Fetching the paper…
Reading the bibliography…
Two novel deep hybrid architectures, the Deep Hybrid Boltzmann Machine and the Deep Hybrid Denoising Auto-encoder, are proposed for handling semi-supervised learning problems.
Rules and representations
Chomsky, Noam · 1980
Earlier work this paper cites.
The” wake-sleep” algorithm for unsupervised neural networks
Hinton, Geoffrey E., Dayan, Peter, Frey, Brendan J., and Neal, Radford M · 1995
Earlier work this paper cites.
Annealed importance sampling
Neal, Radford M · 2001
Earlier work this paper cites.
Training Products of Experts by Minimizing Contrastive Divergence
Hinton, Geoffrey E · 2002
Earlier work this paper cites.
A new learning algorithm for mean field boltzmann machines
Welling, Max and Hinton, Geoffrey E · 2002
Earlier work this paper cites.
Principled Hybrids of Generative and Discriminative Models
Lasserre, Julia A., Bishop, Christopher M., and Minka, Thomas P · 2006
Earlier work this paper cites.
Greedy Layer-wise Training of Deep Networks
Bengio, Yoshua, Lamblin, Pascal, Popovici, Dan, and Larochelle, Hugo · 2007
Earlier work this paper cites.
Classification using Discriminative Restricted Boltzmann Machines
Larochelle, Hugo and Bengio, Yoshua · 2008
Earlier work this paper cites.
Semi-supervised learning of compact document representations with deep networks
Ranzato, Marc’ Aurelio and Szummer, Martin · 2008
Earlier work this paper cites.
Deep boltzmann machines
Salakhutdinov, Ruslan and Hinton, Geoffrey E · 2009
Earlier work this paper cites.
MOA: Massive online analysis, a framework for stream classification and clustering
Bifet, Albert, Holmes, Geoffrey, Pfahringer, Bernhard, Kranen, Philipp, Kremer, Hardy, Jansen, Timm, and Seidl, Thomas · 2010
Earlier work this paper cites.
Why does unsupervised pre-training help deep learning?
Erhan, Dumitru, Bengio, Yoshua, Courville, Aaron, Manzagol, Pierre-Antoine, Vincent, Pascal, and Bengio, Samy · 2010
Cited alongside, same era.
Efficient learning of deep boltzmann machines
Salakhutdinov, Ruslan and Larochelle, Hugo · 2010
Cited alongside, same era.
Sum-product networks: A new deep architecture
Poon, Hoifung and Domingos, Pedro · 2011
Cited alongside, same era.
Semi-supervised recursive autoencoders for predicting sentiment distributions
Socher, Richard, Pennington, Jeffrey, Huang, Eric H., Ng, Andrew Y., and Manning, Christopher D · 2011
Cited alongside, same era.
Layer-wise learning of deep generative models
Arnold, Ludovic and Ollivier, Yann · 2012
Cited alongside, same era.
Learning Deep Belief Networks from Non-stationary Streams
Calandra, Roberto, Raiko, Tapani, Deisenroth, Marc Peter, and Pouzols, Federico Montesino · 2012
Online Incremental Feature Learning with Denoising Autoencoders
Zhou, Guanyu, Sohn, Kihyuk, and Lee, Honglak · 2012
Later among the works it cites.
Multi-prediction deep boltzmann machines
Goodfellow, Ian, Mirza, Mehdi, Courville, Aaron, and Bengio, Yoshua · 2013
Later among the works it cites.
Pseudo-label: The Simple and Efficient Semi-supervised Learning Method for Deep Neural Networks
Lee, Dong-Hyun · 2013
Later among the works it cites.
How auto-encoders could provide credit assignment in deep networks via target propagation
Bengio, Yoshua · 2014
Later among the works it cites.
Semi-supervised learning with deep generative models
Kingma, Diederik P., Mohamed, Shakir, Rezende, Danilo Jimenez, and Welling, Max · 2014
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
On evaluating stream learning algorithms
Gama, João, Sebastião, Raquel, and Rodrigues, Pedro Pereira · 2012
Cited alongside, same era.
Improving neural networks by preventing co-adaptation of feature detectors
Hinton, Geoffrey E., Srivastava, Nitish, Krizhevsky, Alex, Sutskever, Ilya, and Salakhutdinov, Ruslan R · 2012
Cited alongside, same era.
Learning Algorithms for the Classification Restricted Boltzmann Machine
Larochelle, Hugo, Mandel, Michael, Pascanu, Razvan, and Bengio, Yoshua · 2012
Cited alongside, same era.
Deep learning via semi-supervised embedding
Weston, Jason, Ratle, Frédéric, Mobahi, Hossein, and Collobert, Ronan · 2012
Cited alongside, same era.
Reweighted wake-sleep
Bornschein, Jörg and Bengio, Yoshua
Cited in the paper.
The manifold tangent classifier
Rifai, Salah, Dauphin, Yann N., Vincent, Pascal, Bengio, Yoshua, and Muller, Xavier
Cited in the paper.
Lee, Chen-Yu, Xie, Saining, Gallagher, Patrick, Zhang, Zhengyou, and Tu, Zhuowen · 2014
Later among the works it cites.
Supervised Deep Learning with Auxiliary Networks
Zhang, Junbo, Tian, Guangjian, Mu, Yadong, and Fan, Wei · 2014
Later among the works it cites.
Difference target propagation
Lee, Dong-Hyun, Zhang, Saizheng, Fischer, Asja, and Bengio, Yoshua · 2015
Closest in time.
Learning a deep hybrid model for semi-supervised text classification
Ororbia II, Alexander G., Giles, C. Lee, and Reitter, David · 2015
Closest in time.
Online learning of deep hybrid architectures for semi-supervised categorization
Ororbia II, Alexander G., Reitter, David, Wu, Jian, and Giles, C. Lee · 2015
Closest in time.