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Convolutional Neural Networks (CNNs) have become the state-of-the-art in supervised learning vision tasks.
K. Hornik, M. Stinchcombe, and H. White, “Multilayer feedforward networks are universal approximators,” Neural networks
1989
Earlier work this paper cites.
American Mathematical Society, 1996
F. R. K. Chung, Spectral Graph Theory (CBMS Regional Conference Series in Mathematics, No. 92) · 1996
Earlier work this paper cites.
Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner, “Gradient-based learning applied to document recognition,” Proceedings of the IEEE
1998
Earlier work this paper cites.
Y. LeCun, C. Cortes, and C. J. Burges, “The mnist database of handwritten digits,” 1998
1998
Earlier work this paper cites.
A. Y. Ng, “Feature selection, l 1 vs. l 2 regularization, and rotational invariance,” in Proceedings of the twenty-first international conference on Machine learning
2004
Earlier work this paper cites.
L. Bottou, “Large-scale machine learning with stochastic gradient descent,” in Proceedings of COMPSTAT’2010
2010
Cited alongside, same era.
X. Glorot, A. Bordes, and Y. Bengio, “Deep sparse rectifier neural networks,” in International Conference on Artificial Intelligence and Statistics
2011
Cited alongside, same era.
A. Krizhevsky, I. Sutskever, and G. E. Hinton, “Imagenet classification with deep convolutional neural networks,” in Advances in neural information processing systems
2012
Cited alongside, same era.
D. I. Shuman, S. K. Narang, P. Frossard, A. Ortega, and P. Vandergheynst, “The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains,” IEEE Signal Processing Magazine
2013
Cited alongside, same era.
I. Sutskever, J. Martens, G. Dahl, and G. Hinton, “On the importance of initialization and momentum in deep learning,” in Proceedings of the 30th international conference on machine learning (ICML-13)
2013
Later among the works it cites.
B. Graham, “Spatially-sparse convolutional neural networks,” arXiv preprint arXiv:1409.6070
2014
Later among the works it cites.
2015
Later among the works it cites.
J. Masci, D. Boscaini, M. Bronstein, and P. Vandergheynst, “Shapenet: Convolutional neural networks on non-euclidean manifolds,” tech. rep., 2015
2015
Later among the works it cites.
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2013
Cited alongside, same era.