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Manifold Construction by Local Neighborhood Preservation

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Neural Information Processing (ICONIP 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4985))

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Abstract

This work presents a neighborhood preservation method to construct the latent manifold. This manifold preserves the relative Euclidean distances among neighboring data points. Its computation cost is close to the linear algorithm and its performance in preserving the local relationships is promising when we compared it with the methods, LLE and Isomap.

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Masumi Ishikawa Kenji Doya Hiroyuki Miyamoto Takeshi Yamakawa

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© 2008 Springer-Verlag Berlin Heidelberg

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Liou, CY., Cheng, WC. (2008). Manifold Construction by Local Neighborhood Preservation. In: Ishikawa, M., Doya, K., Miyamoto, H., Yamakawa, T. (eds) Neural Information Processing. ICONIP 2007. Lecture Notes in Computer Science, vol 4985. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69162-4_71

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  • DOI: https://doi.org/10.1007/978-3-540-69162-4_71

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-69159-4

  • Online ISBN: 978-3-540-69162-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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