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There have been long-standing controversies and inconsistencies over the experiment setup and criteria for identifying the "winning ticket" in literature.
Optimal brain damage
Yann LeCun, John S Denker, and Sara A Solla · 1990
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Learning multiple layers of features from tiny images
Alex Krizhevsky · 2009
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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Tiny imagenet visual recognition challenge
Ya Le and Xuan Yang · 2015
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Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding
Song Han, Huizi Mao, and William J. Dally · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Sergey Zagoruyko and Nikos Komodakis · 2016
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Visualizing deep network training trajectories with pca
Eliana Lorch · 2016
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To prune, or not to prune: exploring the efficacy of pruning for model compression
Michael Zhu and Suyog Gupta · 2017
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Mobilenets: Efficient convolutional neural networks for mobile vision applications
Andrew Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, and Hartwig Adam · 2017
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The lottery ticket hypothesis: Finding sparse, trainable neural networks
Jonathan Frankle and Michael Carbin · 2018
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Piggyback: Adapting a single network to multiple tasks by learning to mask weights
Arun Mallya, Dillon Davis, and Svetlana Lazebnik · 2018
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Visualizing the loss landscape of neural nets
Hao Li, Zheng Xu, Gavin Taylor, Christoph Studer, and Tom Goldstein · 2018
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The state of sparsity in deep neural networks
Trevor Gale, Erich Elsen, and Sara Hooker · 2019
Cited alongside, same era.
Playing the lottery with rewards and multiple languages: lottery tickets in rl and nlp
Haonan Yu, Sergey Edunov, Yuandong Tian, and Ari S Morcos · 2019
Cited alongside, same era.
One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers
Ari S Morcos, Haonan Yu, Michela Paganini, and Yuandong Tian · 2019
Cited alongside, same era.
Sparse transfer learning via winning lottery tickets
Rahul Mehta · 2019
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The early phase of neural network training
Jonathan Frankle, David J Schwab, and Ari S Morcos · 2020
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Picking winning tickets before training by preserving gradient flow
Chaoqi Wang, Guodong Zhang, and Roger Grosse · 2020
Later among the works it cites.
The lottery tickets hypothesis for supervised and self-supervised pre-training in computer vision models
Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Michael Carbin, and Zhangyang Wang · 2021
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Efficient lottery ticket finding: Less data is more
Zhenyu Zhang, Xuxi Chen, Tianlong Chen, and Zhangyang Wang · 2021
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Uncovering the impact of hyperparameters for global magnitude pruning, 2021
Janice Lan, Rudy Chin, Alexei Baevski, and Ari S. Morcos · 2021
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Snip: Single-shot network pruning based on connection sensitivity
Namhoon Lee, Thalaiyasingam Ajanthan, and Philip Torr · 2019
Cited alongside, same era.
Deconstructing lottery tickets: Zeros, signs, and the supermask
Hattie Zhou, Janice Lan, Rosanne Liu, and Jason Yosinski · 2020
Cited alongside, same era.
Drawing early-bird tickets: Towards more efficient training of deep networks
Haoran You, Chaojian Li, Pengfei Xu, Yonggan Fu, Yue Wang, Xiaohan Chen, Richard G Baraniuk, Zhangyang Wang, and Yingyan Lin · 2020
Cited alongside, same era.
Comparing rewinding and fine-tuning in neural network pruning
Alex Renda, Jonathan Frankle, and Michael Carbin · 2020
Cited alongside, same era.
The lottery ticket hypothesis for pre-trained bert networks
Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Zhangyang Wang, and Michael Carbin · 2020
Cited alongside, same era.
Rethinking the value of network pruning
Zhuang Liu, Mingjie Sun, Tinghui Zhou, Gao Huang, and Trevor Darrell · 2020
Cited alongside, same era.
Linear mode connectivity and the lottery ticket hypothesis
Jonathan Frankle, Gintare Karolina Dziugaite, Daniel Roy, and Michael Carbin · 2020
Cited alongside, same era.
Zhenyu Zhang, Xuxi Chen, Tianlong Chen, and Zhangyang Wang · 2021
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{GAN}s can play lottery tickets too
Xuxi Chen, Zhenyu Zhang, Yongduo Sui, and Tianlong Chen · 2021
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Good students play big lottery better
Haoyu Ma, Tianlong Chen, Ting-Kuei Hu, Chenyu You, Xiaohui Xie, and Zhangyang Wang · 2021
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Playing lottery tickets with vision and language
Zhe Gan, Yen-Chun Chen, Linjie Li, Tianlong Chen, Yu Cheng, Shuohang Wang, and Jingjing Liu · 2021
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A unified lottery ticket hypothesis for graph neural networks
Tianlong Chen, Yongduo Sui, Xuxi Chen, Aston Zhang, and Zhangyang Wang · 2021
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Ultra-data-efficient gan training: Drawing a lottery ticket first, then training it toughly
Tianlong Chen, Yu Cheng, Zhe Gan, Jingjing Liu, and Zhangyang Wang · 2021
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The lottery ticket hypothesis for object recognition
Sharath Girish, Shishira R Maiya, Kamal Gupta, Hao Chen, Larry Davis, and Abhinav Shrivastava · 2021
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Earlybert: Efficient bert training via early-bird lottery tickets
Xiaohan Chen, Yu Cheng, Shuohang Wang, Zhe Gan, Zhangyang Wang, and Jingjing Liu · 2021
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