An Ensemble of Simple Convolutional Neural Network Models for MNIST Digit Recognition

L. Breiman, “Bagging Predictors,” in Machine Learning , 24(2):123-140 (1996)

1996

Earlier work this paper cites.

Y. Freund and R. E. Shapire, “Discussion of additive logistic regression: A statistical view of boosting,” in Annals of Statistics , 28:337-374 (2000)

2000

Earlier work this paper cites.

J. Friedman, “Greedy function approximation: a gradient boosting machine,” Annals of statistics , 1189–1232 (2001)

2001

Earlier work this paper cites.

M. Ranzato, F. J. Huang, Y. L. Boureau, and Y. LeCun, “Unsupervised learning of invariant feature hierarchies with applications to object recognition,” in Proc. of the Conference on Computer Vision and Pattern Recognition (CVPR) , pp. 1-8 (2007)

2007

Earlier work this paper cites.

S. Santurkar, D. Tsipras, A. Ilyas, and A. Madry, “How does batch normalization help optimization?,” in Advances in Neural Information Processing Systems (2018)

Original

2008

Earlier work this paper cites.

Y. Lecun, C. Cortes, and C. J. Burges. “MNIST handwritten digit database”. In: ATT Labs [Online]. Available: http://yann.lecun.com/exdb/mnist (2010)

2010

Earlier work this paper cites.

D. Ciresan, U. Meier, and J. Schmidhuber, “Multi-column deep neural networks for image classification,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2012)

2012

Earlier work this paper cites.

L. Wan, M. Zeiler, S. Zhang, Y. LeCun, and R. Fergus, “Regularization of Neural Networks using DropConnect,” in Proc. International Conference on Machine Learning (ICML) (2013)

2013

Cited alongside, same era.

S. Ioffe and C. Szegedy, “Batch normalization: Accelerating deep network training by reducing internal covariate shift,” arXiv preprint arXiv:1502.03167 (2015)

Original

2015

Cited alongside, same era.

S. Sabour, N. Frosst, and G. E. Hinton, “Dynamic routing between capsules,” in Advances in Neural Information Processing Systems (NeurIPS) , pp. 3859-3869 (2017)

2017

Cited alongside, same era.

G. Ke, Q. Meng, T. Finley, T. Wang, W. Chen, W. Ma, Q. Ye, T. Liu, “LightGBM: A highly efficient gradient boosting decision tree,” in Advances in Neural Information Processing Systems , 3149-3157 (2017)

2017

Cited alongside, same era.

J. Bjorck, C. Gomes, B. Selman, K. Q. Weinberger, “Understanding Batch Normalization," in Advances in Neural Information Processing Systems (2018)

2018

Later among the works it cites.

A. Paszke, S. Gross, F. Massa, A. Lerer, J. Bradbury, G. Chanan, T. Killeen, Z. Lin, N, Gimelshein, L. Antiga, A. Desmaison, A. Kopf, E. Yang, Z. DeVito, M. Raison, A. Tejani, S. Chilamkurthy, B. Steiner, L. Fang, J. Bai, and S. Chintala, “PyTorch: An Imperative Style, High-Performance Deep Learning Library,” in Advances in Neural Information Processing Systems (NeurIPS) (2019)

2019

Later among the works it cites.

E. D. Cubuk, B. Zoph, D. Mane, V. Vasudevan, and Q. V. Le, “AutoAugment: Learning augmentation policies from data,” in Proc. of the Conference on Computer Vision and Pattern Recognition (CVPR) , 113-123 (2019)

2019

Later among the works it cites.

E. D. Cubuk, B. Zoph, J. Shlens, Q. V. Le, “Randaugment: Practical automated data augmentation with a reduced search space,” arXiv preprint arXiv:1909.13719 (2019)

Original