Incremental Manifold Learning Via Tangent Space Alignment

  title={Incremental Manifold Learning Via Tangent Space Alignment},
  author={Xiaoming Liu and Jianwei Yin and Zhilin Feng and Jinxiang Dong},
  booktitle={IAPR International Workshop on Artificial Neural Networks in Pattern Recognition},
Several algorithms have been proposed to analysis the structure of high-dimensional data based on the notion of manifold learning. They have been used to extract the intrinsic characteristic of different type of high-dimensional data by performing nonlinear dimensionality reduction. Most of them operate in a “batch” mode and cannot be efficiently applied when data are collected sequentially. In this paper, we proposed an incremental version (ILTSA) of LTSA (Local Tangent Space Alignment), which… 

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  • Computer Science
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  • 2011
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A global geometric framework for nonlinear dimensionality reduction.

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  • D. DonohoC. Grimes
  • Computer Science, Mathematics
    Proceedings of the National Academy of Sciences of the United States of America
  • 2003
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