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Lottery Ticket Hypothesis (LTH) claims the existence of a winning ticket (i.e., a properly pruned sub-network together with original weight initialization) that can achieve competitive performance to the original dense network.
The lottery ticket hypothesis at scale
Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M. Roy, and Michael Carbin · 1903
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Sparse transfer learning via winning lottery tickets
Rahul Mehta · 1905
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Optimal transport: old and new , volume 338
Cédric Villani · 2009
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Sinkhorn distances: Lightspeed computation of optimal transport
Marco Cuturi · 2013
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Inductive representation learning on large graphs
William L. Hamilton, Zhitao Ying, and Jure Leskovec · 2017
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Semi-supervised classification with graph convolutional networks
Thomas N. Kipf and Max Welling · 2017
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Fastgcn: Fast learning with graph convolutional networks via importance sampling
Jie Chen, Tengfei Ma, and Cao Xiao · 2018
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Hyperbolic entailment cones for learning hierarchical embeddings
Octavian-Eugen Ganea, Gary Bécigneul, and Thomas Hofmann · 2018
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Graph attention networks
Petar Velickovic, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, and Yoshua Bengio · 2018
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Graph convolutional neural networks for web-scale recommender systems
Rex Ying, Ruining He, Kaifeng Chen, Pong Eksombatchai, William L. Hamilton, and Jure Leskovec · 2018
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The lottery ticket hypothesis: Finding sparse, trainable neural networks
Jonathan Frankle and Michael Carbin · 2019
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Diffusion improves graph learning
Johannes Klicpera, Stefan Weißenberger, and Stephan Günnemann · 2019
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Rethinking the value of network pruning
Zhuang Liu, Mingjie Sun, Tinghui Zhou, Gao Huang, and Trevor Darrell · 2019
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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
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Simplifying graph convolutional networks
Felix Wu, Amauri H. Souza Jr., Tianyi Zhang, Christopher Fifty, Tao Yu, and Kilian Q. Weinberger · 2019
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How powerful are graph neural networks?
Keyulu Xu, Weihua Hu, Jure Leskovec, and Stefanie Jegelka · 2019
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Graph transformer networks
Seongjun Yun, Minbyul Jeong, Raehyun Kim, Jaewoo Kang, and Hyunwoo J. Kim · 2019
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Deconstructing lottery tickets: Zeros, signs, and the supermask
Hattie Zhou, Janice Lan, Rosanne Liu, and Jason Yosinski · 2019
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Losing heads in the lottery: Pruning transformer attention in neural machine translation
Maximiliana Behnke and Kenneth Heafield · 2020
Cited alongside, same era.
Successfully applying the stabilized lottery ticket hypothesis to the transformer architecture
Christopher Brix, Parnia Bahar, and Hermann Ney · 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.
Rigging the lottery: Making all tickets winners
Utku Evci, Trevor Gale, Jacob Menick, Pablo Samuel Castro, and Erich Elsen · 2020
Cited alongside, same era.
Linear mode connectivity and the lottery ticket hypothesis
Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M. Roy, and Michael Carbin · 2020
Cited alongside, same era.
Resprop: Reuse sparsified backpropagation
Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP
Haonan Yu, Sergey Edunov, Yuandong Tian, and Ari S. Morcos · 2020
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Data-efficient gan training beyond (just) augmentations: A lottery ticket perspective
Tianlong Chen, Yu Cheng, Zhe Gan, Jingjing Liu, and Zhangyang Wang · 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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Long live the lottery: The existence of winning tickets in lifelong learning
Tianlong Chen, Zhenyu Zhang, Sijia Liu, Shiyu Chang, and Zhangyang Wang · 2021
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The elastic lottery ticket hypothesis
Xiaohan Chen, Yu Cheng, Shuohang Wang, Zhe Gan, Jingjing Liu, and Zhangyang Wang · 2021
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Gans can play lottery tickets too
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Negar Goli and Tor M. Aamodt · 2020
Cited alongside, same era.
Open graph benchmark: Datasets for machine learning on graphs
Weihua Hu, Matthias Fey, Marinka Zitnik, Yuxiao Dong, Hongyu Ren, Bowen Liu, Michele Catasta, and Jure Leskovec · 2020
Cited alongside, same era.
Predicting economic growth by region embedding: A multigraph convolutional network approach
Bo Hui, Da Yan, Wei-Shinn Ku, and Wenlu Wang · 2020
Cited alongside, same era.
Proving the lottery ticket hypothesis: Pruning is all you need
Eran Malach, Gilad Yehudai, Shai Shalev-Shwartz, and Ohad Shamir · 2020
Cited alongside, same era.
When BERT plays the lottery, all tickets are winning
Sai Prasanna, Anna Rogers, and Anna Rumshisky · 2020
Cited alongside, same era.
Sparse weight activation training
Md Aamir Raihan and Tor M. Aamodt · 2020
Cited alongside, same era.
Winning the lottery with continuous sparsification
Pedro Savarese, Hugo Silva, and Michael Maire · 2020
Cited alongside, same era.
Xuxi Chen, Zhenyu Zhang, Yongduo Sui, and Tianlong Chen · 2021
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Multi-prize lottery ticket hypothesis: Finding accurate binary neural networks by pruning A randomly weighted network
James Diffenderfer and Bhavya Kailkhura · 2021
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Winning lottery tickets in deep generative models
Neha Mukund Kalibhat, Yogesh Balaji, and Soheil Feizi · 2021
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Lottery ticket preserves weight correlation: Is it desirable or not?
Ning Liu, Geng Yuan, Zhengping Che, Xuan Shen, Xiaolong Ma, Qing Jin, Jian Ren, Jian Tang, Sijia Liu, and Yanzhi Wang · 2021
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On lottery tickets and minimal task representations in deep reinforcement learning
Marc Aurel Vischer, Robert Tjarko Lange, and Henning Sprekeler · 2021
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Mest: Accurate and fast memory-economic sparse training framework on the edge
Geng Yuan, Xiaolong Ma, Wei Niu, Zhengang Li, Zhenglun Kong, Ning Liu, Yifan Gong, Zheng Zhan, Chaoyang He, Qing Jin, et al · 2021
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Why lottery ticket wins? a theoretical perspective of sample complexity on sparse neural networks
Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, and Jinjun Xiong · 2021
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Validating the lottery ticket hypothesis with inertial manifold theory
Zeru Zhang, Jiayin Jin, Zijie Zhang, Yang Zhou, Xin Zhao, Jiaxiang Ren, Ji Liu, Lingfei Wu, Ruoming Jin, and Dejing Dou · 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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Coarsening the granularity: Towards structurally sparse lottery tickets
Tianlong Chen, Xuxi Chen, Xiaolong Ma, Yanzhi Wang, and Zhangyang Wang · 2022
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Chex: Channel exploration for cnn model compression
Zejiang Hou, Minghai Qin, Fei Sun, Xiaolong Ma, Kun Yuan, Yi Xu, Yen-Kuang Chen, Rong Jin, Yuan Xie, and Sun-Yuan Kung · 2022
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Investigating transfer learning in graph neural networks
Nishai Kooverjee, Steven James, and Terence L. van Zyl · 2022
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