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The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
9 March 2018
Jonathan Frankle
Michael Carbin
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Papers citing
"The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks"
36 / 2,186 papers shown
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253
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Structured Compression by Weight Encryption for Unstructured Pruning and Quantization
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Dongsoo Lee
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Parichay Kapoor
Baeseong Park
Gu-Yeon Wei
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249
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Exploring Structural Sparsity of Deep Networks via Inverse Scale Spaces
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Chen Liu
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Zuyuan Zhong
Xinwei Sun
Jinshan Zeng
Xingtai Lv
244
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Gu-Yeon Wei
152
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Analysis of Gene Interaction Graphs as Prior Knowledge for Machine Learning Models
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Mohammad Hashir
Martin Weiss
Vincent Frappier
T. Perkins
G. Boucher
Joseph Paul Cohen
207
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06 May 2019
Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask
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Hattie Zhou
Janice Lan
Rosanne Liu
J. Yosinski
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03 May 2019
Differentiable Visual Computing
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148
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Low-Memory Neural Network Training: A Technical Report
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Megan Leszczynski
Jian Zhang
Christopher Ré
253
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24 Apr 2019
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Linchao Zhu
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205
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08 Apr 2019
Adversarial Robustness vs Model Compression, or Both?
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Kaidi Xu
Sijia Liu
Jan-Henrik Lambrechts
Huan Zhang
Aojun Zhou
Kaisheng Ma
Yanzhi Wang
Xue Lin
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296
172
0
29 Mar 2019
How Can We Be So Dense? The Benefits of Using Highly Sparse Representations
Subutai Ahmad
Luiz Scheinkman
185
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0
27 Mar 2019
Convolution with even-sized kernels and symmetric padding
Neural Information Processing Systems (NeurIPS), 2019
Shuang Wu
Guanrui Wang
Pei Tang
F. Chen
Luping Shi
202
77
0
20 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
316
19
0
17 Mar 2019
Stabilizing the Lottery Ticket Hypothesis
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Gintare Karolina Dziugaite
Daniel M. Roy
Michael Carbin
174
104
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05 Mar 2019
Regularity Normalization: Neuroscience-Inspired Unsupervised Attention across Neural Network Layers
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670
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Parameter Efficient Training of Deep Convolutional Neural Networks by Dynamic Sparse Reparameterization
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Xin Wang
396
332
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15 Feb 2019
Identity Crisis: Memorization and Generalization under Extreme Overparameterization
International Conference on Learning Representations (ICLR), 2019
Chiyuan Zhang
Samy Bengio
Moritz Hardt
Michael C. Mozer
Y. Singer
306
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0
13 Feb 2019
Intrinsically Sparse Long Short-Term Memory Networks
Shiwei Liu
Decebal Constantin Mocanu
Mykola Pechenizkiy
136
9
0
26 Jan 2019
Sparse evolutionary Deep Learning with over one million artificial neurons on commodity hardware
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Decebal Constantin Mocanu
A. R. Ramapuram Matavalam
Yulong Pei
Mykola Pechenizkiy
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26 Jan 2019
A Theoretical Analysis of Deep Q-Learning
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On the Benefit of Width for Neural Networks: Disappearance of Bad Basins
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Tian Ding
Tian Ding
588
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28 Dec 2018
Artificial neural networks condensation: A strategy to facilitate adaption of machine learning in medical settings by reducing computational burden
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N. Sepulveda
Ming Zheng
163
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23 Dec 2018
Neural Rejuvenation: Improving Deep Network Training by Enhancing Computational Resource Utilization
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Zhe Lin
Jianming Zhang
Alan Yuille
149
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0
02 Dec 2018
Structured Pruning of Neural Networks with Budget-Aware Regularization
Computer Vision and Pattern Recognition (CVPR), 2018
Carl Lemaire
Andrew Achkar
Pierre-Marc Jodoin
219
95
0
23 Nov 2018
Understanding Learning Dynamics Of Language Models with SVCCA
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Adam Lopez
419
112
0
01 Nov 2018
The Deep Weight Prior
Andrei Atanov
Arsenii Ashukha
Kirill Struminsky
Dmitry Vetrov
Max Welling
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213
37
0
16 Oct 2018
Rethinking the Value of Network Pruning
Zhuang Liu
Mingjie Sun
Tinghui Zhou
Gao Huang
Trevor Darrell
299
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11 Oct 2018
A Closer Look at Structured Pruning for Neural Network Compression
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Jack Turner
Amos Storkey
Michael F. P. O'Boyle
3DPC
185
31
0
10 Oct 2018
Learning with Random Learning Rates
Léonard Blier
Pierre Wolinski
Yann Ollivier
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264
21
0
02 Oct 2018
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Ilia Shumailov
Robert D. Mullins
Ross J. Anderson
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207
43
0
29 Sep 2018
Dense neural networks as sparse graphs and the lightning initialization
T. Pircher
D. Haspel
Eberhard Schlücker
42
1
0
24 Sep 2018
Learning Representations for Neural Network-Based Classification Using the Information Bottleneck Principle
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2018
Rana Ali Amjad
Bernhard C. Geiger
464
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Nonparametric regression using deep neural networks with ReLU activation function
Johannes Schmidt-Hieber
634
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22 Aug 2017
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