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Auto-Encoders are unsupervised models that aim to learn patterns from observed data by minimizing a reconstruction cost.
Distributed representations
Geoffrey E Hinton · 1984
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Auto-association by multilayer perceptrons and singular value decomposition
H. Bourlard and Y. Kamp · 1988
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On the approximability of minimizing nonzero variables or unsatisfied relations in linear systems
Edoardo Amaldi and Viggo Kann · 1998
Earlier work this paper cites.
Independent component analysis: algorithms and applications
Aapo Hyvärinen and Erkki Oja · 2000
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Near-optimal signal recovery from random projections: Universal encoding strategies?
Emmanuel J Candes and Terence Tao · 2006
Earlier work this paper cites.
Stable signal recovery from incomplete and inaccurate measurements
Emmanuel J Candes, Justin K Romberg, and Terence Tao · 2006
Earlier work this paper cites.
Robust face recognition via sparse representation
J. Wright, A.Y. Yang, A. Ganesh, S.S. Sastry, and Yi Ma · 2009
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Linear spatial pyramid matching using sparse coding for image classification
Jianchao Yang, Kai Yu, Yihong Gong, and Thomas Huang · 2009
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Understanding the difficulty of training deep feedforward neural networks
Xavier Glorot and Yoshua Bengio · 2010
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Fast inference in sparse coding algorithms with applications to object recognition
Koray Kavukcuoglu, Marc’Aurelio Ranzato, and Yann LeCun · 2010
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Rectified linear units improve restricted boltzmann machines
Vinod Nair and Geoffrey E Hinton · 2010
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Deep sparse rectifier neural networks
Xavier Glorot, Antoine Bordes, and Yoshua Bengio · 2011
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Alireza Makhzani and Brendan Frey · 2013
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Exact solutions to the nonlinear dynamics of learning in deep linear neural networks
Andrew M Saxe, James L McClelland, and Surya Ganguli · 2013
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Zero-bias autoencoders and the benefits of co-adapting features
Roland Memisevic, Kishore Reddy Konda, and David Krueger · 2014
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When can dictionary learning uniquely recover sparse data from subsamples?
Christopher J Hillar and Friedrich T Sommer · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Unsupervised learning of sparse features for scalable audio classification
Mikael Henaff, Kevin Jarrett, Koray Kavukcuoglu, and Yann LeCun · 2011
Cited alongside, same era.
Sparse autoencoder
Andrew Ng · 2011
Cited alongside, same era.
Why regularized auto-encoders learn sparse representation?
Devansh Arpit, Yingbo Zhou, Hung Ngo, and Venu Govindaraju · 2016
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