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Understanding High-Dimensional SpacesRepresentation by Graphs

Understanding High-Dimensional Spaces: Representation by Graphs [A geometric space has the advantage that the similarity between any pair of points is independent of the presence and placement of any other points, no matter what the particular measure of similarity might be. This is computationally attractive, which is why it has been the basis of everything discussed so far.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Understanding High-Dimensional SpacesRepresentation by Graphs

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Publisher
Springer Berlin Heidelberg
Copyright
© The Author 2012
ISBN
978-3-642-33397-2
Pages
67 –71
DOI
10.1007/978-3-642-33398-9_6
Publisher site
See Chapter on Publisher Site

Abstract

[A geometric space has the advantage that the similarity between any pair of points is independent of the presence and placement of any other points, no matter what the particular measure of similarity might be. This is computationally attractive, which is why it has been the basis of everything discussed so far.]

Published: Sep 25, 2012

Keywords: Random Walk Laplacian; Edge Weight Sum; Aggregate Electrical Resistance; Laplacian Embedding; Embedding Choices

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