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The ability to learn from a small number of examples has been a difficult problem in machine learning since its inception.
Caltech-256 object category dataset
G. Griffin, A. Holub, and P. Perona · 2007
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P. Welinder, S. Branson, T. Mita, C. Wah, F. Schroff, S. Belongie, and P. Perona · 2010
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Deep learning of representations for unsupervised and transfer learning
Yoshua Bengio et al · 2011
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A survey on metric learning for feature vectors and structured data
Aurélien Bellet, Amaury Habrard, and Marc Sebban · 2013
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On the importance of initialization and momentum in deep learning
Ilya Sutskever, James Martens, George Dahl, and Geoffrey Hinton · 2013
Earlier work this paper cites.
TensorFlow: Large-scale machine learning on heterogeneous systems, 2015
Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mané, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng · 2015
Cited alongside, same era.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
Cited alongside, same era.
Siamese neural networks for one-shot image recognition
Gregory Koch · 2015
Cited alongside, same era.
Human-level concept learning through probabilistic program induction
Brenden M. Lake, Ruslan Salakhutdinov, and Joshua B. Tenenbaum · 2015
Cited alongside, same era.
Visual genome: Connecting language and vision using crowdsourced dense image annotations
Ranjay Krishna, Yuke Zhu, Oliver Groth, Justin Johnson, Kenji Hata, Joshua Kravitz, Stephanie Chen, Yannis Kalanditis, Li-Jia Li, David A Shamma, Michael Bernstein, and Li Fei-Fei · 2016
Optimization as a model for few-shot learning
Sachin Ravi and Hugo Larochelle · 2016
Later among the works it cites.
Matching networks for one shot learning
Oriol Vinyals, Charles Blundell, Timothy P. Lillicrap, Koray Kavukcuoglu, and Daan Wierstra · 2016
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Generative adversarial residual pairwise networks for one shot learning
Akshay Mehrotra and Ambedkar Dukkipati · 2017
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A simple neural network module for relational reasoning
A. Santoro, D. Raposo, D. G. T. Barrett, M. Malinowski, R. Pascanu, P. Battaglia, and T. Lillicrap · 2017
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Few-Shot Learning Through an Information Retrieval Lens
E. Triantafillou, R. Zemel, and R. Urtasun · 2017
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Cited alongside, same era.