暂无分享,去创建一个
[1] Jeffrey Pennington,et al. Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions , 2011, EMNLP.
[2] Pedro M. Domingos,et al. Sum-product networks: A new deep architecture , 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).
[3] David Reitter,et al. Learning a Deep Hybrid Model for Semi-Supervised Text Classification , 2015, EMNLP.
[4] Zhuowen Tu,et al. Deeply-Supervised Nets , 2014, AISTATS.
[5] Razvan Pascanu,et al. Learning Algorithms for the Classification Restricted Boltzmann Machine , 2012, J. Mach. Learn. Res..
[6] Dong-Hyun Lee,et al. Pseudo-Label : The Simple and Efficient Semi-Supervised Learning Method for Deep Neural Networks , 2013 .
[7] Tom Minka,et al. Principled Hybrids of Generative and Discriminative Models , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[8] Honglak Lee,et al. Online Incremental Feature Learning with Denoising Autoencoders , 2012, AISTATS.
[9] Marc'Aurelio Ranzato,et al. Semi-supervised learning of compact document representations with deep networks , 2008, ICML '08.
[10] Yoram Singer,et al. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization , 2011, J. Mach. Learn. Res..
[11] Yoshua Bengio,et al. Difference Target Propagation , 2014, ECML/PKDD.
[12] Radford M. Neal. Annealed importance sampling , 1998, Stat. Comput..
[13] Pascal Vincent,et al. Contractive Auto-Encoders: Explicit Invariance During Feature Extraction , 2011, ICML.
[14] Jason Weston,et al. Deep learning via semi-supervised embedding , 2008, ICML '08.
[15] Matthew D. Zeiler. ADADELTA: An Adaptive Learning Rate Method , 2012, ArXiv.
[16] João Gama,et al. On evaluating stream learning algorithms , 2012, Machine Learning.
[17] Yoshua Bengio,et al. Why Does Unsupervised Pre-training Help Deep Learning? , 2010, AISTATS.
[18] Geoffrey E. Hinton,et al. A New Learning Algorithm for Mean Field Boltzmann Machines , 2002, ICANN.
[19] Yoshua Bengio,et al. How Auto-Encoders Could Provide Credit Assignment in Deep Networks via Target Propagation , 2014, ArXiv.
[20] Yadong Mu,et al. Supervised deep learning with auxiliary networks , 2014, KDD.
[21] Geoffrey E. Hinton. Training Products of Experts by Minimizing Contrastive Divergence , 2002, Neural Computation.
[22] Pascal Vincent,et al. The Manifold Tangent Classifier , 2011, NIPS.
[23] Yoshua Bengio,et al. Multi-Prediction Deep Boltzmann Machines , 2013, NIPS.
[24] Yann Ollivier,et al. Layer-wise learning of deep generative models , 2012, ArXiv.
[25] Max Welling,et al. Semi-supervised Learning with Deep Generative Models , 2014, NIPS.
[26] Tapani Raiko,et al. Learning Deep Belief Networks from Non-stationary Streams , 2012, ICANN.
[27] Xinyun Chen. Under Review as a Conference Paper at Iclr 2017 Delving into Transferable Adversarial Ex- Amples and Black-box Attacks , 2016 .
[28] Thomas Seidl,et al. MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering , 2010, WAPA.
[29] Geoffrey E. Hinton,et al. Deep Boltzmann Machines , 2009, AISTATS.
[30] Geoffrey E. Hinton,et al. The "wake-sleep" algorithm for unsupervised neural networks. , 1995, Science.
[31] Nitish Srivastava,et al. Improving neural networks by preventing co-adaptation of feature detectors , 2012, ArXiv.
[32] Yoshua Bengio,et al. Classification using discriminative restricted Boltzmann machines , 2008, ICML '08.
[33] David Reitter,et al. Online Learning of Deep Hybrid Architectures for Semi-supervised Categorization , 2015, ECML/PKDD.
[34] R. Horton. Rules and representations , 1993, The Lancet.
[35] Hugo Larochelle,et al. Efficient Learning of Deep Boltzmann Machines , 2010, AISTATS.
[36] Yoshua Bengio,et al. Greedy Layer-Wise Training of Deep Networks , 2006, NIPS.