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Learning from a few examples remains a key challenge in machine learning.
Building a large annotated corpus of english: The penn treebank
MP Marcus, MA Marcinkiewicz, and B Santorini · 1993
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Locally weighted learning
C Atkeson, A Moore, and S Schaal · 1997
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Long short-term memory
S Hochreiter and J Schmidhuber · 1997
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Neighbourhood component analysis
S Roweis, G Hinton, and R Salakhutdinov · 2004
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Learning a nonlinear embedding by preserving class neighbourhood structure
R Salakhutdinov and G Hinton · 2007
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Distance metric learning for large margin nearest neighbor classification
K Weinberger and L Saul · 2009
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Convolutional deep belief networks on cifar-10
A Krizhevsky and G Hinton · 2010
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Recurrent neural network based language model
T Mikolov, M Karafiát, L Burget, J Cernockỳ, and S Khudanpur · 2010
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One shot learning of simple visual concepts
BM Lake, R Salakhutdinov, J Gross, and J Tenenbaum · 2011
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Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups
G Hinton et al · 2012
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Imagenet classification with deep convolutional neural networks
A Krizhevsky, I Sutskever, and G Hinton · 2012
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Zero-shot learning by convex combination of semantic embeddings
M Norouzi, T Mikolov, S Bengio, Y Singer, J Shlens, A Frome, G Corrado, and J Dean · 2013
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Neural machine translation by jointly learning to align and translate
D Bahdanau, K Cho, and Y Bengio · 2014
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Decaf: A deep convolutional activation feature for generic visual recognition
J Donahue, Y Jia, O Vinyals, J Hoffman, N Zhang, E Tzeng, and T Darrell · 2014
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A Graves, G Wayne, and I Danihelka · 2014
Cited alongside, same era.
The goldilocks principle: Reading children’s books with explicit memory representations
F Hill, A Bordes, S Chopra, and J Weston · 2015
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Deep metric learning using triplet network
E Hoffer and N Ailon · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
S Ioffe and C Szegedy · 2015
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Siamese neural networks for one-shot image recognition
G Koch, R Zemel, and R Salakhutdinov · 2015
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ImageNet Large Scale Visual Recognition Challenge
O Russakovsky, J Deng, H Su, J Krause, S Satheesh, S Ma, Z Huang, A Karpathy, A Khosla, M Bernstein, A Berg, and L Fei-Fei · 2015
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K Simonyan and A Zisserman · 2014
Cited alongside, same era.
Sequence to sequence learning with neural networks
I Sutskever, O Vinyals, and QV Le · 2014
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Memory networks
J Weston, S Chopra, and A Bordes · 2014
Cited alongside, same era.
Recurrent neural network regularization
W Zaremba, I Sutskever, and O Vinyals · 2014
Cited alongside, same era.
Teaching machines to read and comprehend
K Hermann, T Kocisky, E Grefenstette, L Espeholt, W Kay, M Suleyman, and P Blunsom · 2015
Cited alongside, same era.
C Szegedy, W Liu, Y Jia, P Sermanet, S Reed, D Anguelov, D Erhan, V Vanhoucke, and A Rabinovich · 2015
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Rethinking the inception architecture for computer vision
C Szegedy, V Vanhoucke, S Ioffe, J Shlens, and Z Wojna · 2015
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Order matters: Sequence to sequence for sets
O Vinyals, S Bengio, and M Kudlur · 2015
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Pointer networks
O Vinyals, M Fortunato, and N Jaitly · 2015
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Meta-learning with memory-augmented neural networks
A Santoro, S Bartunov, M Botvinick, D Wierstra, and T Lillicrap · 2016
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