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Learning orthogonal projections for Isomap
Zheng, Yali1; Fang, Bin1; Tang, Yuan Yan2; Zhang, Taiping1; Liu, Ruizong1
2013-03-01
Source PublicationNeurocomputing
ISSN0925-2312
Volume103Pages:149-154
Abstract

We propose a dimensionality reduction technique in this paper, named Orthogonal Isometric Projection (OIP). In contrast with Isomap, which learns the low-dimension embedding, and solves problem under the classic Multidimensional Scaling (MDS) framework, we consider an explicit linear projection by capturing the geodesic distance, which is able to handle new data straightforward, and leads to a standard eigenvalue problem. We consider the orthogonal projection, and analyze the properties of orthogonal projection, and demonstrate the benefits, in which Euclidean distance, and angle at each pair in high-dimensional space are equivalent to ones in low-dimension, such that both global and local geometric structure are preserved. Numerical experiments are reported to demonstrate the performance of OIP by comparing with a few competing methods over different datasets.

KeywordManifold Learning Isomap Orthogonal Projection
DOIhttps://doi.org/10.1016/j.neucom.2012.09.015
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000313374500016
PublisherELSEVIER SCIENCE BV, PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS
The Source to ArticleEngineering Village
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被引频次[WOS]:4   [WOS记录]     [WOS相关记录]
Document TypeJournal article
专题DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.School of Computer Science, Chongqing University, Chongqing, China;
2.University of Macau, Macau, China
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Zheng, Yali,Fang, Bin,Tang, Yuan Yan,et al. Learning orthogonal projections for Isomap[J]. Neurocomputing,2013,103:149-154.
APA Zheng, Yali,Fang, Bin,Tang, Yuan Yan,Zhang, Taiping,&Liu, Ruizong.(2013).Learning orthogonal projections for Isomap.Neurocomputing,103,149-154.
MLA Zheng, Yali,et al."Learning orthogonal projections for Isomap".Neurocomputing 103(2013):149-154.
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