Shapley Value as Principled Metric for Structured Network Pruning

2 June 2020

Markus Gross

Papers citing "Shapley Value as Principled Metric for Structured Network Pruning"

30 / 30 papers shown

Title
Everybody Prune Now: Structured Pruning of LLMs with only Forward Passes Lucio Dery Steven Kolawole Jean-Francois Kagey Virginia Smith Graham Neubig Ameet Talwalkar 77 36 0 08 Feb 2024
Pruning by Explaining: A Novel Criterion for Deep Neural Network Pruning Seul-Ki Yeom P. Seegerer Sebastian Lapuschkin Alexander Binder Simon Wiedemann K. Müller Wojciech Samek CVBM 65 209 0 18 Dec 2019
Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask Hattie Zhou Janice Lan Rosanne Liu J. Yosinski UQCV 55 389 0 03 May 2019
Explaining Deep Neural Networks with a Polynomial Time Algorithm for Shapley Values Approximation Marco Ancona Cengiz Öztireli Markus Gross FAtt TDI 99 226 0 26 Mar 2019
Studying the Plasticity in Deep Convolutional Neural Networks using Random Pruning Deepak Mittal S. Bhardwaj Mitesh M. Khapra Balaraman Ravindran 3DPC 68 32 0 26 Dec 2018
SNIP: Single-shot Network Pruning based on Connection Sensitivity Namhoon Lee Thalaiyasingam Ajanthan Philip Torr VLM 266 1,206 0 04 Oct 2018
Layer-compensated Pruning for Resource-constrained Convolutional Neural Networks Ting-Wu Chin Cha Zhang Diana Marculescu 59 46 0 01 Oct 2018
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks Jonathan Frankle Michael Carbin 245 3,484 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
Learning Sparse Neural Networks through $L_0$ Regularization Christos Louizos Max Welling Diederik P. Kingma 433 1,147 0 04 Dec 2017
Learning Efficient Convolutional Networks through Network Slimming Zhuang Liu Jianguo Li Zhiqiang Shen Gao Huang Shoumeng Yan Changshui Zhang 125 2,424 0 22 Aug 2017
ThiNet: A Filter Level Pruning Method for Deep Neural Network Compression Jian-Hao Luo Jianxin Wu Weiyao Lin 58 1,761 0 20 Jul 2017
Channel Pruning for Accelerating Very Deep Neural Networks Yihui He Xiangyu Zhang Jian Sun 204 2,529 0 19 Jul 2017
Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Kundaje FAtt 203 3,881 0 10 Apr 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 191 6,015 0 04 Mar 2017
Training Sparse Neural Networks Suraj Srinivas Akshayvarun Subramanya R. Venkatesh Babu 142 207 0 21 Nov 2016
Pruning Filters for Efficient ConvNets Hao Li Asim Kadav Igor Durdanovic H. Samet H. Graf 3DPC 195 3,705 0 31 Aug 2016
Network Trimming: A Data-Driven Neuron Pruning Approach towards Efficient Deep Architectures Hengyuan Hu Rui Peng Yu-Wing Tai Chi-Keung Tang 75 891 0 12 Jul 2016
Not Just a Black Box: Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Shcherbina A. Kundaje FAtt 85 791 0 05 May 2016
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size F. Iandola Song Han Matthew W. Moskewicz Khalid Ashraf W. Dally Kurt Keutzer 153 7,495 0 24 Feb 2016
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding Song Han Huizi Mao W. Dally 3DGS 263 8,854 0 01 Oct 2015
Learning both Weights and Connections for Efficient Neural Networks Song Han Jeff Pool J. Tran W. Dally CVBM 313 6,694 0 08 Jun 2015
Fast ConvNets Using Group-wise Brain Damage V. Lebedev Victor Lempitsky AAML 178 449 0 08 Jun 2015
Compressing Neural Networks with the Hashing Trick Wenlin Chen James T. Wilson Stephen Tyree Kilian Q. Weinberger Yixin Chen 163 1,191 0 19 Apr 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 364 19,723 0 09 Mar 2015
Compressing Deep Convolutional Networks using Vector Quantization Yunchao Gong Liu Liu Ming Yang Lubomir D. Bourdev MQ 168 1,171 0 18 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.7K 100,479 0 04 Sep 2014
Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation Emily L. Denton Wojciech Zaremba Joan Bruna Yann LeCun Rob Fergus FAtt 177 1,693 0 02 Apr 2014
Do Deep Nets Really Need to be Deep? Lei Jimmy Ba R. Caruana 165 2,119 0 21 Dec 2013
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 312 7,316 0 20 Dec 2013