Editorial introduction to the Neural Networks special issue on Deep Learning of Representations
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[1] Jürgen Schmidhuber,et al. Deep learning in neural networks: An overview , 2014, Neural Networks.
[2] Quoc V. Le,et al. Sequence to Sequence Learning with Neural Networks , 2014, NIPS.
[3] Richard M. Schwartz,et al. Fast and Robust Neural Network Joint Models for Statistical Machine Translation , 2014, ACL.
[4] Jeffrey Dean,et al. Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.
[5] Camille Couprie,et al. Learning Hierarchical Features for Scene Labeling , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[6] Yann LeCun,et al. Pedestrian Detection with Unsupervised Multi-stage Feature Learning , 2012, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[7] Marc'Aurelio Ranzato,et al. Building high-level features using large scale unsupervised learning , 2011, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[8] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[9] Tara N. Sainath,et al. Deep Neural Networks for Acoustic Modeling in Speech Recognition , 2012 .
[10] Tara N. Sainath,et al. FUNDAMENTAL TECHNOLOGIES IN MODERN SPEECH RECOGNITION Digital Object Identifier 10.1109/MSP.2012.2205597 , 2012 .
[11] Jürgen Schmidhuber,et al. Multi-column deep neural network for traffic sign classification , 2012, Neural Networks.
[12] Dong Yu,et al. Conversational Speech Transcription Using Context-Dependent Deep Neural Networks , 2012, ICML.
[13] Yoshua Bengio,et al. Spike-and-Slab Sparse Coding for Unsupervised Feature Discovery , 2012, ArXiv.
[14] Yoshua Bengio,et al. Unsupervised and Transfer Learning Challenge: a Deep Learning Approach , 2011, ICML Unsupervised and Transfer Learning.
[15] Yoshua Bengio,et al. Domain Adaptation for Large-Scale Sentiment Classification: A Deep Learning Approach , 2011, ICML.
[16] Yoshua Bengio,et al. Deep Sparse Rectifier Neural Networks , 2011, AISTATS.
[17] Geoffrey E. Hinton,et al. Phone Recognition with the Mean-Covariance Restricted Boltzmann Machine , 2010, NIPS.
[18] Geoffrey E. Hinton,et al. Binary coding of speech spectrograms using a deep auto-encoder , 2010, INTERSPEECH.
[19] Geoffrey E. Hinton,et al. Rectified Linear Units Improve Restricted Boltzmann Machines , 2010, ICML.
[20] Yoshua Bengio,et al. Why Does Unsupervised Pre-training Help Deep Learning? , 2010, AISTATS.
[21] Honglak Lee,et al. Unsupervised feature learning for audio classification using convolutional deep belief networks , 2009, NIPS.
[22] Yann LeCun,et al. What is the best multi-stage architecture for object recognition? , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[23] Honglak Lee,et al. Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations , 2009, ICML '09.
[24] Jason Weston,et al. Deep learning via semi-supervised embedding , 2008, ICML '08.
[25] Honglak Lee,et al. Sparse deep belief net model for visual area V2 , 2007, NIPS.
[26] Geoffrey E. Hinton,et al. Restricted Boltzmann machines for collaborative filtering , 2007, ICML '07.
[27] Rajat Raina,et al. Self-taught learning: transfer learning from unlabeled data , 2007, ICML '07.
[28] Yoshua. Bengio,et al. Learning Deep Architectures for AI , 2007, Found. Trends Mach. Learn..
[29] Yoshua Bengio,et al. Greedy Layer-Wise Training of Deep Networks , 2006, NIPS.
[30] Marc'Aurelio Ranzato,et al. Efficient Learning of Sparse Representations with an Energy-Based Model , 2006, NIPS.
[31] Yee Whye Teh,et al. A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.
[32] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[33] Lawrence D. Jackel,et al. Backpropagation Applied to Handwritten Zip Code Recognition , 1989, Neural Computation.