Exploiting constraint inconsistence for dimension selection in subspace clustering: A semi-supervised approach-Reference-Cited by-同舟云学术

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Exploiting constraint inconsistence for dimension selection in subspace clustering: A semi-supervised approach

Published:2011-10 Issue:17 Volume:74 Page:3598-3608
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Zhang Xianchao,Qiu Yang,Wu Yao

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference29 articles.

1. Fast algorithms for projected clustering;Aggarwal,1999

2. Finding generalized projected clusters in high dimensional space;Aggarwal,2000

3. Automatic subspace clustering of high dimensional data for data mining applications;Agrawal,1998

4. SISC: a text classification approach using semi supervised subspace clustering;Ahmed,2009

5. DUSC: dimensionality unbiased subspace clustering;Assent,2007

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2. Graph regularized multilayer concept factorization for data representation;Neurocomputing;2017-05

3. An adaptive RV measure based fuzzy weighting subspace clustering (ARV-FWSC) for fMRI data analysis;Biomedical Signal Processing and Control;2015-09

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