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Learning to Prune Deep Neural Networks via Layer-wise Optimal Brain Surgeon

22 May 2017

Papers citing "Learning to Prune Deep Neural Networks via Layer-wise Optimal Brain Surgeon"

50 / 275 papers shown

Title
Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Pruned Neural Networks Shuai Zhang Meng Wang Sijia Liu Pin-Yu Chen Jinjun Xiong UQCV MLT 142 13 0 12 Oct 2021
Deep Neural Compression Via Concurrent Pruning and Self-Distillation J. Ó. Neill Sourav Dutta H. Assem VLM 91 5 0 30 Sep 2021
Neural network relief: a pruning algorithm based on neural activity Aleksandr Dekhovich David Tax M. Sluiter Miguel A. Bessa 173 12 0 22 Sep 2021
Pruning with Compensation: Efficient Channel Pruning for Deep Convolutional Neural Networks Zhouyang Xie Yan Fu Sheng-Zhao Tian Junlin Zhou Duanbing Chen 3DV 76 0 0 31 Aug 2021
GRIM: A General, Real-Time Deep Learning Inference Framework for Mobile Devices based on Fine-Grained Structured Weight Sparsity Wei Niu Zhengang Xiaolong Ma Zhaoyang Han Gang Zhou Xuehai Qian Xue Lin Yanzhi Wang Bin Ren 78 20 0 25 Aug 2021
Achieving on-Mobile Real-Time Super-Resolution with Neural Architecture and Pruning Search Zheng Zhan Yifan Gong Pu Zhao Geng Yuan Wei Niu ... Malith Jayaweera David Kaeli Bin Ren Xue Lin Yanzhi Wang SupR 115 51 0 18 Aug 2021
Group Fisher Pruning for Practical Network Compression Liyang Liu Shilong Zhang Zhanghui Kuang Aojun Zhou Jingliang Xue Xinjiang Wang Yimin Chen Wenming Yang Q. Liao Wayne Zhang 136 170 0 02 Aug 2021
Experiments on Properties of Hidden Structures of Sparse Neural Networks Julian Stier Harsh Darji Michael Granitzer 63 3 0 27 Jul 2021
Privacy Vulnerability of Split Computing to Data-Free Model Inversion Attacks Xin Dong Hongxu Yin J. Álvarez Jan Kautz Pavlo Molchanov H. T. Kung MIACV 171 11 0 13 Jul 2021
M-FAC: Efficient Matrix-Free Approximations of Second-Order Information Elias Frantar Eldar Kurtic Dan Alistarh 228 60 0 07 Jul 2021
Universal approximation and model compression for radial neural networks I. Ganev Twan van Laarhoven Robin Walters 172 10 0 06 Jul 2021
Connectivity Matters: Neural Network Pruning Through the Lens of Effective Sparsity Artem Vysogorets Julia Kempe 159 24 0 05 Jul 2021
Learned Token Pruning for Transformers Sehoon Kim Sheng Shen D. Thorsley A. Gholami Woosuk Kwon Joseph Hassoun Kurt Keutzer 135 174 0 02 Jul 2021
Analytic Insights into Structure and Rank of Neural Network Hessian Maps Sidak Pal Singh Gregor Bachmann Thomas Hofmann FAtt 133 40 0 30 Jun 2021
AC/DC: Alternating Compressed/DeCompressed Training of Deep Neural Networks Alexandra Peste Eugenia Iofinova Adrian Vladu Dan Alistarh AI4CE 500 76 0 23 Jun 2021
CompConv: A Compact Convolution Module for Efficient Feature Learning Chen Zhang Yinghao Xu Yujun Shen VLM SSL 83 10 0 19 Jun 2021
Efficient Deep Learning: A Survey on Making Deep Learning Models Smaller, Faster, and Better Gaurav Menghani VLM MedIm 201 448 0 16 Jun 2021
Efficient Micro-Structured Weight Unification and Pruning for Neural Network Compression Sheng Lin Wei Jiang Wei Wang Kaidi Xu Yanzhi Wang Shan Liu Songnan Li 63 1 0 15 Jun 2021
The Flip Side of the Reweighted Coin: Duality of Adaptive Dropout and Regularization Daniel LeJeune Hamid Javadi Richard G. Baraniuk 99 8 0 14 Jun 2021
Dynamic Sparse Training for Deep Reinforcement Learning Ghada Sokar Elena Mocanu Decebal Constantin Mocanu Mykola Pechenizkiy Peter Stone 196 64 0 08 Jun 2021
Can Subnetwork Structure be the Key to Out-of-Distribution Generalization? Dinghuai Zhang Kartik Ahuja Yilun Xu Yisen Wang Aaron Courville OOD 137 103 0 05 Jun 2021
1xN Pattern for Pruning Convolutional Neural Networks Mingbao Lin Yu-xin Zhang Yuchao Li Bohong Chen Yong Li Mengdi Wang Shen Li Yonghong Tian Rongrong Ji 3DPC 205 46 0 31 May 2021
LEAP: Learnable Pruning for Transformer-based Models Z. Yao Xiaoxia Wu Linjian Ma Sheng Shen Kurt Keutzer Michael W. Mahoney Yuxiong He 107 7 0 30 May 2021
Stealthy Backdoors as Compression Artifacts Yulong Tian Fnu Suya Fengyuan Xu David Evans 124 26 0 30 Apr 2021
Neural Mean Discrepancy for Efficient Out-of-Distribution Detection Xin Dong Junfeng Guo Ang Li W. Ting Cong Liu H. T. Kung OODD 187 65 0 23 Apr 2021
Scaling Up Exact Neural Network Compression by ReLU Stability Thiago Serra Xin Yu Abhinav Kumar Srikumar Ramalingam 110 26 0 15 Feb 2021
ChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations Rishabh Tiwari Udbhav Bamba Arnav Chavan D. K. Gupta 97 33 0 14 Feb 2021
BRECQ: Pushing the Limit of Post-Training Quantization by Block ReconstructionInternational Conference on Learning Representations (ICLR), 2025 Yuhang Li Yazhe Niu Xu Tan Yang Yang Peng Hu Tao Gui F. Yu Wei Wang Shi Gu MQ 252 492 0 10 Feb 2021
RANP: Resource Aware Neuron Pruning at Initialization for 3D CNNsInternational Conference on 3D Vision (3DV), 2025 Zhiwei Xu Thalaiyasingam Ajanthan Vibhav Vineet Leonid Sigal 135 3 0 09 Feb 2021
A Deeper Look into Convolutions via Eigenvalue-based Pruning Ilke Çugu Emre Akbas FAtt 95 1 0 04 Feb 2021
Network Automatic Pruning: Start NAP and Take a Nap Wenyuan Zeng Yuwen Xiong R. Urtasun 70 9 0 17 Jan 2021
The Role of Regularization in Shaping Weight and Node Pruning Dependency and Dynamics Yael Ben-Guigui Jacob Goldberger Tammy Riklin-Raviv 114 0 0 07 Dec 2020
Rethinking Weight Decay For Efficient Neural Network Pruning Hugo Tessier Vincent Gripon Mathieu Léonardon M. Arzel T. Hannagan David Bertrand 155 28 0 20 Nov 2020
MixMix: All You Need for Data-Free Compression Are Feature and Data MixingIEEE International Conference on Computer Vision (ICCV), 2023 Yuhang Li Feng Zhu Yazhe Niu Mingzhu Shen Xin Dong F. Yu Shaoqing Lu Shi Gu MQ 110 47 0 19 Nov 2020
Layer-Wise Data-Free CNN Compression Maxwell Horton Yanzi Jin Ali Farhadi Mohammad Rastegari MQ 95 18 0 18 Nov 2020
Using noise to probe recurrent neural network structure and prune synapses Eli Moore Rishidev Chaudhuri 76 6 0 14 Nov 2020
Methods for Pruning Deep Neural Networks S. Vadera Salem Ameen 3DPC 126 143 0 31 Oct 2020
Permute, Quantize, and Fine-tune: Efficient Compression of Neural NetworksComputer Vision and Pattern Recognition (CVPR), 2025 Julieta Martinez Jashan Shewakramani Ting Liu Ioan Andrei Bârsan Wenyuan Zeng R. Urtasun MQ 170 31 0 29 Oct 2020
Data Agnostic Filter Gating for Efficient Deep Networks Xiu Su Shan You Tao Huang Hongyan Xu Haiwei Yang Chao Qian Changshui Zhang Chang Xu 84 10 0 28 Oct 2020
PHEW: Constructing Sparse Networks that Learn Fast and Generalize Well without Training DataInternational Conference on Machine Learning (ICML), 2024 S. M. Patil C. Dovrolis 177 22 0 22 Oct 2020
Layer-adaptive sparsity for the Magnitude-based PruningInternational Conference on Learning Representations (ICLR), 2025 Jaeho Lee Sejun Park Sangwoo Mo SungSoo Ahn Jinwoo Shin 129 228 0 15 Oct 2020
Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot Jingtong Su Yihang Chen Tianle Cai Tianhao Wu Ruiqi Gao Liwei Wang Jason D. Lee 119 86 0 22 Sep 2020
Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning Bingbing Li Zhenglun Kong Tianyun Zhang Ji Li Hao Sun Hang Liu Caiwen Ding VLM 297 65 0 17 Sep 2020
CNNPruner: Pruning Convolutional Neural Networks with Visual Analytics Guan Li Junpeng Wang Han-Wei Shen Kaixin Chen Guihua Shan Zhonghua Lu AAML 76 48 0 08 Sep 2020
Training Sparse Neural Networks using Compressed Sensing Jonathan W. Siegel Jianhong Chen Pengchuan Zhang Jinchao Xu 112 5 0 21 Aug 2020
Data-Independent Structured Pruning of Neural Networks via Coresets Ben Mussay Dan Feldman Samson Zhou Vladimir Braverman Margarita Osadchy 100 26 0 19 Aug 2020
Towards Modality Transferable Visual Information Representation with Optimal Model Compression Rongqun Lin Linwei Zhu Shiqi Wang Sam Kwong 92 2 0 13 Aug 2020
Communication-Efficient Federated Learning via Optimal Client Sampling Mónica Ribero H. Vikalo FedML 139 101 0 30 Jul 2020
Embedding Differentiable Sparsity into Deep Neural Network Yongjin Lee 39 0 0 23 Jun 2020
Exploring Weight Importance and Hessian Bias in Model Pruning Mingchen Li Yahya Sattar Christos Thrampoulidis Samet Oymak 118 4 0 19 Jun 2020