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Rethinking the Value of Network Pruning

11 October 2018

Gao Huang

Papers citing "Rethinking the Value of Network Pruning"

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Title
EDropout: Energy-Based Dropout and Pruning of Deep Neural Networks Hojjat Salehinejad S. Valaee 59 47 0 07 Jun 2020
An Overview of Neural Network Compression James OÑeill AI4CE 160 100 0 05 Jun 2020
Pruning via Iterative Ranking of Sensitivity Statistics Stijn Verdenius M. Stol Patrick Forré AAML 82 38 0 01 Jun 2020
Feature Statistics Guided Efficient Filter Pruning Hang Li Chen Ma Wenyuan Xu Xue Liu 49 34 0 21 May 2020
BiQGEMM: Matrix Multiplication with Lookup Table For Binary-Coding-based Quantized DNNs Yongkweon Jeon Baeseong Park S. Kwon Byeongwook Kim Jeongin Yun Dongsoo Lee MQ 63 31 0 20 May 2020
Joint Multi-Dimension Pruning via Numerical Gradient Update Zechun Liu Xinming Zhang Zhiqiang Shen Zhe Li Yichen Wei Kwang-Ting Cheng Jian Sun 76 19 0 18 May 2020
Dynamic Sparsity Neural Networks for Automatic Speech Recognition Zhaofeng Wu Ding Zhao Qiao Liang Jiahui Yu Anmol Gulati Ruoming Pang 51 41 0 16 May 2020
Joint Progressive Knowledge Distillation and Unsupervised Domain Adaptation Le Thanh Nguyen-Meidine Eric Granger M. Kiran Jose Dolz Louis-Antoine Blais-Morin 78 23 0 16 May 2020
Dynamic Sparse Training: Find Efficient Sparse Network From Scratch With Trainable Masked Layers Junjie Liu Zhe Xu Runbin Shi R. Cheung Hayden Kwok-Hay So 62 122 0 14 May 2020
Binarizing MobileNet via Evolution-based Searching Hai T. Phan Zechun Liu Dang T. Huynh Marios Savvides Kwang-Ting Cheng Zhiqiang Shen 3DV MQ 92 44 0 13 May 2020
CupNet -- Pruning a network for geometric data R. Heese L. Morand Dirk Helm Michael Bortz 3DPC 15 0 0 11 May 2020
Pruning Algorithms to Accelerate Convolutional Neural Networks for Edge Applications: A Survey Jiayi Liu S. Tripathi Unmesh Kurup Mohak Shah 3DPC MedIm 71 52 0 08 May 2020
DMCP: Differentiable Markov Channel Pruning for Neural Networks Shaopeng Guo Yujie Wang Quanquan Li Junjie Yan 74 166 0 07 May 2020
Dependency Aware Filter Pruning Kai Zhao Xinyu Zhang Qi Han Ming-Ming Cheng 28 3 0 06 May 2020
Pruning artificial neural networks: a way to find well-generalizing, high-entropy sharp minima Enzo Tartaglione Andrea Bragagnolo Marco Grangetto 66 12 0 30 Apr 2020
Out-of-the-box channel pruned networks Ragav Venkatesan Gurumurthy Swaminathan Xiong Zhou Anna Luo 37 0 0 30 Apr 2020
Masking as an Efficient Alternative to Finetuning for Pretrained Language Models Mengjie Zhao Tao R. Lin Fei Mi Martin Jaggi Hinrich Schütze 77 121 0 26 Apr 2020
Computation on Sparse Neural Networks: an Inspiration for Future Hardware Fei Sun Minghai Qin Tianyun Zhang Liu Liu Yen-kuang Chen Yuan Xie 110 7 0 24 Apr 2020
Convolution-Weight-Distribution Assumption: Rethinking the Criteria of Channel Pruning Zhongzhan Huang Wenqi Shao Xinjiang Wang Liang Lin Ping Luo 75 56 0 24 Apr 2020
SIPA: A Simple Framework for Efficient Networks Gihun Lee Sangmin Bae Jaehoon Oh Seyoung Yun 19 1 0 24 Apr 2020
Non-Blocking Simultaneous Multithreading: Embracing the Resiliency of Deep Neural Networks Gil Shomron U. Weiser 47 15 0 17 Apr 2020
Training with Quantization Noise for Extreme Model Compression Angela Fan Pierre Stock Benjamin Graham Edouard Grave Remi Gribonval Hervé Jégou Armand Joulin MQ 113 246 0 15 Apr 2020
GeneCAI: Genetic Evolution for Acquiring Compact AI Mojan Javaheripi Mohammad Samragh T. Javidi F. Koushanfar 74 9 0 08 Apr 2020
Network Adjustment: Channel Search Guided by FLOPs Utilization Ratio Zhengsu Chen J. Niu Lingxi Xie Xuefeng Liu Longhui Wei Qi Tian 54 12 0 06 Apr 2020
DSA: More Efficient Budgeted Pruning via Differentiable Sparsity Allocation Xuefei Ning Tianchen Zhao Wenshuo Li Peng Lei Yu Wang Huazhong Yang 90 104 0 05 Apr 2020
Rethinking Depthwise Separable Convolutions: How Intra-Kernel Correlations Lead to Improved MobileNets D. Haase Manuel Amthor 69 136 0 30 Mar 2020
CAKES: Channel-wise Automatic KErnel Shrinking for Efficient 3D Networks Qihang Yu Yingwei Li Jieru Mei Yuyin Zhou Alan Yuille 3DPC 66 3 0 28 Mar 2020
Dynamic Narrowing of VAE Bottlenecks Using GECO and L0 Regularization Cedric De Boom Samuel T. Wauthier Tim Verbelen Bart Dhoedt DRL 35 6 0 24 Mar 2020
Steepest Descent Neural Architecture Optimization: Escaping Local Optimum with Signed Neural Splitting Lemeng Wu Mao Ye Qi Lei Jason D. Lee Qiang Liu 88 15 0 23 Mar 2020
Review of data analysis in vision inspection of power lines with an in-depth discussion of deep learning technology Xinyu Liu Xiren Miao Hao Jiang Jia Chen 55 12 0 22 Mar 2020
DP-Net: Dynamic Programming Guided Deep Neural Network Compression Dingcheng Yang Wenjian Yu Ao Zhou Haoyuan Mu G. Yao Xiaoyi Wang 37 6 0 21 Mar 2020
Verification of Neural Networks: Enhancing Scalability through Pruning Dario Guidotti Francesco Leofante Luca Pulina A. Tacchella 47 24 0 17 Mar 2020
Channel Pruning via Optimal Thresholding Yun Ye Ganmei You Jong-Kae Fwu Xia Zhu Q. Yang Yuan Zhu 47 12 0 10 Mar 2020
What is the State of Neural Network Pruning? Davis W. Blalock Jose Javier Gonzalez Ortiz Jonathan Frankle John Guttag 293 1,058 0 06 Mar 2020
Towards Practical Lottery Ticket Hypothesis for Adversarial Training Bai Li Shiqi Wang Yunhan Jia Yantao Lu Zhenyu Zhong Lawrence Carin Suman Jana AAML 142 14 0 06 Mar 2020
Pruning Filters while Training for Efficiently Optimizing Deep Learning Networks Sourjya Roy Priyadarshini Panda G. Srinivasan A. Raghunathan 3DPC VLM 70 19 0 05 Mar 2020
Cluster Pruning: An Efficient Filter Pruning Method for Edge AI Vision Applications Chinthaka Gamanayake Lahiru Jayasinghe Benny Kai Kiat Ng Chau Yuen VLM 91 47 0 05 Mar 2020
Comparing Rewinding and Fine-tuning in Neural Network Pruning Alex Renda Jonathan Frankle Michael Carbin 310 388 0 05 Mar 2020
Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection Mao Ye Chengyue Gong Lizhen Nie Denny Zhou Adam R. Klivans Qiang Liu 113 111 0 03 Mar 2020
Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs Jonathan Frankle D. Schwab Ari S. Morcos 117 143 0 29 Feb 2020
Deep Randomized Neural Networks Claudio Gallicchio Simone Scardapane OOD 102 65 0 27 Feb 2020
$Learning the mapping $\mathbf{x}\mapsto \sum_{i=1}^d x_i^2$: the cost of finding the needle in a haystack$ Learning the mapping $\mathbf{x}\mapsto \sum_{i=1}^d x_i^2$ : the cost of finding the needle in a haystack Jiefu Zhang Leonardo Zepeda-Núnez Yuan Yao Lin Lin 22 0 0 24 Feb 2020
HYDRA: Pruning Adversarially Robust Neural Networks Vikash Sehwag Shiqi Wang Prateek Mittal Suman Jana AAML 69 25 0 24 Feb 2020
The Early Phase of Neural Network Training Jonathan Frankle D. Schwab Ari S. Morcos 98 174 0 24 Feb 2020
Gradual Channel Pruning while Training using Feature Relevance Scores for Convolutional Neural Networks Sai Aparna Aketi Sourjya Roy A. Raghunathan Kaushik Roy 63 22 0 23 Feb 2020
Compressing BERT: Studying the Effects of Weight Pruning on Transfer Learning Mitchell A. Gordon Kevin Duh Nicholas Andrews VLM 93 343 0 19 Feb 2020
Identifying Critical Neurons in ANN Architectures using Mixed Integer Programming M. Elaraby Guy Wolf Margarida Carvalho 51 5 0 17 Feb 2020
DeepLight: Deep Lightweight Feature Interactions for Accelerating CTR Predictions in Ad Serving Wei Deng Junwei Pan Tian Zhou Deguang Kong Aaron Flores Guang Lin 34 4 0 17 Feb 2020
Lookahead: A Far-Sighted Alternative of Magnitude-based Pruning Sejun Park Jaeho Lee Sangwoo Mo Jinwoo Shin 65 94 0 12 Feb 2020
A study of local optima for learning feature interactions using neural networks Yangzi Guo Adrian Barbu 115 1 0 11 Feb 2020