Nonlinear dimensionality reduction by locally linear embedding

Nonlinear dimensionality reduction by locally linear embedding (2000)

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by Sam T. Roweis , Lawrence K. Saul

Venue:	SCIENCE
Citations:	1156 - 19 self

BibTeX

@ARTICLE{Roweis00nonlineardimensionality,
    author = {Sam T. Roweis and Lawrence K. Saul},
    title = {Nonlinear dimensionality reduction by locally linear embedding},
    journal = {SCIENCE},
    year = {2000},
    volume = {290},
    pages = {2323--2326}
}

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Abstract

Many areas of science

Citations

557	Data Structures and Network Algorithms - Tarjan - 1983
82	Matrix analysis. Cambridge Univ - Horn, Johnson - 1985
38	Self-Organization and Associative Memory (Springer-Verlag - Kohonen - 1984
21	der Vorst (Eds.), Templates for the Solution of Algebraic Eigenvalue Problems: A Practical Guide - Bai, Demmel, et al. - 2000
18	Principal Component Analysis; Springer-Verlag - Jolliffe - 2002
1	Interface Foundation of North America - Littman, Swayne, et al. - 1992
1	does not require the original data to be described in a single coordinate system, only that each data point be located in relation to its neighbors - Indeed
1	Data points in Fig. 1B (N � 2000) were sampled from the manifold (D � 3) shown in Fig. 1A. Nearest neighbors (K � 20) were determined by Euclidean distance. This particular manifold was introduced by Tenenbaum (4), who showed that its global structure cou - Manifold
1	for sharing their unpublished work (at the University of Toronto) on segmentation and pose estimation that motivated us to “think globally, fit locally”; J. Tenenbaum (Stanford University) for many stimulating discussions about his work (4) and for sharin - Hinton, Revow