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Few-shot learning is an important area of research.
The use of multiple measurements in taxonomic problems
Ronald A Fisher · 1936
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Learning a similarity metric discriminatively, with application to face verification
Sumit Chopra, Raia Hadsell, and Yann Lecun · 2005
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Visualizing data using t-SNE
Laurens van der Maaten and Geoffrey Hinton · 2008
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ImageNet: A Large-Scale Hierarchical Image Database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton · 2012
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
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Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
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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, Alexander C. Berg, and Li Fei-Fei · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Matching Networks for One Shot Learning
Oriol Vinyals, Charles Blundell, Timothy Lillicrap, Koray Kavukcuoglu, and Daan Wierstra · 2016
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Wide residual networks
Sergey Zagoruyko and Nikos Komodakis · 2016
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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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Low-shot Visual Recognition by Shrinking and Hallucinating Features
Bharath Hariharan and Ross Girshick · 2017
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Meta-SGD: Learning to Learn Quickly for Few-Shot Learning
Zhenguo Li, Fengwei Zhou, Fei Chen, and Hang Li · 2017
Cited alongside, same era.
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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Few-shot Learning with Graph Neural Networks
Victor Garcia and Joan Bruna · 2018
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Agilenet: Lightweight dictionary-based few-shot learning
Mohammad Ghasemzadeh, Fang Lin, Bita Darvish Rouhani, Farinaz Koushanfar, and Ke Huang · 2018
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Dynamic Few-Shot Visual Learning without Forgetting
Spyros Gidaris and Nikos Komodakis · 2018
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Meta-Learning for Semi-supervised Few-Shot Classification
Mengye Ren, Eleni Triantafillou, Sachin Ravi, Jake Snell, Kevin Swersky, Joshua B. Tenenbaum, Hugo Larochelle, and Richard S. Zemel · 2018
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Learning to compare: Relation network for few-shot learning
Flood Sung, Yongxin Yang, Li Zhang, Tao Xiang, Philip H.S. Torr, and Timothy M. Hospedales · 2018
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Improving Generalization via Scalable Neighborhood Component Analysis
Zhirong Wu, Alexei A. Efros, , and Stella X. Yu · 2018
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Variadic learning by bayesian nonparametric deep embedding
Kelsey R Allen, Hanul Shin, Evan Shelhamer, and Josh B. Tenenbaum · 2019
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A closer look at few-shot classification
Wei-Yu Chen, Yen-Cheng Liu, Zsolt Kira, Yu-Chiang Frank Wang, and Jia-Bin Huang · 2019
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Image deformation meta-networks for one-shot learning
Zitian Chen, Yanwei Fu, Yu-Xiong Wang, Lin Ma, Wei Liu, and Martial Hebert · 2019
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Neural network encapsulation
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Transductive Propagation Network for Few-shot Learning
Yanbin Liu, Juho Lee, Minseop Park, Saehoon Kim, and Yi Yang · 2018
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A Simple Neural Attentive Meta-Learner
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On First-Order Meta-Learning Algorithms
Alex Nichol, Joshua Achiam, and John Schulman · 2018
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TADAM: Task dependent adaptive metric for improved few-shot learning
Boris N. Oreshkin, Pau Rodriguez, and Alexandre Lacoste · 2018
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Few-Shot Image Recognition by Predicting Parameters from Activations
Siyuan Qiao, Chenxi Liu, Wei Shen, and Alan Yuille · 2018
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Hybrid Attention-Based Prototypical Networks for Noisy Few-Shot Relation Classification
Tianyu Gao, Xu Han, Zhiyuan Liu, and Maosong Sun · 2019
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Meta-learning probabilistic inference for prediction
Jonathan Gordon, John Bronskill, Matthias Bauer, Sebastian Nowozin, and Richard Turner · 2019
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Meta-learning with individualized feature space for few-shot classification
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Learning to learn with conditional class dependencies
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Network reparameterization for unseen class categorization
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Meta-learning with latent embedding optimization
Andrei A. Rusu, Dushyant Rao, Jakub Sygnowski, Oriol Vinyals, Razvan Pascanu, Simon Osindero, and Raia Hadsell · 2019
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Projective subspace networks for few-shot learning
Christian Simon, Piotr Koniusz, and Mehrtash Harandi · 2019
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