The Difficulty of Training Deep Architectures and the Effect of Unsupervised Pre-Training
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Pascal Vincent | Samy Bengio | Yoshua Bengio | Dumitru Erhan | Pierre-Antoine Manzagol | Yoshua Bengio | D. Erhan | Samy Bengio | Pierre-Antoine Manzagol | Pascal Vincent
[1] Johan Håstad,et al. On the power of small-depth threshold circuits , 1990, Proceedings [1990] 31st Annual Symposium on Foundations of Computer Science.
[2] David Haussler,et al. Unsupervised learning of distributions on binary vectors using two layer networks , 1991, NIPS 1991.
[3] Thomas G. Dietterich,et al. Editors. Advances in Neural Information Processing Systems , 2002 .
[4] Geoffrey E. Hinton,et al. Reducing the Dimensionality of Data with Neural Networks , 2006, Science.
[5] Yee Whye Teh,et al. A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.
[6] Marc'Aurelio Ranzato,et al. Efficient Learning of Sparse Representations with an Energy-Based Model , 2006, NIPS.
[7] Geoffrey E. Hinton,et al. Restricted Boltzmann machines for collaborative filtering , 2007, ICML '07.
[8] Honglak Lee,et al. Sparse deep belief net model for visual area V2 , 2007, NIPS.
[9] Thomas Hofmann,et al. Efficient Learning of Sparse Representations with an Energy-Based Model , 2007 .
[10] Marc'Aurelio Ranzato,et al. Sparse Feature Learning for Deep Belief Networks , 2007, NIPS.
[11] Thomas Hofmann,et al. Greedy Layer-Wise Training of Deep Networks , 2007 .
[12] Geoffrey E. Hinton,et al. Learning a Nonlinear Embedding by Preserving Class Neighbourhood Structure , 2007, AISTATS.
[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] Geoffrey E. Hinton,et al. Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes , 2007, NIPS.
[16] Geoffrey E. Hinton,et al. Visualizing Data using t-SNE , 2008 .
[17] Jason Weston,et al. A unified architecture for natural language processing: deep neural networks with multitask learning , 2008, ICML '08.
[18] Jason Weston,et al. Deep learning via semi-supervised embedding , 2008, ICML '08.
[19] Yoshua Bengio,et al. Extracting and composing robust features with denoising autoencoders , 2008, ICML '08.
[20] Yoshua Bengio,et al. Justifying and Generalizing Contrastive Divergence , 2009, Neural Computation.