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Transfer learning through fine-tuning a pre-trained neural network with an extremely large dataset, such as ImageNet, can significantly accelerate training while the accuracy is frequently bottlenecked by the limited dataset size of the new target task.
Multitask learning
Rich Caruana · 1997
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A fast learning algorithm for deep belief nets
Geoffrey E Hinton, Simon Osindero, and Yee-Whye Teh · 2006
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Greedy layer-wise training of deep networks
Yoshua Bengio, Pascal Lamblin, Dan Popovici, and Hugo Larochelle · 2007
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A survey on transfer learning
Sinno Jialin Pan, Qiang Yang, et al · 2010
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Parameter transfer unit for deep neural networks
Yinghua Zhang, Yu Zhang, and Qiang Yang · 2011
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Decaf: A deep convolutional activation feature for generic visual recognition
Jeff Donahue, Yangqing Jia, Oriol Vinyals, Judy Hoffman, Ning Zhang, Eric Tzeng, and Trevor Darrell · 2014
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Recurrent models of visual attention
Volodymyr Mnih, Nicolas Heess, Alex Graves, et al · 2014
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Fitnets: Hints for thin deep nets
Adriana Romero, Nicolas Ballas, Samira Ebrahimi Kahou, Antoine Chassang, Carlo Gatta, and Yoshua Bengio · 2014
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How transferable are features in deep neural networks?
Jason Yosinski, Jeff Clune, Yoshua Bengio, and Hod Lipson · 2014
Cited alongside, same era.
Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2015
Cited alongside, same era.
Show, attend and tell: Neural image caption generation with visual attention
Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhudinov, Rich Zemel, and Yoshua Bengio · 2015
Cited alongside, same era.
Deep residual learning for image recognition
Kaiming he, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Cited alongside, same era.
What makes imagenet good for transfer learning?
Minyoung Huh, Pulkit Agrawal, and Alexei A Efros · 2016
Cited alongside, same era.
Borrowing treasures from the wealthy: Deep transfer learning through selective joint fine-tuning
Weifeng Ge and Yizhou Yu · 2017
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Overcoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, et al · 2017
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Learning without forgetting
Zhizhong Li and Derek Hoiem · 2017
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Sparse deep transfer learning for convolutional neural network
Jiaming Liu, Yali Wang, and Yu Qiao · 2017
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A gift from knowledge distillation: Fast optimization, network minimization and transfer learning
Junho Yim, Donggyu Joo, Jihoon Bae, and Junmo Kim · 2017
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Large scale fine-grained categorization and domain-specific transfer learning
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Stacked attention networks for image question answering
Zichao Yang, Xiaodong He, Jianfeng Gao, Li Deng, and Alex Smola · 2016
Cited alongside, same era.
Sergey Zagoruyko and Nikos Komodakis · 2016
Cited alongside, same era.
Exploiting convolution filter patterns for transfer learning
Mehmet Aygun, Yusuf Aytar, and Hazim Kemal Ekenel · 2017
Cited alongside, same era.
Yin Cui, Yang Song, Chen Sun, Andrew Howard, and Serge Belongie · 2018
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Explicit inductive bias for transfer learning with convolutional networks
Xuhong Li, Yves Grandvalet, and Franck Davoine · 2018
Later among the works it cites.