SeReNe: Sensitivity based Regularization of Neurons for Structured Sparsity in Neural Networks

7 February 2021

Papers citing "SeReNe: Sensitivity based Regularization of Neurons for Structured Sparsity in Neural Networks"

26 / 26 papers shown

Title
Playing the Lottery With Concave Regularizers for Sparse Trainable Neural Networks Giulia Fracastoro Sophie M. Fosson Andrea Migliorati G. Calafiore 165 1 0 19 Jan 2025
Pruning artificial neural networks: a way to find well-generalizing, high-entropy sharp minima Enzo Tartaglione Andrea Bragagnolo Marco Grangetto 58 12 0 30 Apr 2020
Channel Pruning via Automatic Structure Search Mingbao Lin Rongrong Ji Yuxin Zhang Baochang Zhang Yongjian Wu Yonghong Tian 88 243 0 23 Jan 2020
Pruning from Scratch Yulong Wang Xiaolu Zhang Lingxi Xie Jun Zhou Hang Su Bo Zhang Xiaolin Hu 58 194 0 27 Sep 2019
Post-synaptic potential regularization has potential Enzo Tartaglione Daniele Perlo Marco Grangetto BDL AAML 48 6 0 19 Jul 2019
Learning Sparse Networks Using Targeted Dropout Aidan Gomez Ivan Zhang Siddhartha Rao Kamalakara Divyam Madaan Kevin Swersky Y. Gal Geoffrey E. Hinton 71 98 0 31 May 2019
The State of Sparsity in Deep Neural Networks Trevor Gale Erich Elsen Sara Hooker 161 758 0 25 Feb 2019
Learning Sparse Neural Networks via Sensitivity-Driven Regularization Enzo Tartaglione S. Lepsøy Attilio Fiandrotti Gianluca Francini 53 71 0 28 Oct 2018
SNIP: Single-shot Network Pruning based on Connection Sensitivity Namhoon Lee Thalaiyasingam Ajanthan Philip Torr VLM 257 1,205 0 04 Oct 2018
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks Jonathan Frankle Michael Carbin 233 3,473 0 09 Mar 2018
Learning Sparse Neural Networks through $L_0$ Regularization Christos Louizos Max Welling Diederik P. Kingma 430 1,144 0 04 Dec 2017
To prune, or not to prune: exploring the efficacy of pruning for model compression Michael Zhu Suyog Gupta 194 1,276 0 05 Oct 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 283 8,883 0 25 Aug 2017
Empirical Analysis of the Hessian of Over-Parametrized Neural Networks Levent Sagun Utku Evci V. U. Güney Yann N. Dauphin Léon Bottou 54 418 0 14 Jun 2017
Soft Weight-Sharing for Neural Network Compression Karen Ullrich Edward Meeds Max Welling 167 417 0 13 Feb 2017
Variational Dropout Sparsifies Deep Neural Networks Dmitry Molchanov Arsenii Ashukha Dmitry Vetrov BDL 141 830 0 19 Jan 2017
Dynamic Network Surgery for Efficient DNNs Yiwen Guo Anbang Yao Yurong Chen 81 1,059 0 16 Aug 2016
Learning Structured Sparsity in Deep Neural Networks W. Wen Chunpeng Wu Yandan Wang Yiran Chen Hai Helen Li 178 2,339 0 12 Aug 2016
Quantized Convolutional Neural Networks for Mobile Devices Jiaxiang Wu Cong Leng Yuhang Wang Qinghao Hu Jian Cheng MQ 85 1,166 0 21 Dec 2015
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,020 0 10 Dec 2015
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks Nicolas Papernot Patrick McDaniel Xi Wu S. Jha A. Swami AAML 102 3,072 0 14 Nov 2015
Learning both Weights and Connections for Efficient Neural Networks Song Han Jeff Pool J. Tran W. Dally CVBM 313 6,681 0 08 Jun 2015
Variational Dropout and the Local Reparameterization Trick Diederik P. Kingma Tim Salimans Max Welling BDL 226 1,514 0 08 Jun 2015
Fast ConvNets Using Group-wise Brain Damage V. Lebedev Victor Lempitsky AAML 175 449 0 08 Jun 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 362 19,660 0 09 Mar 2015
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.6K 100,386 0 04 Sep 2014