Matching networks for one shot learning

Advances in Neural Information Processing Systems

Volumn , Issue , 2016, Pages 3637-3645

  Vinyals, Oriol ^a   Blundell, Charles ^a   Lillicrap, Timothy ^a   Kavukcuoglu, Koray ^a   Wierstra, Daan ^a  

^a DEEPMIND   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING SYSTEMS;

EXTERNAL MEMORY; LANGUAGE MODEL; LEARNING PARADIGMS; MATCHING NETWORKS; METRIC LEARNING; ONE-SHOT LEARNING; SATISFACTORY SOLUTIONS; SHOT ACCURACY;

MODELING LANGUAGES;

EID: 85018863845     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (30)

1. C Atkeson, A Moore, and S Schaal. Locally weighted learning. Artificial Intelligence Review, 1997.
2. D Bahdanau, K Cho, and Y Bengio. Neural machine translation by jointly learning to align and translate. ICLR, 2014.
3. J Donahue, Y Jia, O Vinyals, J Hoffman, N Zhang, E Tzeng, and T Darrell. Decaf: A deep convolutional activation feature for generic visual recognition. In ICML, 2014.
4. A Graves, G Wayne, and I Danihelka. Neural turing machines. arXiv preprint arXiv: 1410.5401, 2014.
5. K Hermann, T Kocisky, E Grefenstette, L Espeholt, W Kay, M Suleyman, and P Blunsom. Teaching machines to read and comprehend. In NIPS, 2015.
6. F Hill, A Bordes, S Chopra, and J Weston. The goldilocks principle: Reading children's books with explicit memory representations. arXiv preprint arXiv: 1511.02301, 2015.
7. G Hinton et al. Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups. Signal Processing Magazine, IEEE, 2012.
8. S Hochreiter and J Schmidhuber. Long short-term memory. Neural computation, 1997.
9. E Hoffer and N Ailon. Deep metric learning using triplet network. Similarity-Based Pattern Recognition, 2015.
10. S Ioffe and C Szegedy. Batch normalization: Accelerating deep network training by reducing internal covariate shift. arXiv preprint arXiv: 1502.03167, 2015.
11. G Koch, R Zemel, and R Salakhutdinov. Siamese neural networks for one-shot image recognition. In ICML Deep Learning workshop, 2015.
12. A Krizhevsky and G Hinton. Convolutional deep belief networks on cifar-10. Unpublished, 2010.
13. A Krizhevsky, I Sutskever, and G Hinton. Imagenet classification with deep convolutional neural networks. In NIPS, 2012.
14. BM Lake, R Salakhutdinov, J Gross, and J Tenenbaum. One shot learning of simple visual concepts. In CogSci, 2011.
15. MP Marcus, MA Marcinkiewicz, and B Santorini. Building a large annotated corpus of english: The penn treebank. Computational linguistics, 1993.
16. T Mikolov, M Karafiát, L Burget, J Cernockỳ, and S Khudanpur. Recurrent neural network based language model. In INTERSPEECH, 2010.
17. M Norouzi, T Mikolov, S Bengio, Y Singer, J Shlens, A Frome, G Corrado, and J Dean. Zero-shot learning by convex combination of semantic embeddings. arXiv preprint arXiv: 1312.5650, 2013.
18. S Roweis, G Hinton, and R Salakhutdinov. Neighbourhood component analysis. NIPS, 2004.
19. 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. ImageNet Large Scale Visual Recognition Challenge. IJCV, 2015.
20. R Salakhutdinov and G Hinton. Learning a nonlinear embedding by preserving class neighbourhood structure. In AISTATS, 2007.
21. A Santoro, S Bartunov, M Botvinick, D Wierstra, and T Lillicrap. Meta-learning with memory-augmented neural networks. In ICML, 2016.
22. K Simonyan and A Zisserman. Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv: 1409.1556, 2014.
23. I Sutskever, O Vinyals, and QV Le. Sequence to sequence learning with neural networks. In NIPS, 2014.
24. C Szegedy, W Liu, Y Jia, P Sermanet, S Reed, D Anguelov, D Erhan, V Vanhoucke, and A Rabinovich. Going deeper with convolutions. In CVPR, 2015.
25. C Szegedy, V Vanhoucke, S Ioffe, J Shlens, and Z Wojna. Rethinking the inception architecture for computer vision. arXiv preprint arXiv: 1512.00567, 2015.
26. O Vinyals, S Bengio, and M Kudlur. Order matters: Sequence to sequence for sets. arXiv preprint arXiv: 1511.06391, 2015.
27. O Vinyals, M Fortunato, and N Jaitly. Pointer networks. In NIPS, 2015.
28. K Weinberger and L Saul. Distance metric learning for large margin nearest neighbor classification. JMLR, 2009.
29. J Weston, S Chopra, and A Bordes. Memory networks. ICLR, 2014.
30. W Zaremba, I Sutskever, and O Vinyals. Recurrent neural network regularization. arXiv preprint arXiv: 1409.2329, 2014.