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In few-shot classification, we are interested in learning algorithms that train a classifier from only a handful of labeled examples.
Least squares quantization in pcm
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Unsupervised word sense disambiguation rivaling supervised methods
David Yarowsky · 1995
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Lifelong learning algorithms
Sebastian Thrun · 1998
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Statistical Learning Theory
V.N. Vapnik · 1998
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Transductive inference for text classification using support vector machines
Thorsten Joachims · 1999
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Learning to learn using gradient descent
Sepp Hochreiter, A Steven Younger, and Peter R Conwell · 2001
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Improving k-means by outlier removal
Ville Hautamäki, Svetlana Cherednichenko, Ismo Kärkkäinen, Tomi Kinnunen, and Pasi Fränti · 2005
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Semi-supervised self-training of object detection models
Chuck Rosenberg, Martial Hebert, and Henry Schneiderman · 2005
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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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Semi-Supervised Learning
Olivier Chapelle, Bernhard Schölkopf, and Alexander Zien · 2010
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One shot learning of simple visual concepts
Brenden M. Lake, Ruslan Salakhutdinov, Jason Gross, and Joshua B. Tenenbaum · 2011
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Sanjay Chawla and Aristides Gionis · 2013
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Adam: A method for stochastic optimization
Diederik Kingma and Jimmy Ba · 2014
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Transductive multi-view zero-shot learning
Yanwei Fu, Timothy M. Hospedales, Tao Xiang, and Shaogang Gong · 2015
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Siamese neural networks for one-shot image recognition
Gregory Koch, Richard Zemel, and Ruslan Salakhutdinov · 2015
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Matching networks for one shot learning
Oriol Vinyals, Charles Blundell, Tim Lillicrap, Koray Kavukcuoglu, and Daan Wierstra · 2016
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Semi-supervised learning literature survey
Xiaojin Zhu · 2016
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Learning algorithms for active learning
Philip Bachman, Alessandro Sordoni, and Adam Trischler · 2017
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Model-agnostic meta-learning for fast adaptation of deep networks
Chelsea Finn, Pieter Abbeel, and Sergey Levine · 2017
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Local search methods for k-means with outliers
Shalmoli Gupta, Ravi Kumar, Kefu Lu, Benjamin Moseley, and Sergei Vassilvitskii · 2017
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Meta-learning with temporal convolutions
Nikhil Mishra, Mostafa Rohaninejad, Xi Chen, and Pieter Abbeel · 2017
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Imagenet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, et al · 2015
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Using fast weights to attend to the recent past
Jimmy Ba, Geoffrey E. Hinton, Volodymyr Mnih, Joel Z. Leibo, and Catalin Ionescu · 2016
Cited alongside, same era.
One-shot learning with memory-augmented neural networks
Adam Santoro, Sergey Bartunov, Matthew Botvinick, Daan Wierstra, and Timothy P. Lillicrap · 2016
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Optimization as a model for few-shot learning
Sachin Ravi and Hugo Larochelle · 2017
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Prototypical networks for few-shot learning
Jake Snell, Kevin Swersky, and Richard S. Zemel · 2017
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