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DIS
2005
Springer
14 years 1 months ago
Active Constrained Clustering by Examining Spectral Eigenvectors
Abstract. This work focuses on the active selection of pairwise constraints for spectral clustering. We develop and analyze a technique for Active Constrained Clustering by Examini...
Qianjun Xu, Marie desJardins, Kiri Wagstaff
ML
2010
ACM
193views Machine Learning» more  ML 2010»
13 years 2 months ago
On the eigenvectors of p-Laplacian
Spectral analysis approaches have been actively studied in machine learning and data mining areas, due to their generality, efficiency, and rich theoretical foundations. As a natur...
Dijun Luo, Heng Huang, Chris H. Q. Ding, Feiping N...
PAKDD
2009
ACM
209views Data Mining» more  PAKDD 2009»
14 years 4 months ago
Approximate Spectral Clustering.
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-...
Christopher Leckie, James C. Bezdek, Kotagiri Rama...
ICMCS
2005
IEEE
104views Multimedia» more  ICMCS 2005»
14 years 1 months ago
Joint Inter and Intra Shot Modeling for Spectral Video Shot Clustering
This paper proposed a novel video shot clustering algorithm using spectral method by joint modeling of inter and intra shot. Gauss Mixture Model (GMM) is used for probabilistic sp...
Jianning Zhang, Lifeng Sun, Shiqiang Yang, Yuzhuo ...
ESANN
2007
13 years 9 months ago
Feature clustering and mutual information for the selection of variables in spectral data
Spectral data often have a large number of highly-correlated features, making feature selection both necessary and uneasy. A methodology combining hierarchical constrained clusteri...
Catherine Krier, Damien François, Fabrice R...