{{keywords>Semi-Supervised Learning}}

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Semi-Supervised Learning
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===== Recommended Reading =====

  * [[http://rinuboney.github.io/2016/01/19/ladder-network.html|Introduction to Semi-Supervised Learning with Ladder Networks]] by Rinu Boney (2016)
  * [[https://arxiv.org/pdf/1507.02672.pdf|Semi-Supervised Learning with Ladder Networks]] by Antti Rasmus et al. (2015)
  * [[http://pages.cs.wisc.edu/~jerryzhu/pub/ssl_survey.pdf|Semi-Supervised Learning Literature Survey]]
  * [[https://arxiv.org/abs/1610.02242|Temporal Ensembling for Semi-Supervised Learning]] by Xiaojin Zhu (2008), a review of methods from the pre-deep learning era
  * [[http://papers.nips.cc/paper/6333-regularization-with-stochastic-transformations-and-perturbations-for-deep-semi-supervised-learning.pdf|Regularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised Learning]] by Mehdi Sajjadi, Mehran Javanmardi and Tolga Tasdizen (2016)
  * [[http://openaccess.thecvf.com/content_cvpr_2017/papers/Abbasnejad_Infinite_Variational_Autoencoder_CVPR_2017_paper.pdf|Infinite Variational Autoencoder for Semi-Supervised Learning]] by Ehsan Abbasnejad and Anthony Dick (2016)
  * [[https://papers.nips.cc/paper/1582-semi-supervised-support-vector-machines.pdf|Semi-Supervised Support Vector Machines ]] by Kristin Bennett and Ayhan Demiriz (1999)
  * [[https://wiseodd.github.io/techblog/2016/12/03/autoencoders/|Many flavors of Autoencoder]] by Agustinus Kristiadi (2016)

===== Tutorials =====
  * [[https://blog.keras.io/building-autoencoders-in-keras.html|Building Autoencoders in Keras]] by  Francois Chollet (2016)