Generalizing semi-supervised generative adversarial networks to regression

@article{Olmschenk2019GeneralizingSG,
  title={Generalizing semi-supervised generative adversarial networks to regression},
  author={Greg Olmschenk and Zhigang Zhu and Hao Tang},
  journal={ArXiv},
  year={2019},
  volume={abs/1811.11269}
}
  • Greg Olmschenk, Zhigang Zhu, Hao Tang
  • Published 2019
  • Mathematics, Computer Science
  • ArXiv
  • In this work, we generalize semi-supervised generative adversarial networks (GANs) from classification problems to regression problems. In the last few years, the importance of improving the training of neural networks using semi-supervised training has been demonstrated for classification problems. With probabilistic classification being a subset of regression problems, this generalization opens up many new possibilities for the use of semi-supervised GANs as well as presenting an avenue for a… CONTINUE READING

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