Contractive Auto-Encoders: Explicit Invariance During Feature Extraction
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Pascal Vincent | Yoshua Bengio | Salah Rifai | Xavier Glorot | Xavier Muller | Xavier Glorot | Yoshua Bengio | Pascal Vincent | X. Muller | S. Rifai | Salah Rifai
[1] Geoffrey E. Hinton,et al. Learning representations by back-propagating errors , 1986, Nature.
[2] Geoffrey E. Hinton,et al. Learning representations by back-propagation errors, nature , 1986 .
[3] Kurt Hornik,et al. Neural networks and principal component analysis: Learning from examples without local minima , 1989, Neural Networks.
[4] Christopher M. Bishop,et al. Advances in Neural Information Processing Systems 8 (NIPS 1995) , 1991 .
[5] Yann LeCun,et al. Tangent Prop - A Formalism for Specifying Selected Invariances in an Adaptive Network , 1991, NIPS.
[6] Christopher M. Bishop,et al. Current address: Microsoft Research, , 2022 .
[7] David J. Field,et al. Sparse coding with an overcomplete basis set: A strategy employed by V1? , 1997, Vision Research.
[8] Nathalie Japkowicz,et al. Nonlinear Autoassociation Is Not Equivalent to PCA , 2000, Neural Computation.
[9] Ronald,et al. Learning representations by backpropagating errors , 2004 .
[10] Yoshua Bengio,et al. Greedy Layer-Wise Training of Deep Networks , 2006, NIPS.
[11] Yee Whye Teh,et al. A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.
[12] Honglak Lee,et al. Sparse deep belief net model for visual area V2 , 2007, NIPS.
[13] Yoshua Bengio,et al. An empirical evaluation of deep architectures on problems with many factors of variation , 2007, ICML '07.
[14] Yoshua. Bengio,et al. Learning Deep Architectures for AI , 2007, Found. Trends Mach. Learn..
[15] Jason Weston,et al. Deep learning via semi-supervised embedding , 2008, ICML '08.
[16] Honglak Lee,et al. Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations , 2009, ICML '09.
[17] Yann LeCun,et al. What is the best multi-stage architecture for object recognition? , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[18] R. Fergus,et al. Learning invariant features through topographic filter maps , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[19] Alex Krizhevsky,et al. Learning Multiple Layers of Features from Tiny Images , 2009 .
[20] Pascal Vincent,et al. Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion , 2010, J. Mach. Learn. Res..