Marginal Deep Architecture: Stacking Feature Learning Modules to Build Deep Learning Models
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Kang Zhang | Junyu Dong | Guoqiang Zhong | Yuchen Zheng | Hongxu Wei | Junyu Dong | G. Zhong | Yuchen Zheng | Kang Zhang | Hongxu Wei
[1] Quoc V. Le,et al. Sequence to Sequence Learning with Neural Networks , 2014, NIPS.
[2] Mohamed Cheriet,et al. An Empirical Evaluation of Supervised Dimensionality Reduction for Recognition , 2013, 2013 12th International Conference on Document Analysis and Recognition.
[3] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[4] Junyu Dong,et al. Visual Texture Perception with Feature Learning Models and Deep Architectures , 2014, CCPR.
[5] Xiaofei He,et al. Locality Preserving Projections , 2003, NIPS.
[6] Honglak Lee,et al. Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations , 2009, ICML '09.
[7] Wu-Jun Li,et al. Gaussian Process Latent Random Field , 2010, AAAI.
[8] Yoshua Bengio,et al. Extracting and composing robust features with denoising autoencoders , 2008, ICML '08.
[9] Jason Weston,et al. A unified architecture for natural language processing: deep neural networks with multitask learning , 2008, ICML '08.
[10] Tara N. Sainath,et al. FUNDAMENTAL TECHNOLOGIES IN MODERN SPEECH RECOGNITION Digital Object Identifier 10.1109/MSP.2012.2205597 , 2012 .
[11] Nitish Srivastava,et al. Improving neural networks by preventing co-adaptation of feature detectors , 2012, ArXiv.
[12] Shuicheng Yan,et al. Graph Embedding and Extensions: A General Framework for Dimensionality Reduction , 2007 .
[13] Marc'Aurelio Ranzato,et al. Sparse Feature Learning for Deep Belief Networks , 2007, NIPS.
[14] Geoffrey E. Hinton,et al. Deep Learning , 2015, Nature.
[15] Juhan Nam,et al. Multimodal Deep Learning , 2011, ICML.
[16] Pascal Vincent,et al. Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion , 2010, J. Mach. Learn. Res..
[17] L. J. P. van der Maaten,et al. An Introduction to Dimensionality Reduction Using Matlab , 2007 .
[18] Geoffrey E. Hinton,et al. Reducing the Dimensionality of Data with Neural Networks , 2006, Science.
[19] George Trigeorgis,et al. A Deep Semi-NMF Model for Learning Hidden Representations , 2014, ICML.
[20] Guoqiang Zhong,et al. From shallow feature learning to deep learning: Benefits from the width and depth of deep architectures , 2019, WIREs Data Mining Knowl. Discov..
[21] B. Frey,et al. The human splicing code reveals new insights into the genetic determinants of disease , 2015, Science.
[22] Geoffrey E. Hinton,et al. Stochastic Neighbor Embedding , 2002, NIPS.
[23] Junyu Dong,et al. Stretching deep architectures for text recognition , 2015, 2015 13th International Conference on Document Analysis and Recognition (ICDAR).
[24] Eric O. Postma,et al. Dimensionality Reduction: A Comparative Review , 2008 .
[25] Luca Maria Gambardella,et al. Deep, Big, Simple Neural Nets for Handwritten Digit Recognition , 2010, Neural Computation.
[26] Geoffrey E. Hinton,et al. Learning representations by back-propagating errors , 1986, Nature.
[27] Xiaoqiang Lu,et al. Scene Recognition by Manifold Regularized Deep Learning Architecture , 2015, IEEE Transactions on Neural Networks and Learning Systems.
[28] Quoc V. Le,et al. Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis , 2011, CVPR 2011.
[29] Bolei Zhou,et al. Learning Deep Features for Scene Recognition using Places Database , 2014, NIPS.
[30] R. Fisher. THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS , 1936 .
[31] Honglak Lee,et al. Unsupervised feature learning for audio classification using convolutional deep belief networks , 2009, NIPS.
[32] Trevor Darrell,et al. DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition , 2013, ICML.