Multi-View Intact Space Learning

@article{Xu2015MultiViewIS,
  title={Multi-View Intact Space Learning},
  author={Chang Xu and Dacheng Tao and Chao Xu},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2015},
  volume={37},
  pages={2531-2544}
}
It is practical to assume that an individual view is unlikely to be sufficient for effective multi-view learning. Therefore, integration of multi-view information is both valuable and necessary. In this paper, we propose the Multi-view Intact Space Learning (MISL) algorithm, which integrates the encoded complementary information in multiple views to discover a latent intact representation of the data. Even though each view on its own is insufficient, we show theoretically that by combing… CONTINUE READING
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