The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks

9 March 2018

Papers citing "The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks"

50 / 599 papers shown

Title
FreezeNet: Full Performance by Reduced Storage Costs Paul Wimmer Jens Mehnert A. P. Condurache 23 13 0 28 Nov 2020
Bringing AI To Edge: From Deep Learning's Perspective Di Liu Hao Kong Xiangzhong Luo Weichen Liu Ravi Subramaniam 52 116 0 25 Nov 2020
Rethinking Weight Decay For Efficient Neural Network Pruning Hugo Tessier Vincent Gripon Mathieu Léonardon M. Arzel T. Hannagan David Bertrand 26 25 0 20 Nov 2020
Dynamic Hard Pruning of Neural Networks at the Edge of the Internet Lorenzo Valerio F. M. Nardini A. Passarella R. Perego 12 12 0 17 Nov 2020
LOss-Based SensiTivity rEgulaRization: towards deep sparse neural networks Enzo Tartaglione Andrea Bragagnolo A. Fiandrotti Marco Grangetto ODL UQCV 15 34 0 16 Nov 2020
Gaussian Processes with Skewed Laplace Spectral Mixture Kernels for Long-term Forecasting Kai Chen Twan van Laarhoven E. Marchiori AI4TS 37 8 0 08 Nov 2020
Low-Complexity Models for Acoustic Scene Classification Based on Receptive Field Regularization and Frequency Damping Khaled Koutini Florian Henkel Hamid Eghbalzadeh Gerhard Widmer 14 9 0 05 Nov 2020
A Bayesian Perspective on Training Speed and Model Selection Clare Lyle Lisa Schut Binxin Ru Y. Gal Mark van der Wilk 39 24 0 27 Oct 2020
ShiftAddNet: A Hardware-Inspired Deep Network Haoran You Xiaohan Chen Yongan Zhang Chaojian Li Sicheng Li Zihao Liu Zhangyang Wang Yingyan Lin OOD MQ 73 76 0 24 Oct 2020
Brain-Inspired Learning on Neuromorphic Substrates Friedemann Zenke Emre Neftci 33 87 0 22 Oct 2020
Mixed-Precision Embedding Using a Cache J. Yang Jianyu Huang Jongsoo Park P. T. P. Tang Andrew Tulloch 19 36 0 21 Oct 2020
Learning to Embed Categorical Features without Embedding Tables for Recommendation Wang-Cheng Kang D. Cheng Tiansheng Yao Xinyang Yi Ting-Li Chen Lichan Hong Ed H. Chi LMTD CML DML 50 68 0 21 Oct 2020
Variational Capsule Encoder Harish RaviPrakash Syed Muhammad Anwar Ulas Bagci BDL DRL 13 2 0 18 Oct 2020
Training independent subnetworks for robust prediction Marton Havasi Rodolphe Jenatton Stanislav Fort Jeremiah Zhe Liu Jasper Snoek Balaji Lakshminarayanan Andrew M. Dai Dustin Tran UQCV OOD 30 208 0 13 Oct 2020
Pretrained Transformers for Text Ranking: BERT and Beyond Jimmy J. Lin Rodrigo Nogueira Andrew Yates VLM 219 610 0 13 Oct 2020
Are Neural Nets Modular? Inspecting Functional Modularity Through Differentiable Weight Masks Róbert Csordás Sjoerd van Steenkiste Jürgen Schmidhuber 37 87 0 05 Oct 2020
Pruning Convolutional Filters using Batch Bridgeout Najeeb Khan Ian Stavness 19 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 6 85 0 22 Sep 2020
MEAL V2: Boosting Vanilla ResNet-50 to 80%+ Top-1 Accuracy on ImageNet without Tricks Zhiqiang Shen Marios Savvides 23 63 0 17 Sep 2020
Multi-Task Learning with Deep Neural Networks: A Survey M. Crawshaw CVBM 30 608 0 10 Sep 2020
CNNPruner: Pruning Convolutional Neural Networks with Visual Analytics Guan Li Junpeng Wang Han-Wei Shen Kaixin Chen Guihua Shan Zhonghua Lu AAML 21 47 0 08 Sep 2020
It's Hard for Neural Networks To Learn the Game of Life Jacob Mitchell Springer Garrett T. Kenyon 11 21 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
LotteryFL: Personalized and Communication-Efficient Federated Learning with Lottery Ticket Hypothesis on Non-IID Datasets Ang Li Jingwei Sun Binghui Wang Lin Duan Sicheng Li Yiran Chen H. Li FedML 6 125 0 07 Aug 2020
Linear discriminant initialization for feed-forward neural networks Marissa Masden D. Sinha FedML 29 3 0 24 Jul 2020
The Representation Theory of Neural Networks M. Armenta Pierre-Marc Jodoin 19 30 0 23 Jul 2020
Probabilistic Active Meta-Learning Jean Kaddour Steindór Sæmundsson M. Deisenroth 19 34 0 17 Jul 2020
T-Basis: a Compact Representation for Neural Networks Anton Obukhov M. Rakhuba Stamatios Georgoulis Menelaos Kanakis Dengxin Dai Luc Van Gool 39 27 0 13 Jul 2020
Beyond Signal Propagation: Is Feature Diversity Necessary in Deep Neural Network Initialization? Yaniv Blumenfeld D. Gilboa Daniel Soudry ODL 20 13 0 02 Jul 2020
Hardware Acceleration of Sparse and Irregular Tensor Computations of ML Models: A Survey and Insights Shail Dave Riyadh Baghdadi Tony Nowatzki Sasikanth Avancha Aviral Shrivastava Baoxin Li 53 81 0 02 Jul 2020
GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding Dmitry Lepikhin HyoukJoong Lee Yuanzhong Xu Dehao Chen Orhan Firat Yanping Huang M. Krikun Noam M. Shazeer Z. Chen MoE 20 1,106 0 30 Jun 2020
Training highly effective connectivities within neural networks with randomly initialized, fixed weights Cristian Ivan Razvan V. Florian 19 4 0 30 Jun 2020
Supermasks in Superposition Mitchell Wortsman Vivek Ramanujan Rosanne Liu Aniruddha Kembhavi Mohammad Rastegari J. Yosinski Ali Farhadi SSL CLL 17 279 0 26 Jun 2020
Data-dependent Pruning to find the Winning Lottery Ticket Dániel Lévai Zsolt Zombori UQCV 6 0 0 25 Jun 2020
Revisiting Loss Modelling for Unstructured Pruning César Laurent Camille Ballas Thomas George Nicolas Ballas Pascal Vincent 22 14 0 22 Jun 2020
Logarithmic Pruning is All You Need Laurent Orseau Marcus Hutter Omar Rivasplata 23 88 0 22 Jun 2020
Deep Polynomial Neural Networks Grigorios G. Chrysos Stylianos Moschoglou Giorgos Bouritsas Jiankang Deng Yannis Panagakis S. Zafeiriou 29 92 0 20 Jun 2020
Directional Pruning of Deep Neural Networks Shih-Kang Chao Zhanyu Wang Yue Xing Guang Cheng ODL 13 33 0 16 Jun 2020
Progressive Skeletonization: Trimming more fat from a network at initialization Pau de Jorge Amartya Sanyal Harkirat Singh Behl Philip H. S. Torr Grégory Rogez P. Dokania 31 95 0 16 Jun 2020
Optimal Lottery Tickets via SubsetSum: Logarithmic Over-Parameterization is Sufficient Ankit Pensia Shashank Rajput Alliot Nagle Harit Vishwakarma Dimitris Papailiopoulos 19 102 0 14 Jun 2020
High-contrast "gaudy" images improve the training of deep neural network models of visual cortex Benjamin R. Cowley Jonathan W. Pillow 24 10 0 13 Jun 2020
Towards More Practical Adversarial Attacks on Graph Neural Networks Jiaqi Ma Shuangrui Ding Qiaozhu Mei AAML 17 119 0 09 Jun 2020
A Framework for Neural Network Pruning Using Gibbs Distributions Alex Labach S. Valaee 9 5 0 08 Jun 2020
An Empirical Analysis of the Impact of Data Augmentation on Knowledge Distillation Deepan Das Haley Massa Abhimanyu Kulkarni Theodoros Rekatsinas 21 18 0 06 Jun 2020
An Overview of Neural Network Compression James OÑeill AI4CE 45 98 0 05 Jun 2020
Feature Purification: How Adversarial Training Performs Robust Deep Learning Zeyuan Allen-Zhu Yuanzhi Li MLT AAML 27 146 0 20 May 2020
Dynamic Sparse Training: Find Efficient Sparse Network From Scratch With Trainable Masked Layers Junjie Liu Zhe Xu Runbin Shi R. Cheung Hayden Kwok-Hay So 9 119 0 14 May 2020
Data-Free Network Quantization With Adversarial Knowledge Distillation Yoojin Choi Jihwan P. Choi Mostafa El-Khamy Jungwon Lee MQ 18 119 0 08 May 2020
Pruning artificial neural networks: a way to find well-generalizing, high-entropy sharp minima Enzo Tartaglione Andrea Bragagnolo Marco Grangetto 21 11 0 30 Apr 2020
Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond Fanghui Liu Xiaolin Huang Yudong Chen Johan A. K. Suykens BDL 36 172 0 23 Apr 2020