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Output details

11 - Computer Science and Informatics

Kingston University

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Output 7 of 40 in the submission

Article title

Automatic configuration of spectral dimensionality reduction methods

Type

D - Journal article

DOI

10.1016/j.patrec.2010.05.025

Title of journal

Pattern Recognition Letters

Article number

Volume number

Issue number

First page of article

1720

ISSN of journal

0167-8655

Year of publication

2010

URL

http://eprints.kingston.ac.uk/16479/

Number of additional authors

Additional information

<24> This paper deals with the issue of automatic configuration of the various parameters of spectral dimensionality reduction methods (ISOMAP, Locally Linear Embedding, Laplacian Eigenmaps). The proposed framework performs better than previous solutions for all different dimensionality reduction methods. Such an approach clearly facilitates the usage of this family of spectral methods for all possible datasets.

Interdisciplinary

Cross-referral requested

Research group

None

Citation count

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract