An efficient algorithm of learning the parametric map of locally linear embedding

Xu Zhang*, Yushu Liu, Chunxiao Gao, Jinghao Liu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

A method is presented to obtain maps between the high-dimensional data and the low-dimensional space deduced by locally linear embedding (LLE). Since LLE does not provide a parametric function that build maps between the image space and the low-dimensional manifold. In this paper, multivariate linear regression is applied to deduce the maps. It can successfully project a new data point onto the embedded space. Also it can be extended to supervised LLE). The performance analysis on the obtained experimental results demonstrated that the proposed method is effective and efficient.

Original languageEnglish
Title of host publicationProceedings - 2008 2nd International Symposium on Intelligent Information Technology Application, IITA 2008
Pages52-56
Number of pages5
DOIs
Publication statusPublished - 2008
Event2008 2nd International Symposium on Intelligent Information Technology Application, IITA 2008 - Shanghai, China
Duration: 21 Dec 200822 Dec 2008

Publication series

NameProceedings - 2008 2nd International Symposium on Intelligent Information Technology Application, IITA 2008
Volume3

Conference

Conference2008 2nd International Symposium on Intelligent Information Technology Application, IITA 2008
Country/TerritoryChina
CityShanghai
Period21/12/0822/12/08

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