Generalized Autoencoder: A Neural Network Framework for Dimensionality Reduction

@article{Wang2014GeneralizedAA,
  title={Generalized Autoencoder: A Neural Network Framework for Dimensionality Reduction},
  author={Wei Wang and Ying Huang and Yizhou Wang and Liang Wang},
  journal={2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops},
  year={2014},
  pages={496-503}
}
The autoencoder algorithm and its deep version as traditional dimensionality reduction methods have achieved great success via the powerful representability of neural networks. However, they just use each instance to reconstruct itself and ignore to explicitly model the data relation so as to discover the underlying effective manifold structure. In this paper, we propose a dimensionality reduction method by manifold learning, which iteratively explores data relation and use the relation to… CONTINUE READING

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