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A Closer Look at Structured Pruning for Neural Network Compression

10 October 2018

Elliot J. Crowley

Jack Turner

Amos Storkey

Michael F. P. O'Boyle

3DPC

ArXiv (abs)PDF HTML Github (141★)

Papers citing "A Closer Look at Structured Pruning for Neural Network Compression"

27 / 27 papers shown

Title
The State of Sparsity in Deep Neural Networks Trevor Gale Erich Elsen Sara Hooker 161 761 0 25 Feb 2019
Rethinking ImageNet Pre-training Kaiming He Ross B. Girshick Piotr Dollár VLM SSeg 130 1,086 0 21 Nov 2018
Rethinking the Value of Network Pruning Zhuang Liu Mingjie Sun Tinghui Zhou Gao Huang Trevor Darrell 36 1,474 0 11 Oct 2018
SNIP: Single-shot Network Pruning based on Connection Sensitivity Namhoon Lee Thalaiyasingam Ajanthan Philip Torr VLM 266 1,207 0 04 Oct 2018
DARTS: Differentiable Architecture Search Hanxiao Liu Karen Simonyan Yiming Yang 204 4,366 0 24 Jun 2018
NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications Tien-Ju Yang Andrew G. Howard Bo Chen Xiao Zhang Alec Go Mark Sandler Vivienne Sze Hartwig Adam 138 521 0 09 Apr 2018
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks Jonathan Frankle Michael Carbin 245 3,485 0 09 Mar 2018
AMC: AutoML for Model Compression and Acceleration on Mobile Devices Yihui He Ji Lin Zhijian Liu Hanrui Wang Li Li Song Han 98 1,349 0 10 Feb 2018
Residual Connections Encourage Iterative Inference Stanislaw Jastrzebski Devansh Arpit Nicolas Ballas Vikas Verma Tong Che Yoshua Bengio 57 155 0 13 Oct 2017
Learning Efficient Convolutional Networks through Network Slimming Zhuang Liu Jianguo Li Zhiqiang Shen Gao Huang Shoumeng Yan Changshui Zhang 125 2,426 0 22 Aug 2017
Learning Transferable Architectures for Scalable Image Recognition Barret Zoph Vijay Vasudevan Jonathon Shlens Quoc V. Le 186 5,607 0 21 Jul 2017
Channel Pruning for Accelerating Very Deep Neural Networks Yihui He Xiangyu Zhang Jian Sun 204 2,529 0 19 Jul 2017
Bayesian Compression for Deep Learning Christos Louizos Karen Ullrich Max Welling UQCV BDL 166 481 0 24 May 2017
In-Datacenter Performance Analysis of a Tensor Processing Unit N. Jouppi C. Young Nishant Patil David Patterson Gaurav Agrawal ... Vijay Vasudevan Richard Walter Walter Wang Eric Wilcox Doe Hyun Yoon 235 4,638 0 16 Apr 2017
Efficient Processing of Deep Neural Networks: A Tutorial and Survey Vivienne Sze Yu-hsin Chen Tien-Ju Yang J. Emer AAML 3DV 120 3,026 0 27 Mar 2017
Variational Dropout Sparsifies Deep Neural Networks Dmitry Molchanov Arsenii Ashukha Dmitry Vetrov BDL 147 831 0 19 Jan 2017
Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer Sergey Zagoruyko N. Komodakis 147 2,586 0 12 Dec 2016
Pruning Filters for Efficient ConvNets Hao Li Asim Kadav Igor Durdanovic H. Samet H. Graf 3DPC 195 3,705 0 31 Aug 2016
Learning Structured Sparsity in Deep Neural Networks W. Wen Chunpeng Wu Yandan Wang Yiran Chen Hai Helen Li 187 2,341 0 12 Aug 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 351 8,000 0 23 May 2016
Deep Roots: Improving CNN Efficiency with Hierarchical Filter Groups Yani Andrew Ioannou D. Robertson R. Cipolla A. Criminisi 80 265 0 20 May 2016
Deep Networks with Stochastic Depth Gao Huang Yu Sun Zhuang Liu Daniel Sedra Kilian Q. Weinberger 215 2,361 0 30 Mar 2016
Multi-Scale Context Aggregation by Dilated Convolutions Feng Yu V. Koltun SSeg 271 8,459 0 23 Nov 2015
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding Song Han Huizi Mao W. Dally 3DGS 263 8,859 0 01 Oct 2015
Learning both Weights and Connections for Efficient Neural Networks Song Han Jeff Pool J. Tran W. Dally CVBM 313 6,700 0 08 Jun 2015
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 251 4,681 0 21 Dec 2014
Do Deep Nets Really Need to be Deep? Lei Jimmy Ba R. Caruana 167 2,119 0 21 Dec 2013