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v1v2v3 (latest)

Variational Dropout Sparsifies Deep Neural Networks

International Conference on Machine Learning (ICML), 2017

19 January 2017

Dmitry Vetrov

Papers citing "Variational Dropout Sparsifies Deep Neural Networks"

50 / 481 papers shown

Title
DeepCABAC: A Universal Compression Algorithm for Deep Neural NetworksIEEE Journal on Selected Topics in Signal Processing (JSTSP), 2019 Simon Wiedemann H. Kirchhoffer Stefan Matlage Paul Haase Arturo Marbán ... Ahmed Osman D. Marpe H. Schwarz Thomas Wiegand Wojciech Samek 244 107 0 27 Jul 2019
Sparse Networks from Scratch: Faster Training without Losing Performance Tim Dettmers Luke Zettlemoyer 261 356 0 10 Jul 2019
Neuron ranking -- an informed way to condense convolutional neural networks architecture Kamil Adamczewski Mijung Park FAtt 125 3 0 03 Jul 2019
Deep Active Learning with Adaptive AcquisitionInternational Joint Conference on Artificial Intelligence (IJCAI), 2019 Manuel Haussmann Fred Hamprecht M. Kandemir 149 41 0 27 Jun 2019
The Difficulty of Training Sparse Neural Networks Utku Evci Fabian Pedregosa Aidan Gomez Erich Elsen 283 106 0 25 Jun 2019
Learning Waveform-Based Acoustic Models using Deep Variational Convolutional Neural NetworksIEEE/ACM Transactions on Audio Speech and Language Processing (TASLP), 2019 Dino Oglic Zoran Cvetkovic Peter Sollich BDL 208 8 0 23 Jun 2019
Quantifying and Leveraging Classification Uncertainty for Chest Radiograph AssessmentInternational Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2019 Florin-Cristian Ghesu Bogdan Georgescu Eli Gibson Sebastian Gündel Mannudeep K. Kalra Ramandeep Singh S. Digumarthy Sasa Grbic Dorin Comaniciu UQCV 152 52 0 18 Jun 2019
Scalable Model Compression by Entropy Penalized ReparameterizationInternational Conference on Learning Representations (ICLR), 2019 Deniz Oktay Johannes Ballé Saurabh Singh Abhinav Shrivastava 231 46 0 15 Jun 2019
Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical BayesAAAI Conference on Artificial Intelligence (AAAI), 2019 R. Krishnan Mahesh Subedar Omesh Tickoo BDL 233 58 0 12 Jun 2019
The Generalization-Stability Tradeoff In Neural Network PruningNeural Information Processing Systems (NeurIPS), 2019 Brian Bartoldson Ari S. Morcos Adrian Barbu G. Erlebacher 273 84 0 09 Jun 2019
Non-Differentiable Supervised Learning with Evolution Strategies and Hybrid Methods Karel Lenc Erich Elsen Tom Schaul Karen Simonyan 115 20 0 07 Jun 2019
Variational Resampling Based Assessment of Deep Neural Networks under Distribution ShiftIEEE Symposium Series on Computational Intelligence (SSCI), 2019 Xudong Sun Alexej Gossmann Yu Wang J. Herbinger OOD 210 5 0 07 Jun 2019
One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizersNeural Information Processing Systems (NeurIPS), 2019 Ari S. Morcos Haonan Yu Michela Paganini Yuandong Tian 176 242 0 06 Jun 2019
Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLPInternational Conference on Learning Representations (ICLR), 2019 Haonan Yu Sergey Edunov Yuandong Tian Ari S. Morcos 181 152 0 06 Jun 2019
An Introduction to Variational Autoencoders Diederik P. Kingma Max Welling BDL SSL DRL 683 2,733 0 06 Jun 2019
NodeDrop: A Condition for Reducing Network Size without Effect on Output Louis Jensen Jacob A. Harer S. Chin 95 0 0 03 Jun 2019
Bayesian Evidential Deep Learning with PAC Regularization Manuel Haussmann S. Gerwinn M. Kandemir UQCV EDL BDL 205 1 0 03 Jun 2019
Discovering Neural WiringsNeural Information Processing Systems (NeurIPS), 2019 Mitchell Wortsman Ali Farhadi Mohammad Rastegari AI4CE 445 127 0 03 Jun 2019
Multi-Objective Pruning for CNNs Using Genetic AlgorithmInternational Conference on Artificial Neural Networks (ICANN), 2019 Chuanguang Yang Zhulin An Chao Li Boyu Diao Yongjun Xu 3DPC 95 33 0 02 Jun 2019
Learning Sparse Networks Using Targeted Dropout Aidan Gomez Ivan Zhang Siddhartha Rao Kamalakara Divyam Madaan Kevin Swersky Y. Gal Geoffrey E. Hinton 331 99 0 31 May 2019
Robust Sparse Regularization: Simultaneously Optimizing Neural Network Robustness and Compactness Adnan Siraj Rakin Zhezhi He Li Yang Yanzhi Wang Liqiang Wang Deliang Fan AAML 158 21 0 30 May 2019
Where is the Information in a Deep Neural Network? Alessandro Achille Giovanni Paolini Stefano Soatto 364 90 0 29 May 2019
Accelerating Monte Carlo Bayesian Inference via Approximating Predictive Uncertainty over Simplex Yufei Cui Wuguannan Yao Qiao Li Antoni B. Chan Chun Jason Xue 80 4 0 29 May 2019
SpArSe: Sparse Architecture Search for CNNs on Resource-Constrained MicrocontrollersNeural Information Processing Systems (NeurIPS), 2019 Igor Fedorov Ryan P. Adams Matthew Mattina P. Whatmough 216 173 0 28 May 2019
Walsh-Hadamard Variational Inference for Bayesian Deep LearningNeural Information Processing Systems (NeurIPS), 2019 Simone Rossi Sébastien Marmin Maurizio Filippone BDL 194 16 0 27 May 2019
ShrinkTeaNet: Million-scale Lightweight Face Recognition via Shrinking Teacher-Student Networks C. Duong Khoa Luu Kha Gia Quach Ngan Le CVBM 126 40 0 25 May 2019
Structured Compression by Weight Encryption for Unstructured Pruning and QuantizationComputer Vision and Pattern Recognition (CVPR), 2019 S. Kwon Dongsoo Lee Byeongwook Kim Parichay Kapoor Baeseong Park Gu-Yeon Wei MQ 233 57 0 24 May 2019
Revisiting hard thresholding for DNN pruning Konstantinos Pitas Mike Davies P. Vandergheynst AAML 120 2 0 21 May 2019
Sparse Transfer Learning via Winning Lottery Tickets Rahul Mehta UQCV 120 47 0 19 May 2019
DeepCABAC: Context-adaptive binary arithmetic coding for deep neural network compression Simon Wiedemann H. Kirchhoffer Stefan Matlage Paul Haase Arturo Marbán ... Ahmed Osman D. Marpe H. Schwarz Thomas Wiegand Wojciech Samek MQ 168 21 0 15 May 2019
Network Pruning for Low-Rank Binary Indexing Dongsoo Lee S. Kwon Byeongwook Kim Parichay Kapoor Gu-Yeon Wei 139 6 0 14 May 2019
BayesNAS: A Bayesian Approach for Neural Architecture SearchInternational Conference on Machine Learning (ICML), 2019 Hongpeng Zhou Minghao Yang Jun Wang Wei Pan BDL 250 216 0 13 May 2019
Approximated Oracle Filter Pruning for Destructive CNN Width OptimizationInternational Conference on Machine Learning (ICML), 2019 Xiaohan Ding Guiguang Ding Yuchen Guo Jiawei Han C. Yan AAML 156 133 0 12 May 2019
Training CNNs with Selective Allocation of ChannelsInternational Conference on Machine Learning (ICML), 2019 Jongheon Jeong Jinwoo Shin CVBM 176 16 0 11 May 2019
Survey of Dropout Methods for Deep Neural Networks Alex Labach Hojjat Salehinejad S. Valaee 170 165 0 25 Apr 2019
$L_0$ -ARM: Network Sparsification via Stochastic Binary Optimization Yang Li Shihao Ji MQ 221 15 0 09 Apr 2019
How Can We Be So Dense? The Benefits of Using Highly Sparse Representations Subutai Ahmad Luiz Scheinkman 173 102 0 27 Mar 2019
Combining Model and Parameter Uncertainty in Bayesian Neural Networks A. Hubin G. Storvik UQCV BDL 163 13 0 18 Mar 2019
A Brain-inspired Algorithm for Training Highly Sparse Neural Networks Zahra Atashgahi Joost Pieterse Shiwei Liu Decebal Constantin Mocanu Raymond N. J. Veldhuis Mykola Pechenizkiy 256 19 0 17 Mar 2019
Monotonic Gaussian Process for Spatio-Temporal Disease Progression Modeling in Brain Imaging Data Clément Abi-Nader N. Ayache P. Robert Marco Lorenzi 168 3 0 28 Feb 2019
How Large a Vocabulary Does Text Classification Need? A Variational Approach to Vocabulary SelectionNorth American Chapter of the Association for Computational Linguistics (NAACL), 2019 Wenhu Chen Yu-Chuan Su Yilin Shen Zhiyu Zoey Chen Xifeng Yan Wenjie Wang VLM 287 32 0 27 Feb 2019
The State of Sparsity in Deep Neural Networks Trevor Gale Erich Elsen Sara Hooker 337 830 0 25 Feb 2019
Jointly Sparse Convolutional Neural Networks in Dual Spatial-Winograd Domains Yoojin Choi Mostafa El-Khamy Jungwon Lee 125 6 0 21 Feb 2019
Information Losses in Neural Classifiers from Sampling Brandon Foggo N. Yu Jie Shi Yuanqi Gao 129 7 0 15 Feb 2019
Structured Bayesian Compression for Deep models in mobile enabled devices for connected healthcareIEEE Network (IEEE Netw.), 2019 Sijia Chen Bin Song Xiaojiang Du Nadra Guizani HAI MedIm 49 2 0 13 Feb 2019
Gaussian Mean Field Regularizes by Limiting Learned InformationEntropy (Entropy), 2019 Julius Kunze Louis Kirsch H. Ritter David Barber FedML MLT 151 2 0 12 Feb 2019
Radial and Directional Posteriors for Bayesian Neural Networks Changyong Oh Kamil Adamczewski Mijung Park BDL 180 21 0 07 Feb 2019
A Simple Baseline for Bayesian Uncertainty in Deep Learning Wesley J. Maddox T. Garipov Pavel Izmailov Dmitry Vetrov A. Wilson BDL UQCV 631 902 0 07 Feb 2019
Compression of Recurrent Neural Networks for Efficient Language Modeling Artem M. Grachev D. Ignatov Andrey V. Savchenko 151 42 0 06 Feb 2019
Sparse evolutionary Deep Learning with over one million artificial neurons on commodity hardware Shiwei Liu Decebal Constantin Mocanu A. R. Ramapuram Matavalam Yulong Pei Mykola Pechenizkiy BDL 272 94 0 26 Jan 2019

v1v2v3 (latest)

Variational Dropout Sparsifies Deep Neural Networks

International Conference on Machine Learning (ICML), 2017

19 January 2017

Dmitry Vetrov

Papers citing "Variational Dropout Sparsifies Deep Neural Networks"

50 / 481 papers shown

Title
DeepCABAC: A Universal Compression Algorithm for Deep Neural NetworksIEEE Journal on Selected Topics in Signal Processing (JSTSP), 2019 Simon Wiedemann H. Kirchhoffer Stefan Matlage Paul Haase Arturo Marbán ... Ahmed Osman D. Marpe H. Schwarz Thomas Wiegand Wojciech Samek 244 107 0 27 Jul 2019
Sparse Networks from Scratch: Faster Training without Losing Performance Tim Dettmers Luke Zettlemoyer 261 356 0 10 Jul 2019
Neuron ranking -- an informed way to condense convolutional neural networks architecture Kamil Adamczewski Mijung Park FAtt 125 3 0 03 Jul 2019
Deep Active Learning with Adaptive AcquisitionInternational Joint Conference on Artificial Intelligence (IJCAI), 2019 Manuel Haussmann Fred Hamprecht M. Kandemir 149 41 0 27 Jun 2019
The Difficulty of Training Sparse Neural Networks Utku Evci Fabian Pedregosa Aidan Gomez Erich Elsen 283 106 0 25 Jun 2019
Learning Waveform-Based Acoustic Models using Deep Variational Convolutional Neural NetworksIEEE/ACM Transactions on Audio Speech and Language Processing (TASLP), 2019 Dino Oglic Zoran Cvetkovic Peter Sollich BDL 208 8 0 23 Jun 2019
Quantifying and Leveraging Classification Uncertainty for Chest Radiograph AssessmentInternational Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2019 Florin-Cristian Ghesu Bogdan Georgescu Eli Gibson Sebastian Gündel Mannudeep K. Kalra Ramandeep Singh S. Digumarthy Sasa Grbic Dorin Comaniciu UQCV 152 52 0 18 Jun 2019
Scalable Model Compression by Entropy Penalized ReparameterizationInternational Conference on Learning Representations (ICLR), 2019 Deniz Oktay Johannes Ballé Saurabh Singh Abhinav Shrivastava 231 46 0 15 Jun 2019
Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical BayesAAAI Conference on Artificial Intelligence (AAAI), 2019 R. Krishnan Mahesh Subedar Omesh Tickoo BDL 233 58 0 12 Jun 2019
The Generalization-Stability Tradeoff In Neural Network PruningNeural Information Processing Systems (NeurIPS), 2019 Brian Bartoldson Ari S. Morcos Adrian Barbu G. Erlebacher 273 84 0 09 Jun 2019
Non-Differentiable Supervised Learning with Evolution Strategies and Hybrid Methods Karel Lenc Erich Elsen Tom Schaul Karen Simonyan 115 20 0 07 Jun 2019
Variational Resampling Based Assessment of Deep Neural Networks under Distribution ShiftIEEE Symposium Series on Computational Intelligence (SSCI), 2019 Xudong Sun Alexej Gossmann Yu Wang J. Herbinger OOD 210 5 0 07 Jun 2019
One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizersNeural Information Processing Systems (NeurIPS), 2019 Ari S. Morcos Haonan Yu Michela Paganini Yuandong Tian 176 242 0 06 Jun 2019
Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLPInternational Conference on Learning Representations (ICLR), 2019 Haonan Yu Sergey Edunov Yuandong Tian Ari S. Morcos 181 152 0 06 Jun 2019
An Introduction to Variational Autoencoders Diederik P. Kingma Max Welling BDL SSL DRL 683 2,733 0 06 Jun 2019
NodeDrop: A Condition for Reducing Network Size without Effect on Output Louis Jensen Jacob A. Harer S. Chin 95 0 0 03 Jun 2019
Bayesian Evidential Deep Learning with PAC Regularization Manuel Haussmann S. Gerwinn M. Kandemir UQCV EDL BDL 205 1 0 03 Jun 2019
Discovering Neural WiringsNeural Information Processing Systems (NeurIPS), 2019 Mitchell Wortsman Ali Farhadi Mohammad Rastegari AI4CE 445 127 0 03 Jun 2019
Multi-Objective Pruning for CNNs Using Genetic AlgorithmInternational Conference on Artificial Neural Networks (ICANN), 2019 Chuanguang Yang Zhulin An Chao Li Boyu Diao Yongjun Xu 3DPC 95 33 0 02 Jun 2019
Learning Sparse Networks Using Targeted Dropout Aidan Gomez Ivan Zhang Siddhartha Rao Kamalakara Divyam Madaan Kevin Swersky Y. Gal Geoffrey E. Hinton 331 99 0 31 May 2019
Robust Sparse Regularization: Simultaneously Optimizing Neural Network Robustness and Compactness Adnan Siraj Rakin Zhezhi He Li Yang Yanzhi Wang Liqiang Wang Deliang Fan AAML 158 21 0 30 May 2019
Where is the Information in a Deep Neural Network? Alessandro Achille Giovanni Paolini Stefano Soatto 364 90 0 29 May 2019
Accelerating Monte Carlo Bayesian Inference via Approximating Predictive Uncertainty over Simplex Yufei Cui Wuguannan Yao Qiao Li Antoni B. Chan Chun Jason Xue 80 4 0 29 May 2019
SpArSe: Sparse Architecture Search for CNNs on Resource-Constrained MicrocontrollersNeural Information Processing Systems (NeurIPS), 2019 Igor Fedorov Ryan P. Adams Matthew Mattina P. Whatmough 216 173 0 28 May 2019
Walsh-Hadamard Variational Inference for Bayesian Deep LearningNeural Information Processing Systems (NeurIPS), 2019 Simone Rossi Sébastien Marmin Maurizio Filippone BDL 194 16 0 27 May 2019
ShrinkTeaNet: Million-scale Lightweight Face Recognition via Shrinking Teacher-Student Networks C. Duong Khoa Luu Kha Gia Quach Ngan Le CVBM 126 40 0 25 May 2019
Structured Compression by Weight Encryption for Unstructured Pruning and QuantizationComputer Vision and Pattern Recognition (CVPR), 2019 S. Kwon Dongsoo Lee Byeongwook Kim Parichay Kapoor Baeseong Park Gu-Yeon Wei MQ 233 57 0 24 May 2019
Revisiting hard thresholding for DNN pruning Konstantinos Pitas Mike Davies P. Vandergheynst AAML 120 2 0 21 May 2019
Sparse Transfer Learning via Winning Lottery Tickets Rahul Mehta UQCV 120 47 0 19 May 2019
DeepCABAC: Context-adaptive binary arithmetic coding for deep neural network compression Simon Wiedemann H. Kirchhoffer Stefan Matlage Paul Haase Arturo Marbán ... Ahmed Osman D. Marpe H. Schwarz Thomas Wiegand Wojciech Samek MQ 168 21 0 15 May 2019
Network Pruning for Low-Rank Binary Indexing Dongsoo Lee S. Kwon Byeongwook Kim Parichay Kapoor Gu-Yeon Wei 139 6 0 14 May 2019
BayesNAS: A Bayesian Approach for Neural Architecture SearchInternational Conference on Machine Learning (ICML), 2019 Hongpeng Zhou Minghao Yang Jun Wang Wei Pan BDL 250 216 0 13 May 2019
Approximated Oracle Filter Pruning for Destructive CNN Width OptimizationInternational Conference on Machine Learning (ICML), 2019 Xiaohan Ding Guiguang Ding Yuchen Guo Jiawei Han C. Yan AAML 156 133 0 12 May 2019
Training CNNs with Selective Allocation of ChannelsInternational Conference on Machine Learning (ICML), 2019 Jongheon Jeong Jinwoo Shin CVBM 176 16 0 11 May 2019
Survey of Dropout Methods for Deep Neural Networks Alex Labach Hojjat Salehinejad S. Valaee 170 165 0 25 Apr 2019
$L_0$ -ARM: Network Sparsification via Stochastic Binary Optimization Yang Li Shihao Ji MQ 221 15 0 09 Apr 2019
How Can We Be So Dense? The Benefits of Using Highly Sparse Representations Subutai Ahmad Luiz Scheinkman 173 102 0 27 Mar 2019
Combining Model and Parameter Uncertainty in Bayesian Neural Networks A. Hubin G. Storvik UQCV BDL 163 13 0 18 Mar 2019
A Brain-inspired Algorithm for Training Highly Sparse Neural Networks Zahra Atashgahi Joost Pieterse Shiwei Liu Decebal Constantin Mocanu Raymond N. J. Veldhuis Mykola Pechenizkiy 256 19 0 17 Mar 2019
Monotonic Gaussian Process for Spatio-Temporal Disease Progression Modeling in Brain Imaging Data Clément Abi-Nader N. Ayache P. Robert Marco Lorenzi 168 3 0 28 Feb 2019
How Large a Vocabulary Does Text Classification Need? A Variational Approach to Vocabulary SelectionNorth American Chapter of the Association for Computational Linguistics (NAACL), 2019 Wenhu Chen Yu-Chuan Su Yilin Shen Zhiyu Zoey Chen Xifeng Yan Wenjie Wang VLM 287 32 0 27 Feb 2019
The State of Sparsity in Deep Neural Networks Trevor Gale Erich Elsen Sara Hooker 337 830 0 25 Feb 2019
Jointly Sparse Convolutional Neural Networks in Dual Spatial-Winograd Domains Yoojin Choi Mostafa El-Khamy Jungwon Lee 125 6 0 21 Feb 2019
Information Losses in Neural Classifiers from Sampling Brandon Foggo N. Yu Jie Shi Yuanqi Gao 129 7 0 15 Feb 2019
Structured Bayesian Compression for Deep models in mobile enabled devices for connected healthcareIEEE Network (IEEE Netw.), 2019 Sijia Chen Bin Song Xiaojiang Du Nadra Guizani HAI MedIm 49 2 0 13 Feb 2019
Gaussian Mean Field Regularizes by Limiting Learned InformationEntropy (Entropy), 2019 Julius Kunze Louis Kirsch H. Ritter David Barber FedML MLT 151 2 0 12 Feb 2019
Radial and Directional Posteriors for Bayesian Neural Networks Changyong Oh Kamil Adamczewski Mijung Park BDL 180 21 0 07 Feb 2019
A Simple Baseline for Bayesian Uncertainty in Deep Learning Wesley J. Maddox T. Garipov Pavel Izmailov Dmitry Vetrov A. Wilson BDL UQCV 631 902 0 07 Feb 2019
Compression of Recurrent Neural Networks for Efficient Language Modeling Artem M. Grachev D. Ignatov Andrey V. Savchenko 151 42 0 06 Feb 2019
Sparse evolutionary Deep Learning with over one million artificial neurons on commodity hardware Shiwei Liu Decebal Constantin Mocanu A. R. Ramapuram Matavalam Yulong Pei Mykola Pechenizkiy BDL 272 94 0 26 Jan 2019