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ICPR
2008
IEEE
14 years 4 months ago
Multiclass spectral clustering based on discriminant analysis
Many existing spectral clustering algorithms share a conventional graph partitioning criterion: normalized cuts (NC). However, one problem with NC is that it poorly captures the g...
Xi Li, Zhongfei Zhang, Yanguo Wang, Weiming Hu
PAKDD
2007
ACM
152views Data Mining» more  PAKDD 2007»
13 years 9 months ago
Spectral Clustering Based Null Space Linear Discriminant Analysis (SNLDA)
While null space based linear discriminant analysis (NLDA) obtains a good discriminant performance, the ability easily suffers from an implicit assumption of Gaussian model with sa...
Wenxin Yang, Junping Zhang
ICCV
2003
IEEE
14 years 5 months ago
Multiclass Spectral Clustering
We propose a principled account on multiclass spectral clustering. Given a discrete clustering formulation, we first solve a relaxed continuous optimization problem by eigendecomp...
Stella X. Yu, Jianbo Shi
CORR
2010
Springer
249views Education» more  CORR 2010»
13 years 3 months ago
Performance Analysis of Spectral Clustering on Compressed, Incomplete and Inaccurate Measurements
Spectral clustering is one of the most widely used techniques for extracting the underlying global structure of a data set. Compressed sensing and matrix completion have emerged a...
Blake Hunter, Thomas Strohmer
MICCAI
2008
Springer
14 years 4 months ago
Spectral Clustering as a Diagnostic Tool in Cross-Sectional MR Studies: An Application to Mild Dementia
Abstract. Structural imaging investigations commonly apply a segmentation step followed by the extraction of feature data that can be used to compare or discriminate groups. We pre...
Paul Aljabar, Daniel Rueckert, William R. Crum