Fetching the paper…
Reading the bibliography…
We consider the problem of designing models to leverage a recently introduced approximate model averaging technique called dropout.
Bagging predictors
Breiman, Leo · 1994
Earlier work this paper cites.
A model of multiplicative neural responses in parietal cortex
Salinas, E. and Abbott, L. F · 1996
Earlier work this paper cites.
On the piecewise analysis of networks of linear threshold neurons
Hahnloser, Richard H. R · 1998
Earlier work this paper cites.
Gradient-based learning applied to document recognition
LeCun, Yann, Bottou, Leon, Bengio, Yoshua, and Haffner, Patrick · 1998
Earlier work this paper cites.
General constructive representations for continuous piecewise-linear functions
Wang, Shuning · 2004
Earlier work this paper cites.
Rank, trace-norm and max-norm
Srebro, Nathan and Shraibman, Adi · 2005
Earlier work this paper cites.
What is the best multi-stage architecture for object recognition?
Jarrett, Kevin, Kavukcuoglu, Koray, Ranzato, Marc’Aurelio, and LeCun, Yann · 2009
Earlier work this paper cites.
Learning multiple layers of features from tiny images
Krizhevsky, Alex and Hinton, Geoffrey · 2009
Earlier work this paper cites.
Deep Boltzmann machines
Salakhutdinov, R. and Hinton, G.E · 2009
Cited alongside, same era.
Theano: a CPU and GPU math expression compiler
Bergstra, James, Breuleux, Olivier, Bastien, Frédéric, Lamblin, Pascal, Pascanu, Razvan, Desjardins, Guillaume, Turian, Joseph, Warde-Farley, David, and Bengio, Yoshua · 2010
Cited alongside, same era.
Deep big simple neural nets for handwritten digit recognition
Ciresan, D. C., Meier, U., Gambardella, L. M., and Schmidhuber, J · 2010
Cited alongside, same era.
Deep sparse rectifier neural networks
Glorot, Xavier, Bordes, Antoine, and Bengio, Yoshua · 2011
Cited alongside, same era.
Reading digits in natural images with unsupervised feature learning
Netzer, Y., Wang, T., Coates, A., Bissacco, A., Wu, B., and Ng, A. Y · 2011
Cited alongside, same era.
The manifold tangent classifier
Rifai, Salah, Dauphin, Yann, Vincent, Pascal, Bengio, Yoshua, and Muller, Xavier · 2011
Cited alongside, same era.
Improving neural networks by preventing co-adaptation of feature detectors
Hinton, Geoffrey E., Srivastava, Nitish, Krizhevsky, Alex, Sutskever, Ilya, and Salakhutdinov, Ruslan · 2012
Later among the works it cites.
ImageNet classification with deep convolutional neural networks
Krizhevsky, Alex, Sutskever, Ilya, and Hinton, Geoffrey · 2012
Later among the works it cites.
Convolutional neural networks applied to house numbers digit classification
Sermanet, Pierre, Chintala, Soumith, and LeCun, Yann · 2012
Later among the works it cites.
Practical bayesian optimization of machine learning algorithms
Snoek, Jasper, Larochelle, Hugo, and Adams, Ryan Prescott · 2012
Later among the works it cites.
Joint training of deep Boltzmann machines for classification
Goodfellow, Ian J., Courville, Aaron, and Bengio, Yoshua · 2013
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Deep convex net: A scalable architecture for speech pattern classification
Yu, Dong and Deng, Li · 2011
Cited alongside, same era.
Theano: new features and speed improvements
Bastien, Frédéric, Lamblin, Pascal, Pascanu, Razvan, Bergstra, James, Goodfellow, Ian, Bergeron, Arnaud, Bouchard, Nicolas, and Bengio, Yoshua · 2012
Cited alongside, same era.
Convolutional neural networks applied to house numbers digit classification
Sermanet, Pierre, Chintala, Soumith, and LeCun, Yann
Cited in the paper.
Malinowski, Mateusz and Fritz, Mario · 2013
Closest in time.
Improving neural networks with dropout
Srivastava, Nitish · 2013
Closest in time.
Stochastic pooling for regularization of deep convolutional neural networks
Zeiler, Matthew D. and Fergus, Rob · 2013
Closest in time.