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This paper introduces an information theoretic co-training objective for unsupervised learning.
Maximum likelihood from incomplete data via the em algorithm
A. P. Dempster, N. M. Laird, and D.B. Rubin · 1977
Earlier work this paper cites.
Learning factorial codes by predictability minimization
Jürgen Schmidhuber · 1992
Earlier work this paper cites.
Timit: Acoustic-phonetic continuous speech corpus ldc93s1, 1993
John S. Garofolo, Lori F. Lamel, William M. Fisher, Jonathan G. Fiscus, David S. Pallett, Nancy L. Dahlgren, and Victor Zue · 1993
Earlier work this paper cites.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
Earlier work this paper cites.
Combining labeled and unlabeled data with co-training
A Blum and T Mitchell · 1998
Cited alongside, same era.
The information bottleneck method
Naftali Tishby, Fernando Pereira, and William Bialek · 1999
Cited alongside, same era.
Pac generalization bounds for co-training
Sanjoy Dasgupta, Michael Littman, and David McAllester · 2002
Cited alongside, same era.
Generative adversarial networks
Ian Goodfellow, Jean Pouget-Abadie, Hehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Cited alongside, same era.
Auto-encoding variational bayes
D.P. Kingma and M. Welling · 2014
Later among the works it cites.
Gated feedback recurrent neural networks
Junyoung Chung, Caglar Gulcehre, Kyunghyun Cho, and Yoshua Bengio · 2015
Later among the works it cites.
Infogan: Interpretable representation learning by information maximizing generative adversarial nets
Xi Chen, Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, and Pieter Abbeel · 2016
Later among the works it cites.
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