Learning the Number of Neurons in Deep Networks

19 November 2016

Papers citing "Learning the Number of Neurons in Deep Networks"

50 / 204 papers shown

Title
Distilling Image Classifiers in Object Detectors Shuxuan Guo J. Álvarez Mathieu Salzmann VLM 30 8 0 09 Jun 2021
Feature Flow Regularization: Improving Structured Sparsity in Deep Neural Networks Yue Wu Yuan Lan Luchan Zhang Yang Xiang 17 6 0 05 Jun 2021
Regularization and Reparameterization Avoid Vanishing Gradients in Sigmoid-Type Networks Leni Ven Johannes Lederer ODL 15 5 0 04 Jun 2021
$Neural Network Training Using $\ell_1$-Regularization and Bi-fidelity Data$ Neural Network Training Using $\ell_1$ -Regularization and Bi-fidelity Data Subhayan De Alireza Doostan 29 24 0 27 May 2021
Schematic Memory Persistence and Transience for Efficient and Robust Continual Learning Yuyang Gao Giorgio Ascoli Liang Zhao 27 4 0 05 May 2021
Alternate Model Growth and Pruning for Efficient Training of Recommendation Systems Xiaocong Du Bhargav Bhushanam Jiecao Yu Dhruv Choudhary Tianxiang Gao Sherman Wong Louis Feng Jongsoo Park Yu Cao A. Kejariwal 34 5 0 04 May 2021
Stealthy Backdoors as Compression Artifacts Yulong Tian Fnu Suya Fengyuan Xu David Evans 35 22 0 30 Apr 2021
Modeling Ideological Salience and Framing in Polarized Online Groups with Graph Neural Networks and Structured Sparsity Valentin Hofmann Xiaowen Dong J. Pierrehumbert Hinrich Schütze 21 14 0 18 Apr 2021
Distilling Object Detectors via Decoupled Features Jianyuan Guo Kai Han Yunhe Wang Han Wu Xinghao Chen Chunjing Xu Chang Xu 43 199 0 26 Mar 2021
Reframing Neural Networks: Deep Structure in Overcomplete Representations Calvin Murdock George Cazenavette Simon Lucey BDL 41 4 0 10 Mar 2021
Consistent Sparse Deep Learning: Theory and Computation Y. Sun Qifan Song F. Liang BDL 43 27 0 25 Feb 2021
ChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations Rishabh Tiwari Udbhav Bamba Arnav Chavan D. K. Gupta 17 31 0 14 Feb 2021
AACP: Model Compression by Accurate and Automatic Channel Pruning Lanbo Lin Yujiu Yang Zhenhua Guo MQ 22 12 0 31 Jan 2021
Deep Model Compression based on the Training History S. H. Shabbeer Basha M. Farazuddin Viswanath Pulabaigari S. Dubey Snehasis Mukherjee VLM 30 17 0 30 Jan 2021
Machine Learning for the Detection and Identification of Internet of Things (IoT) Devices: A Survey Yongxin Liu Jian Wang Jianqiang Li Shuteng Niu Haoze Song 38 131 0 25 Jan 2021
On tuning deep learning models: a data mining perspective M. Öztürk 13 0 0 19 Nov 2020
Channel Planting for Deep Neural Networks using Knowledge Distillation Kakeru Mitsuno Yuichiro Nomura Takio Kurita 36 2 0 04 Nov 2020
Filter Pruning using Hierarchical Group Sparse Regularization for Deep Convolutional Neural Networks Kakeru Mitsuno Takio Kurita 16 6 0 04 Nov 2020
Adaptive Dense-to-Sparse Paradigm for Pruning Online Recommendation System with Non-Stationary Data Mao Ye Dhruv Choudhary Jiecao Yu Ellie Wen Zeliang Chen Jiyan Yang Jongsoo Park Qiang Liu A. Kejariwal 29 9 0 16 Oct 2020
Improving Network Slimming with Nonconvex Regularization Kevin Bui Fredrick Park Shuai Zhang Y. Qi Jack Xin 21 9 0 03 Oct 2020
Self-grouping Convolutional Neural Networks Qingbei Guo Xiaojun Wu J. Kittler Zhiquan Feng 25 22 0 29 Sep 2020
Pruning Convolutional Filters using Batch Bridgeout Najeeb Khan Ian Stavness 28 3 0 23 Sep 2020
Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot Jingtong Su Yihang Chen Tianle Cai Tianhao Wu Ruiqi Gao Liwei Wang J. Lee 14 85 0 22 Sep 2020
3D_DEN: Open-ended 3D Object Recognition using Dynamically Expandable Networks Sudhakaran Jain H. Kasaei 3DPC 6 4 0 15 Sep 2020
A Progressive Sub-Network Searching Framework for Dynamic Inference Li Yang Zhezhi He Yu Cao Deliang Fan AI4CE 20 6 0 11 Sep 2020
A Partial Regularization Method for Network Compression E. Zhenqian Weiguo Gao 16 0 0 03 Sep 2020
Training Sparse Neural Networks using Compressed Sensing Jonathan W. Siegel Jianhong Chen Pengchuan Zhang Jinchao Xu 26 5 0 21 Aug 2020
Neural Architecture Search as Sparse Supernet Yunsheng Wu Aoming Liu Zhiwu Huang Siwei Zhang Luc Van Gool 25 22 0 31 Jul 2020
Deep Learning Methods for Solving Linear Inverse Problems: Research Directions and Paradigms Yanna Bai Wei Chen Jie Chen Weisi Guo 40 66 0 27 Jul 2020
T-Basis: a Compact Representation for Neural Networks Anton Obukhov M. Rakhuba Stamatios Georgoulis Menelaos Kanakis Dengxin Dai Luc Van Gool 41 27 0 13 Jul 2020
ResRep: Lossless CNN Pruning via Decoupling Remembering and Forgetting Xiaohan Ding Tianxiang Hao Jianchao Tan Ji Liu Jungong Han Yuchen Guo Guiguang Ding 23 163 0 07 Jul 2020
DessiLBI: Exploring Structural Sparsity of Deep Networks via Differential Inclusion Paths Yanwei Fu Chen Liu Donghao Li Xinwei Sun Jinshan Zeng Yuan Yao 14 9 0 04 Jul 2020
Efficient Proximal Mapping of the 1-path-norm of Shallow Networks Fabian Latorre Paul Rolland Nadav Hallak V. Cevher AAML 26 4 0 02 Jul 2020
Layer Sparsity in Neural Networks Mohamed Hebiri Johannes Lederer 36 10 0 28 Jun 2020
Embedding Differentiable Sparsity into Deep Neural Network Yongjin Lee 21 0 0 23 Jun 2020
Dynamic Model Pruning with Feedback Tao R. Lin Sebastian U. Stich Luis Barba Daniil Dmitriev Martin Jaggi 32 199 0 12 Jun 2020
ADMP: An Adversarial Double Masks Based Pruning Framework For Unsupervised Cross-Domain Compression Xiaoyu Feng Zhuqing Yuan Guijin Wang Yongpan Liu 25 5 0 07 Jun 2020
Pruning via Iterative Ranking of Sensitivity Statistics Stijn Verdenius M. Stol Patrick Forré AAML 21 37 0 01 Jun 2020
PruneNet: Channel Pruning via Global Importance A. Khetan Zohar Karnin 18 11 0 22 May 2020
Generalized Bayesian Posterior Expectation Distillation for Deep Neural Networks Meet P. Vadera B. Jalaeian Benjamin M. Marlin BDL FedML UQCV 17 20 0 16 May 2020
Out-of-the-box channel pruned networks Ragav Venkatesan Gurumurthy Swaminathan Xiong Zhou Anna Luo 20 0 0 30 Apr 2020
Do We Need Fully Connected Output Layers in Convolutional Networks? Zhongchao Qian Tyler L. Hayes Kushal Kafle Christopher Kanan 9 8 0 28 Apr 2020
torchgpipe: On-the-fly Pipeline Parallelism for Training Giant Models Chiheon Kim Heungsub Lee Myungryong Jeong Woonhyuk Baek Boogeon Yoon Ildoo Kim Sungbin Lim Sungwoong Kim MoE AI4CE 16 53 0 21 Apr 2020
Hierarchical Group Sparse Regularization for Deep Convolutional Neural Networks Kakeru Mitsuno J. Miyao Takio Kurita 21 16 0 09 Apr 2020
Dataless Model Selection with the Deep Frame Potential Calvin Murdock Simon Lucey 41 6 0 30 Mar 2020
Continual Learning with Node-Importance based Adaptive Group Sparse Regularization Sangwon Jung Hongjoon Ahn Sungmin Cha Taesup Moon CLL 25 120 0 30 Mar 2020
Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression Yawei Li Shuhang Gu Christoph Mayer Luc Van Gool Radu Timofte 139 189 0 19 Mar 2020
Sparsity Meets Robustness: Channel Pruning for the Feynman-Kac Formalism Principled Robust Deep Neural Nets Thu Dinh Bao Wang Andrea L. Bertozzi Stanley J. Osher AAML 14 16 0 02 Mar 2020
An Equivalence between Bayesian Priors and Penalties in Variational Inference Pierre Wolinski Guillaume Charpiat Yann Ollivier BDL 17 1 0 01 Feb 2020
Filter Sketch for Network Pruning Mingbao Lin Liujuan Cao Shaojie Li QiXiang Ye Yonghong Tian Jianzhuang Liu Q. Tian Rongrong Ji CLIP 3DPC 31 82 0 23 Jan 2020