhang, and Jian Sun · 2017
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Learning efficient convolutional networks through network slimming
Zhuang Liu, Jianguo Li, Zhiqiang Shen, Gao Huang, Shoumeng Yan, and Changshui Zhang · 2017
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Net-trim: Convex pruning of deep neural networks with performance guarantee
Alireza Aghasi, Afshin Abdi, Nam Nguyen, and Justin Romberg · 2017
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Thinet: A filter level pruning method for deep neural network compression
Jian-Hao Luo, Jianxin Wu, and Weiyao Lin · 2017
Cited alongside, same era.
Exploring the granularity of sparsity in convolutional neural networks
Huizi Mao, Song Han, Jeff Pool, Wenshuo Li, Xingyu Liu, Yu Wang, and William J Dally · 2017
Discrimination-aware channel pruning for deep neural networks
Zhuangwei Zhuang, Mingkui Tan, Bohan Zhuang, Jing Liu, Yong Guo, Qingyao Wu, Junzhou Huang, and Jinhui Zhu · 2018
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Acnet: Strengthening the kernel skeletons for powerful cnn via asymmetric convolution blocks
Xiaohan Ding, Yuchen Guo, Guiguang Ding, and Jungong Han · 2019
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Structured pruning for efficient convnets via incremental regularization
Huan Wang, Qiming Zhang, Yuehai Wang, Lu Yu, and Haoji Hu · 2019
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Towards optimal structured cnn pruning via generative adversarial learning
Shaohui Lin, Rongrong Ji, Chenqian Yan, Baochang Zhang, Liujuan Cao, Qixiang Ye, Feiyue Huang, and David Doermann · 2019
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Structured pruning of neural networks with budget-aware regularization
Carl Lemaire, Andrew Achkar, and Pierre-Marc Jodoin · 2019
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Cited alongside, same era.
Shift: A zero flop, zero parameter alternative to spatial convolutions
Bichen Wu, Alvin Wan, Xiangyu Yue, Peter Jin, Sicheng Zhao, Noah Golmant, Amir Gholaminejad, Joseph Gonzalez, and Kurt Keutzer · 2017
Cited alongside, same era.
More is less: A more complicated network with less inference complexity
Xuanyi Dong, Junshi Huang, Yi Yang, and Shuicheng Yan · 2017
Cited alongside, same era.
Rethinking the value of network pruning
Zhuang Liu, Mingjie Sun, Tinghui Zhou, Gao Huang, and Trevor Darrell · 2018
Cited alongside, same era.
Frequency-domain dynamic pruning for convolutional neural networks
Zhenhua Liu, Jizheng Xu, Xiulian Peng, and Ruiqin Xiong · 2018
Cited alongside, same era.
Accelerator-aware pruning for convolutional neural networks
Hyeong-Ju Kang · 2018
Cited alongside, same era.
Nisp: Pruning networks using neuron importance score propagation
Ruichi Yu, Ang Li, Chun-Fu Chen, Jui-Hsin Lai, Vlad I Morariu, Xintong Han, Mingfei Gao, Ching-Yung Lin, and Larry S Davis · 2018
Cited alongside, same era.
Gate decorator: Global filter pruning method for accelerating deep convolutional neural networks
Zhonghui You, Kun Yan, Jinmian Ye, Meng Ma, and Ping Wang · 2019
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Full-stack filters to build minimum viable cnns
Kai Han, Yunhe Wang, Yixing Xu, Chunjing Xu, Dacheng Tao, and Chang Xu · 2019
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Towards efficient model compression via learned global ranking
Ting Wu Chin, Ruizhou Ding, Cha Zhang, and Diana Marculescu · 2019
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Super sparse convolutional neural networks
Yao Lu, G. Lu, Bob Zhang, Yuanrong Xu, and Jinxing Li · 2019
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Centripetal sgd for pruning very deep convolutional networks with complicated structure
Xiaohan Ding, Guiguang Ding, Yuchen Guo, and Jungong Han · 2019
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Filter pruning via geometric median for deep convolutional neural networks acceleration
Yang He, Ping Liu, Ziwei Wang, Zhilan Hu, and Yi Yang · 2019
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Network pruning via transformable architecture search
Xuanyi Dong and Yi Yang · 2019
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Soft threshold weight reparameterization for learnable sparsity
Aditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain, Sham Kakade, and Ali Farhadi · 2020
Closest in time.
Soft threshold weight reparameterization for learnable sparsity
Aditya Kusupati, V. Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain, Sham M. Kakade, and Ali Farhadi · 2020
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Group sparsity: The hinge between filter pruning and decomposition for network compression
Yawei Li, Shuhang Gu, Christoph Mayer, Luc Van Gool, and Radu Timofte · 2020
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Hrank: Filter pruning using high-rank feature map
Mingbao Lin, Rongrong Ji, Yan Wang, Yichen Zhang, Baochang Zhang, Yonghong Tian, and Ling Shao · 2020
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Dmcp: Differentiable markov channel pruning for neural networks
Shaopeng Guo, Yujie Wang, Quanquan Li, and Junjie Yan · 2020
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