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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"

50 / 481 papers shown

Title
Gradual Channel Pruning while Training using Feature Relevance Scores for Convolutional Neural NetworksIEEE Access (IEEE Access), 2020 Sai Aparna Aketi Sourjya Roy A. Raghunathan Kaushik Roy 193 27 0 23 Feb 2020
Beyond Dropout: Feature Map Distortion to Regularize Deep Neural NetworksAAAI Conference on Artificial Intelligence (AAAI), 2020 Yehui Tang Yunhe Wang Yixing Xu Boxin Shi Chao Xu Chunjing Xu Chang Xu 206 40 0 23 Feb 2020
Neural Network Compression Framework for fast model inference Alexander Kozlov Ivan Lazarevich Vasily Shamporov N. Lyalyushkin Yury Gorbachev 253 39 0 20 Feb 2020
Compressing BERT: Studying the Effects of Weight Pruning on Transfer LearningWorkshop on Representation Learning for NLP (RepL4NLP), 2020 Mitchell A. Gordon Kevin Duh Nicholas Andrews VLM 255 362 0 19 Feb 2020
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep LearningInternational Conference on Learning Representations (ICLR), 2020 Arsenii Ashukha Alexander Lyzhov Dmitry Molchanov Dmitry Vetrov UQCV FedML 463 342 0 15 Feb 2020
Calibrate and Prune: Improving Reliability of Lottery Tickets Through Prediction Calibration Bindya Venkatesh Jayaraman J. Thiagarajan Kowshik Thopalli P. Sattigeri 209 14 0 10 Feb 2020
Soft Threshold Weight Reparameterization for Learnable SparsityInternational Conference on Machine Learning (ICML), 2020 Aditya Kusupati Vivek Ramanujan Raghav Somani Mitchell Wortsman Prateek Jain Sham Kakade Ali Farhadi 569 261 0 08 Feb 2020
Almost Sure Convergence of Dropout Algorithms for Neural Networks Albert Senen-Cerda J. Sanders 210 11 0 06 Feb 2020
Proving the Lottery Ticket Hypothesis: Pruning is All You NeedInternational Conference on Machine Learning (ICML), 2020 Eran Malach Gilad Yehudai Shai Shalev-Shwartz Ohad Shamir 280 310 0 03 Feb 2020
An Equivalence between Bayesian Priors and Penalties in Variational Inference Pierre Wolinski Guillaume Charpiat Yann Ollivier BDL 149 1 0 01 Feb 2020
PoWER-BERT: Accelerating BERT Inference via Progressive Word-vector Elimination Saurabh Goyal Anamitra R. Choudhury Saurabh ManishRaje Venkatesan T. Chakaravarthy Yogish Sabharwal Ashish Verma 324 19 0 24 Jan 2020
Variational Dropout Sparsification for Particle Identification speed-up Artem Sergeevich Ryzhikov D. Derkach M. Hushchyn 58 0 0 21 Jan 2020
A "Network Pruning Network" Approach to Deep Model CompressionIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2020 Vinay Kumar Verma Pravendra Singh Vinay P. Namboodiri Piyush Rai 3DPC VLM 123 10 0 15 Jan 2020
Block-wise Dynamic SparsenessPattern Recognition Letters (Pattern Recognit. Lett.), 2020 Amir Hadifar Johannes Deleu Chris Develder Thomas Demeester 112 3 0 14 Jan 2020
Campfire: Compressible, Regularization-Free, Structured Sparse Training for Hardware Accelerators Noah Gamboa Kais Kudrolli Anand Dhoot A. Pedram 126 11 0 09 Jan 2020
Resource-Efficient Neural Networks for Embedded Systems Wolfgang Roth Günther Schindler Lukas Pfeifenberger Robert Peharz Sebastian Tschiatschek Holger Fröning Franz Pernkopf Zoubin Ghahramani 219 64 0 07 Jan 2020
Sparse Weight Activation TrainingNeural Information Processing Systems (NeurIPS), 2020 Md Aamir Raihan Tor M. Aamodt 294 77 0 07 Jan 2020
Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural NetworksInternational Conference on Machine Learning (ICML), 2019 Aleksandr Shevchenko Marco Mondelli 366 41 0 20 Dec 2019
Taxonomy and Evaluation of Structured Compression of Convolutional Neural Networks Andrey Kuzmin Markus Nagel Saurabh Pitre Sandeep Pendyam Tijmen Blankevoort Max Welling 121 27 0 20 Dec 2019
$$\ell_0$ Regularized Structured Sparsity Convolutional Neural Networks$ $\ell_0$ Regularized Structured Sparsity Convolutional Neural Networks Kevin Bui Fredrick Park Shuai Zhang Y. Qi Jack Xin 82 0 0 17 Dec 2019
Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific DiscoveryIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2019 Samuel Kim Peter Y. Lu Srijon Mukherjee M. Gilbert Li Jing V. Ceperic Marin Soljacic 142 205 0 10 Dec 2019
Frivolous Units: Wider Networks Are Not Really That WideAAAI Conference on Artificial Intelligence (AAAI), 2019 Stephen Casper Xavier Boix Vanessa D’Amario Ling Guo Martin Schrimpf Kasper Vinken Gabriel Kreiman 211 20 0 10 Dec 2019
Hierarchical Indian Buffet Neural Networks for Bayesian Continual LearningConference on Uncertainty in Artificial Intelligence (UAI), 2019 Samuel Kessler Vu Nguyen S. Zohren Stephen J. Roberts BDL 416 26 0 04 Dec 2019
One-Shot Pruning of Recurrent Neural Networks by Jacobian Spectrum EvaluationInternational Conference on Learning Representations (ICLR), 2019 Matthew Shunshi Zhang Bradly C. Stadie 104 34 0 30 Nov 2019
Efficient Approximate Inference with Walsh-Hadamard Variational Inference Simone Rossi Sébastien Marmin Maurizio Filippone BDL 128 1 0 29 Nov 2019
Semi-Relaxed Quantization with DropBits: Training Low-Bit Neural Networks via Bit-wise Regularization J. H. Lee Jihun Yun Sung Ju Hwang Eunho Yang MQ 157 0 0 29 Nov 2019
A Novel Unsupervised Post-Processing Calibration Method for DNNS with Robustness to Domain Shift A. Mozafari H. Gomes Christian Gagné 89 0 0 25 Nov 2019
Rigging the Lottery: Making All Tickets WinnersInternational Conference on Machine Learning (ICML), 2019 Utku Evci Trevor Gale Jacob Menick Pablo Samuel Castro Erich Elsen 479 678 0 25 Nov 2019
Continual Learning with Adaptive Weights (CLAW)International Conference on Learning Representations (ICLR), 2019 T. Adel Han Zhao Richard Turner CLL 164 79 0 21 Nov 2019
CUP: Cluster Pruning for Compressing Deep Neural Networks Rahul Duggal Cao Xiao R. Vuduc Jimeng Sun 3DPC VLM 92 25 0 19 Nov 2019
A Discriminative Gaussian Mixture Model with SparsityInternational Conference on Learning Representations (ICLR), 2019 Hideaki Hayashi S. Uchida 80 7 0 14 Nov 2019
Structured Sparsification of Gated Recurrent Neural NetworksAAAI Conference on Artificial Intelligence (AAAI), 2019 E. Lobacheva Nadezhda Chirkova Alexander Markovich Dmitry Vetrov 208 3 0 13 Nov 2019
Learning Sparse Sharing Architectures for Multiple TasksAAAI Conference on Artificial Intelligence (AAAI), 2019 Tianxiang Sun Yunfan Shao Xiaonan Li Pengfei Liu Hang Yan Xipeng Qiu Xuanjing Huang MoE 211 150 0 12 Nov 2019
Variational Student: Learning Compact and Sparser Networks in Knowledge Distillation FrameworkIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2019 Srinidhi Hegde Ranjitha Prasad R. Hebbalaguppe Vishwajith Kumar 111 20 0 26 Oct 2019
Reduced-Order Modeling of Deep Neural NetworksComputational Mathematics and Mathematical Physics (CMMP), 2019 Julia Gusak Talgat Daulbaev E. Ponomarev A. Cichocki Ivan Oseledets BDL AI4CE 264 8 0 15 Oct 2019
State of Compact Architecture Search For Deep Neural Networks M. Shafiee Andrew Hryniowski Francis Li Z. Q. Lin A. Wong 101 3 0 15 Oct 2019
If dropout limits trainable depth, does critical initialisation still matter? A large-scale statistical analysis on ReLU networksPattern Recognition Letters (PR), 2019 Arnu Pretorius Elan Van Biljon Benjamin van Niekerk Ryan Eloff Matthew Reynard Steven D. James Benjamin Rosman Herman Kamper Steve Kroon 74 2 0 13 Oct 2019
Information Aware Max-Norm Dirichlet Networks for Predictive Uncertainty Estimation Theodoros Tsiligkaridis UQCV BDL 199 9 0 10 Oct 2019
Structured Pruning of Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP), 2019 Ziheng Wang Jeremy Wohlwend Tao Lei 234 322 0 10 Oct 2019
Deep Evidential RegressionNeural Information Processing Systems (NeurIPS), 2019 Alexander Amini Wilko Schwarting A. Soleimany Daniela Rus EDL PER BDL UD UQCV 290 534 0 07 Oct 2019
Class-dependent Compression of Deep Neural Networks R. Entezari O. Saukh 190 7 0 23 Sep 2019
Defeating Misclassification Attacks Against Transfer LearningIEEE Transactions on Dependable and Secure Computing (TDSC), 2019 Bang Wu Shuo Wang Lizhen Qu Cong Wang Carsten Rudolph Xiangwen Yang AAML 123 7 0 29 Aug 2019
Image Captioning with Sparse Recurrent Neural Network J. Tan Chee Seng Chan Joon Huang Chuah VLM 141 7 0 28 Aug 2019
DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity MeasuresInternational Conference on Learning Representations (ICLR), 2019 Huanrui Yang W. Wen Xue Yang 230 106 0 27 Aug 2019
Neural Plasticity NetworksIEEE International Joint Conference on Neural Network (IJCNN), 2019 Yongqian Li Shihao Ji 104 1 0 13 Aug 2019
Adversarial Neural Pruning with Latent Vulnerability Suppression Divyam Madaan Jinwoo Shin Sung Ju Hwang AAML 203 3 0 12 Aug 2019
Group Pruning using a Bounded-Lp norm for Group Gating and RegularizationGerman Conference on Pattern Recognition (DAGM), 2019 Chaithanya Kumar Mummadi Tim Genewein Dan Zhang Thomas Brox Volker Fischer 106 4 0 09 Aug 2019
Exploiting Channel Similarity for Accelerating Deep Convolutional Neural Networks Yunxiang Zhang Chenglong Zhao Bingbing Ni Jian Zhang Haoran Deng 95 2 0 06 Aug 2019
Distilling Knowledge From a Deep Pose Regressor NetworkIEEE International Conference on Computer Vision (ICCV), 2019 Muhamad Risqi U. Saputra Pedro Porto Buarque de Gusmão Yasin Almalioglu Andrew Markham A. Trigoni 180 111 0 02 Aug 2019
Uncertainty Quantification in Deep Learning for Safer Neuroimage Enhancement Ryutaro Tanno Daniel E. Worrall Enrico Kaden Aurobrata Ghosh Francesco Grussu A. Bizzi S. Sotiropoulos A. Criminisi Daniel C. Alexander MedIm DiffM 205 35 0 31 Jul 2019