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Variational Dropout Sparsifies Deep Neural Networks

19 January 2017

Dmitry Vetrov

Papers citing "Variational Dropout Sparsifies Deep Neural Networks"

32 / 32 papers shown

Title
Task-Oriented Communications for Visual Navigation with Edge-Aerial Collaboration in Low Altitude Economy Zhengru Fang Zhenghao Liu Jingjing Wang Senkang Hu Yu Guo Yiqin Deng Yuguang Fang 54 1 0 25 Apr 2025
CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks Kaizheng Wang Keivan K1 Shariatmadar Shireen Kudukkil Manchingal Fabio Cuzzolin David Moens Hans Hallez UQCV BDL 246 14 0 28 Jan 2025
Always-Sparse Training by Growing Connections with Guided Stochastic Exploration Mike Heddes Narayan Srinivasa T. Givargis Alexandru Nicolau 249 0 0 12 Jan 2024
Evil from Within: Machine Learning Backdoors through Hardware Trojans Alexander Warnecke Julian Speith Janka Möller Konrad Rieck C. Paar AAML 184 3 0 17 Apr 2023
COLT: Cyclic Overlapping Lottery Tickets for Faster Pruning of Convolutional Neural Networks Md. Ismail Hossain Mohammed Rakib M. M. L. Elahi Nabeel Mohammed Shafin Rahman 113 1 0 24 Dec 2022
Stable Low-rank Tensor Decomposition for Compression of Convolutional Neural Network Anh-Huy Phan Konstantin Sobolev Konstantin Sozykin Dmitry Ermilov Julia Gusak P. Tichavský Valeriy Glukhov Ivan Oseledets A. Cichocki BDL 66 131 0 12 Aug 2020
How Much Can I Trust You? -- Quantifying Uncertainties in Explaining Neural Networks Kirill Bykov Marina M.-C. Höhne Klaus-Robert Muller Shinichi Nakajima Marius Kloft UQCV FAtt 101 31 0 16 Jun 2020
AlgebraNets Jordan Hoffmann Simon Schmitt Simon Osindero Karen Simonyan Erich Elsen MoE 153 6 0 12 Jun 2020
The Power of Sparsity in Convolutional Neural Networks Soravit Changpinyo Mark Sandler A. Zhmoginov 75 133 0 21 Feb 2017
Soft Weight-Sharing for Neural Network Compression Karen Ullrich Edward Meeds Max Welling 169 419 0 13 Feb 2017
Generalized Dropout Suraj Srinivas R. Venkatesh Babu BDL 57 47 0 21 Nov 2016
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 351 4,636 0 10 Nov 2016
Ultimate tensorization: compressing convolutional and FC layers alike T. Garipov D. Podoprikhin Alexander Novikov Dmitry Vetrov 70 191 0 10 Nov 2016
Variational Lossy Autoencoder Xi Chen Diederik P. Kingma Tim Salimans Yan Duan Prafulla Dhariwal John Schulman Ilya Sutskever Pieter Abbeel DRL SSL GAN 161 676 0 08 Nov 2016
Information Dropout: Learning Optimal Representations Through Noisy Computation Alessandro Achille Stefano Soatto OOD DRL SSL 68 405 0 04 Nov 2016
Dynamic Network Surgery for Efficient DNNs Yiwen Guo Anbang Yao Yurong Chen 84 1,060 0 16 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
Group Sparse Regularization for Deep Neural Networks Simone Scardapane Danilo Comminiello Amir Hussain A. Uncini 425 466 0 02 Jul 2016
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning Christian Szegedy Sergey Ioffe Vincent Vanhoucke Alexander A. Alemi 382 14,268 0 23 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,510 0 10 Dec 2015
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding Song Han Huizi Mao W. Dally 3DGS 263 8,862 0 01 Oct 2015
Tensorizing Neural Networks Alexander Novikov D. Podoprikhin A. Osokin Dmitry Vetrov 117 886 0 22 Sep 2015
Learning both Weights and Connections for Efficient Neural Networks Song Han Jeff Pool J. Tran W. Dally CVBM 316 6,709 0 08 Jun 2015
Variational Dropout and the Local Reparameterization Trick Diederik P. Kingma Tim Salimans Max Welling BDL 229 1,517 0 08 Jun 2015
Fast ConvNets Using Group-wise Brain Damage V. Lebedev Victor Lempitsky AAML 191 449 0 08 Jun 2015
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 467 43,347 0 11 Feb 2015
A Bayesian encourages dropout S. Maeda BDL 66 45 0 22 Dec 2014
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.1K 150,364 0 22 Dec 2014
Going Deeper with Convolutions Christian Szegedy Wei Liu Yangqing Jia P. Sermanet Scott E. Reed Dragomir Anguelov D. Erhan Vincent Vanhoucke Andrew Rabinovich 494 43,698 0 17 Sep 2014
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 455 16,922 0 20 Dec 2013
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 463 7,667 0 03 Jul 2012
Stochastic Variational Inference Matt Hoffman David M. Blei Chong-Jun Wang John Paisley BDL 262 2,627 0 29 Jun 2012