Fetching the paper…
Reading the bibliography…
Recently, it has been observed that when representations are learnt in a way that encourages sparsity, improved performance is obtained on classification tasks.
Sparse coding with an overcomplete basis set: A strategy employed by v1?
Olshausen, Bruno A and Field, David J · 1997
Earlier work this paper cites.
Method of optimal directions for frame design
Engan, Kjersti, Aase, Sven Ole, and Hakon Husoy, J · 1999
Earlier work this paper cites.
Optimally sparse representation in general (nonorthogonal) dictionaries via ℓ1 minimization
Donoho, David L and Elad, Michael · 2003
Earlier work this paper cites.
Learning methods for generic object recognition with invariance to pose and lighting
LeCun, Yann, Huang, Fu Jie, and Bottou, Leon · 2004
Earlier work this paper cites.
K-svd: Design of dictionaries for sparse representation
Aharon, Michal, Elad, Michael, and Bruckstein, Alfred · 2005
Earlier work this paper cites.
Greedy layer-wise training of deep networks
Bengio, Yoshua, Lamblin, Pascal, Popovici, Dan, and Larochelle, Hugo · 2007
Earlier work this paper cites.
Sparse deep belief net model for visual area v2
Lee, Honglak, Ekanadham, Chaitanya, and Ng, Andrew · 2007
Earlier work this paper cites.
Signal recovery from random measurements via orthogonal matching pursuit
Tropp, Joel A and Gilbert, Anna C · 2007
Cited alongside, same era.
Kernel codebooks for scene categorization
Van Gemert, Jan C, Geusebroek, Jan-Mark, Veenman, Cor J, and Smeulders, Arnold WM · 2008
Cited alongside, same era.
Extracting and composing robust features with denoising autoencoders
Vincent, Pascal, Larochelle, Hugo, Bengio, Yoshua, and Manzagol, Pierre-Antoine · 2008
Cited alongside, same era.
Iterative hard thresholding for compressed sensing
Blumensath, Thomas and Davies, Mike E · 2009
Cited alongside, same era.
Coherence analysis of iterative thresholding algorithms
Maleki, Arian · 2009
Cited alongside, same era.
3d object recognition with deep belief nets
Nair, Vinod and Hinton, Geoffrey E · 2009
Learning fast approximations of sparse coding
Gregor, Karol and LeCun, Yann · 2010
Later among the works it cites.
Fast inference in sparse coding algorithms with applications to object recognition
Kavukcuoglu, Koray, Ranzato, Marc’Aurelio, and LeCun, Yann · 2010
Later among the works it cites.
Efficient learning of deep boltzmann machines
Salakhutdinov, Ruslan and Larochelle, Hugo · 2010
Later among the works it cites.
Gnumpy: an easy way to use gpu boards in python
Tieleman, Tijmen · 2010
Later among the works it cites.
The importance of encoding versus training with sparse coding and vector quantization
Coates, Adam and Ng, Andrew · 2011
Later among the works it cites.
An analysis of single-layer networks in unsupervised feature learning
Coates, Adam, Ng, Andrew Y, and Lee, Honglak · 2011
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Why does unsupervised pre-training help deep learning?
Erhan, Dumitru, Bengio, Yoshua, Courville, Aaron, Manzagol, Pierre-Antoine, Vincent, Pascal, and Bengio, Samy · 2010
Cited alongside, same era.
Later among the works it cites.
Improving neural networks by preventing co-adaptation of feature detectors
Hinton, Geoffrey E, Srivastava, Nitish, Krizhevsky, Alex, Sutskever, Ilya, and Salakhutdinov, Ruslan R · 2012
Later among the works it cites.