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The competitive MNIST handwritten digit recognition benchmark has a long history of broken records since 1998.
Beyond Regression: New Tools for Prediction and Analysis in the Behavioral Sciences
Paul J. Werbos · 1974
Earlier work this paper cites.
Une procédure d’apprentissage pour réseau a seuil asymmetrique (a learning scheme for asymmetric threshold networks)
Yann LeCun · 1985
Earlier work this paper cites.
Learning internal representations by error propagation
D. E. Rumelhart, Geoffrey E. Hinton, and Ronald. J. Williams · 1986
Earlier work this paper cites.
Bagging predictors
Leo Breiman · 1996
Earlier work this paper cites.
Gradient-based learning applied to document recognition
Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner · 1998
Cited alongside, same era.
Best practices for convolutional neural networks applied to visual document analysis
Patrice Y. Simard, Dave. Steinkraus, and John C. Platt · 2003
Cited alongside, same era.
Pattern Recognition and Machine Learning
Christopher M. Bishop · 2006
Cited alongside, same era.
Combining multiple classifiers for faster optical character recognition
Kumar Chellapilla, Michael Shilman, and Patrice Simard · 2006
Cited alongside, same era.
Efficient learning of sparse representations with an energy-based model
Marc’Aurelio Ranzato, Christopher Poultney, Sumit Chopra, and Yann LeCun · 2006
Later among the works it cites.
Unsupervised learning of invariant feature hierarchies with applications to object recognition
Marc’Aurelio Ranzato, Fu Jie Huang, Y-Lan Boureau, and Yann LeCun · 2007
Later among the works it cites.
Deep big simple neural nets for handwritten digit recognition
Dan C. Ciresan, Ueli Meier, Luca M. Gambardella, and Jürgen Schmidhuber · 2010
Later among the works it cites.
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