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The recently proposed Lottery Ticket Hypothesis of Frankle and Carbin (2019) suggests that the performance of over-parameterized deep networks is due to the random initialization seeding the network with a small fraction of favorable weights.
The lottery ticket hypothesis at scale
Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M. Roy, and Michael Carbin · 1903
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Optimal brain damage
Yann Le Cun, 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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A survey on transfer learning
Sinno Jialin Pan and Qiang Yang · 2010
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Dropout: A simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
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Learning both weights and connections for efficient neural networks
Song Han, Jeff Pool, John Tran, and William J. Dally · 2015
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Statistical Learning with Sparsity: The Lasso and Generalizations (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)
Trevor Hastie, Robert Tibshirani, and Martin Wainwright · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
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Variational dropout and the local reparameterization trick, 2015
Diederik P. Kingma, Tim Salimans, and Max Welling · 2015
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Squeezenet: Alexnet-level accuracy with 50x fewer parameters and < < 0.5mb model size
Forrest N. Iandola, Song Han, Matthew W. Moskewicz, Khalid Ashraf, William J. Dally, and Kurt Keutzer · 2016
Cited alongside, same era.
Pruning filters for efficient convnets
Hao Li, Asim Kadav, Igor Durdanovic, Hanan Samet, and Hans Peter Graf · 2016
Cited alongside, same era.
Residual networks behave like ensembles of relatively shallow networks
Andreas Veit, Michael J Wilber, and Serge Belongie · 2016
Cited alongside, same era.
Morphnet: Fast and simple resource-constrained structure learning of deep networks, 2017
Ariel Gordon, Elad Eban, Ofir Nachum, Bo Chen, Hao Wu, Tien-Ju Yang, and Edward Choi · 2017
Cited alongside, same era.
Mobilenets: Efficient convolutional neural networks for mobile vision applications
Amc: Automl for model compression and acceleration on mobile devices
Yihui He, Ji Lin, Zhijian Liu, Hanrui Wang, Li-Jia Li, and Song Han · 2018
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Regularization for deep learning: A taxonomy, 2018
Jan Kukačka, Vladimir Golkov, and Daniel Cremers · 2018
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Implicit acceleration by overparameterization: An empirical perspective
Rahul Mehta · 2018
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Mobilenetv2: Inverted residuals and linear bottlenecks
Mark B. Sandler, Andrew G. Howard, Menglong Zhu, Andrey Zhmoginov, and Liang-Chieh Chen · 2018
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The lottery ticket hypothesis: Finding sparse, trainable neural networks
Jonathan Frankle and Michael Carbin · 2019
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Andrew G. Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, and Hartwig Adam · 2017
Cited alongside, same era.
Learning sparse neural networks through l 0 l_{0} regularization, 2017
Christos Louizos, Max Welling, and Diederik P. Kingma · 2017
Cited alongside, same era.
Variational dropout sparsifies deep neural networks, 2017
Dmitry Molchanov, Arsenii Ashukha, and Dmitry Vetrov · 2017
Cited alongside, same era.
Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms
Han Xiao, Kashif Rasul, and Roland Vollgraf · 2017
Cited alongside, same era.
On the optimization of deep networks: Implicit acceleration by overparameterization
Sanjeev Arora, Nadav Cohen, and Elad Hazan · 2018
Cited alongside, same era.
Learning methods for generic object recognition with invariance to pose and lighting
Yann LeCun, Fu Jie Huang, Leon Bottou, et al
Cited in the paper.
Trevor Gale, Erich Elsen, and Sara Hooker · 2019
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SNIP: SINGLE-SHOT NETWORK PRUNING BASED ON CONNECTION SENSITIVITY
Namhoon Lee, Thalaiyasingam Ajanthan, and Philip Torr · 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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Deconstructing lottery tickets: Zeros, signs, and the supermask
Hattie Zhou, Janice Lan, Rosanne Liu, and Jason Yosinski · 2019
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