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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"

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1xN Pattern for Pruning Convolutional Neural NetworksIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021 Mingbao Lin Yu-xin Zhang Yuchao Li Bohong Chen Jiayi Ji Mengdi Wang Shen Li Yonghong Tian Rongrong Ji 3DPC 241 50 0 31 May 2021
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Neural 3D Scene Compression via Model Compression Berivan Isik 298 10 0 07 May 2021
Modulating Regularization Frequency for Efficient Compression-Aware Model Training Dongsoo Lee S. Kwon Byeongwook Kim Jeongin Yun Baeseong Park Yongkweon Jeon 101 0 0 05 May 2021
Encoding Weights of Irregular Sparsity for Fixed-to-Fixed Model CompressionInternational Conference on Learning Representations (ICLR), 2021 Baeseong Park S. Kwon Daehwan Oh Byeongwook Kim Dongsoo Lee 178 4 0 05 May 2021
Effective Sparsification of Neural Networks with Global Sparsity ConstraintComputer Vision and Pattern Recognition (CVPR), 2021 Xiao Zhou Weizhong Zhang Hang Xu Tong Zhang 247 75 0 03 May 2021
What Are Bayesian Neural Network Posteriors Really Like?International Conference on Machine Learning (ICML), 2021 Pavel Izmailov Sharad Vikram Matthew D. Hoffman A. Wilson UQCV BDL 300 434 0 29 Apr 2021
Lottery Jackpots Exist in Pre-trained ModelsIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021 Yuxin Zhang Mingbao Lin Yan Wang Jiayi Ji Rongrong Ji 343 18 0 18 Apr 2021
Robust Classification from Noisy Labels: Integrating Additional Knowledge for Chest Radiography Abnormality Assessment Sebastian Gündel A. Setio Florin-Cristian Ghesu Sasa Grbic Bogdan Georgescu Andreas Maier Dorin Comaniciu NoLa 212 30 0 12 Apr 2021
Not All Attention Is All You Need Hongqiu Wu Hai Zhao Min Zhang 231 10 0 10 Apr 2021
Efficacy of Bayesian Neural Networks in Active Learning Vineeth Rakesh Swayambhoo Jain BDL 104 10 0 02 Apr 2021
Cascade Weight Shedding in Deep Neural Networks: Benefits and Pitfalls for Network Pruning K. Azarian Fatih Porikli CVBM 71 0 0 19 Mar 2021
Contextual Dropout: An Efficient Sample-Dependent Dropout ModuleInternational Conference on Learning Representations (ICLR), 2021 Xinjie Fan Shujian Zhang Korawat Tanwisuth Xiaoning Qian Mingyuan Zhou OOD BDL UQCV 160 31 0 06 Mar 2021
LocalDrop: A Hybrid Regularization for Deep Neural NetworksIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021 Ziqing Lu Chang Xu Bo Du Takashi Ishida Guang Dai Masashi Sugiyama 177 17 0 01 Mar 2021
An Information-Theoretic Justification for Model PruningInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021 Berivan Isik Tsachy Weissman Albert No 294 39 0 16 Feb 2021
Structured Dropout Variational Inference for Bayesian Neural NetworksNeural Information Processing Systems (NeurIPS), 2021 S. Nguyen Duong Nguyen Khai Nguyen Khoat Than Hung Bui Nhat Ho BDL DRL 249 10 0 16 Feb 2021
Bayesian Neural Network Priors RevisitedInternational Conference on Learning Representations (ICLR), 2021 Vincent Fortuin Adrià Garriga-Alonso Sebastian W. Ober F. Wenzel Gunnar Rätsch Richard Turner Mark van der Wilk Laurence Aitchison BDL UQCV 333 154 0 12 Feb 2021
Learning Task-Oriented Communication for Edge Inference: An Information Bottleneck ApproachIEEE Journal on Selected Areas in Communications (JSAC), 2021 Jiawei Shao Yuyi Mao Jun Zhang 219 269 0 08 Feb 2021
Extracting the Auditory Attention in a Dual-Speaker Scenario from EEG using a Joint CNN-LSTM ModelFrontiers in Physiology (Front. Physiol.), 2021 Ivine Kuruvila J. Muncke Eghart Fischer U. Hoppe 77 31 0 08 Feb 2021
SeReNe: Sensitivity based Regularization of Neurons for Structured Sparsity in Neural NetworksIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021 Enzo Tartaglione Andrea Bragagnolo Francesco Odierna Attilio Fiandrotti Marco Grangetto 157 22 0 07 Feb 2021
Deep Model Compression based on the Training HistoryNeurocomputing (Neurocomputing), 2021 S. H. Shabbeer Basha M. Farazuddin Viswanath Pulabaigari S. Dubey Snehasis Mukherjee VLM 243 25 0 30 Jan 2021
Variational Nested DropoutIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021 Yufei Cui Yushun Mao Ziquan Liu Qiao Li Antoni B. Chan Xue Liu Tei-Wei Kuo Chun Jason Xue BDL 122 5 0 27 Jan 2021
Pruning and Quantization for Deep Neural Network Acceleration: A SurveyNeurocomputing (Neurocomputing), 2021 Tailin Liang C. Glossner Lei Wang Shaobo Shi Xiaotong Zhang MQ 460 841 0 24 Jan 2021
Non-Convex Compressed Sensing with Training Data G. Welper 173 1 0 20 Jan 2021
SparseDNN: Fast Sparse Deep Learning Inference on CPUs Ziheng Wang MQ 285 21 0 20 Jan 2021
Rescaling CNN through Learnable Repetition of Network ParametersInternational Conference on Information Photonics (ICIP), 2021 Arnav Chavan Udbhav Bamba Rishabh Tiwari D. K. Gupta 98 0 0 14 Jan 2021
B-SMALL: A Bayesian Neural Network approach to Sparse Model-Agnostic Meta-LearningIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2021 Anish Madan Ranjitha Prasad BDL 78 3 0 01 Jan 2021
Enabling Retrain-free Deep Neural Network Pruning using Surrogate Lagrangian Relaxation Deniz Gurevin Shangli Zhou Lynn Pepin Bingbing Li Mikhail A. Bragin Caiwen Ding Fei Miao 107 3 0 18 Dec 2020
Neural Pruning via Growing RegularizationInternational Conference on Learning Representations (ICLR), 2020 Huan Wang Can Qin Yulun Zhang Y. Fu 251 180 0 16 Dec 2020
The Role of Regularization in Shaping Weight and Node Pruning Dependency and Dynamics Yael Ben-Guigui Jacob Goldberger Tammy Riklin-Raviv 150 0 0 07 Dec 2020
DiffPrune: Neural Network Pruning with Deterministic Approximate Binary Gates and $L_0$ Regularization Yaniv Shulman 270 4 0 07 Dec 2020
Semi-Supervised Learning with Variational Bayesian Inference and Maximum Uncertainty RegularizationAAAI Conference on Artificial Intelligence (AAAI), 2020 Kien Do T. Tran Svetha Venkatesh BDL 193 5 0 03 Dec 2020
Asymptotic convergence rate of Dropout on shallow linear neural networksMeasurement and Modeling of Computer Systems (SIGMETRICS), 2020 Albert Senen-Cerda J. Sanders 192 9 0 01 Dec 2020
Bringing AI To Edge: From Deep Learning's PerspectiveNeurocomputing (Neurocomputing), 2020 Di Liu Hao Kong Xiangzhong Luo Weichen Liu Ravi Subramaniam 226 151 0 25 Nov 2020
Generalized Variational Continual LearningInternational Conference on Learning Representations (ICLR), 2020 Noel Loo S. Swaroop Richard Turner BDL CLL 180 70 0 24 Nov 2020
Rethinking Weight Decay For Efficient Neural Network PruningJournal of Imaging (JI), 2020 Hugo Tessier Vincent Gripon Mathieu Léonardon M. Arzel T. Hannagan David Bertrand 275 29 0 20 Nov 2020
Dynamic Hard Pruning of Neural Networks at the Edge of the InternetJournal of Network and Computer Applications (JNCA), 2020 Lorenzo Valerio F. M. Nardini A. Passarella R. Perego 187 16 0 17 Nov 2020
LOss-Based SensiTivity rEgulaRization: towards deep sparse neural networksNeural Networks (NN), 2020 Enzo Tartaglione Andrea Bragagnolo Attilio Fiandrotti Marco Grangetto ODL UQCV 226 35 0 16 Nov 2020
Efficient Variational Inference for Sparse Deep Learning with Theoretical GuaranteeNeural Information Processing Systems (NeurIPS), 2020 Jincheng Bai Qifan Song Guang Cheng BDL 148 48 0 15 Nov 2020
Dirichlet Pruning for Neural Network Compression Kamil Adamczewski Mijung Park 158 5 0 10 Nov 2020
Sparse within Sparse Gaussian Processes using Neighbor Information Gia-Lac Tran Dimitrios Milios Pietro Michiardi Maurizio Filippone 313 19 0 10 Nov 2020
Observation Space Matters: Benchmark and Optimization AlgorithmIEEE International Conference on Robotics and Automation (ICRA), 2020 J. Kim Sehoon Ha OOD OffRL 187 12 0 02 Nov 2020
Greedy Optimization Provably Wins the Lottery: Logarithmic Number of Winning Tickets is EnoughNeural Information Processing Systems (NeurIPS), 2020 Mao Ye Lemeng Wu Qiang Liu 127 17 0 29 Oct 2020
On Convergence and Generalization of Dropout TrainingNeural Information Processing Systems (NeurIPS), 2020 Poorya Mianjy R. Arora 209 33 0 23 Oct 2020
Failure Prediction by Confidence Estimation of Uncertainty-Aware Dirichlet NetworksIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020 Theodoros Tsiligkaridis UQCV 93 8 0 19 Oct 2020
Layer-adaptive sparsity for the Magnitude-based Pruning Jaeho Lee Sejun Park Sangwoo Mo SungSoo Ahn Jinwoo Shin 224 288 0 15 Oct 2020
$Improve the Robustness and Accuracy of Deep Neural Network with $L_{2,\infty}$ Normalization$ Improve the Robustness and Accuracy of Deep Neural Network with $L_{2,\infty}$ Normalization Lijia Yu Xiao-Shan Gao 37 0 0 10 Oct 2020
Gradient Flow in Sparse Neural Networks and How Lottery Tickets Win Utku Evci Yani Andrew Ioannou Cem Keskin Yann N. Dauphin 190 100 0 07 Oct 2020
A Survey on Deep Neural Network Compression: Challenges, Overview, and Solutions Rahul Mishra Hari Prabhat Gupta Tanima Dutta 125 102 0 05 Oct 2020
PipeTune: Pipeline Parallelism of Hyper and System Parameters Tuning for Deep Learning ClustersInternational Middleware Conference (Middleware), 2020 Isabelly Rocha Nathaniel Morris L. Chen Pascal Felber Robert Birke V. Schiavoni 177 11 0 01 Oct 2020