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Grouping and dimensionality reduction by locally linear embedding

Polito, Marzia and Perona, Pietro (2002) Grouping and dimensionality reduction by locally linear embedding. In: Advances in Neural Information Processing Systems. Advances in Neural Information Processing Systems . Vol.14. No.2. MIT Press , Cambridge, MA, pp. 1255-1262. ISBN 0-262-04208-8. https://resolver.caltech.edu/CaltechAUTHORS:20140730-101719764

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Abstract

Locally Linear Embedding (LLE) is an elegant nonlinear dimensionality-reduction technique recently introduced by Roweis and Saul 2]. It fails when the data is divided into separate groups. We study a variant of LLE that can simultaneously group the data and calculate local embedding of each group. An estimate for the upper bound on the intrinsic dimension of the data set is obtained automatically.


Item Type:Book Section
Related URLs:
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http://papers.nips.cc/paper/2033-grouping-and-dimensionality-reduction-by-locally-linear-embeddingPublisherArticle
ORCID:
AuthorORCID
Perona, Pietro0000-0002-7583-5809
Series Name:Advances in Neural Information Processing Systems
Issue or Number:2
Record Number:CaltechAUTHORS:20140730-101719764
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20140730-101719764
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:47618
Collection:CaltechAUTHORS
Deposited By: Caroline Murphy
Deposited On:19 Aug 2014 18:04
Last Modified:03 Oct 2019 06:55

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