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 language | English |
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Title of host publication | Proceedings - 2008 2nd International Symposium on Intelligent Information Technology Application, IITA 2008 |
Pages | 52-56 |
Number of pages | 5 |
DOIs | |
Publication status | Published - 2008 |
Event | 2008 2nd International Symposium on Intelligent Information Technology Application, IITA 2008 - Shanghai, China Duration: 21 Dec 2008 → 22 Dec 2008 |
Publication series
Name | Proceedings - 2008 2nd International Symposium on Intelligent Information Technology Application, IITA 2008 |
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Volume | 3 |
Conference
Conference | 2008 2nd International Symposium on Intelligent Information Technology Application, IITA 2008 |
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Country/Territory | China |
City | Shanghai |
Period | 21/12/08 → 22/12/08 |
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Zhang, X., Liu, Y., Gao, C., & Liu, J. (2008). An efficient algorithm of learning the parametric map of locally linear embedding. In Proceedings - 2008 2nd International Symposium on Intelligent Information Technology Application, IITA 2008 (pp. 52-56). Article 4739957 (Proceedings - 2008 2nd International Symposium on Intelligent Information Technology Application, IITA 2008; Vol. 3). https://doi.org/10.1109/IITA.2008.331