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ICCV
2011
IEEE
14 years 4 months ago
Source Constrained Clustering
We consider the problem of quantizing data generated from disparate sources, e.g. subjects performing actions with different styles, movies with particular genre bias, various con...
Ekaterina Taralova, Fernando DelaTorre, Martial He...
SDM
2008
SIAM
168views Data Mining» more  SDM 2008»
15 years 5 months ago
Semi-Supervised Clustering via Matrix Factorization
The recent years have witnessed a surge of interests of semi-supervised clustering methods, which aim to cluster the data set under the guidance of some supervisory information. U...
Fei Wang, Tao Li, Changshui Zhang
EOR
2006
135views more  EOR 2006»
15 years 4 months ago
Principles of scatter search
Scatter search is an evolutionary method that has been successfully applied to hard optimization problems. The fundamental concepts and principles of the method were first propose...
Rafael Martí, Manuel Laguna, Fred Glover
AEI
2005
99views more  AEI 2005»
15 years 4 months ago
Comparison among five evolutionary-based optimization algorithms
Evolutionary algorithms (EAs) are stochastic search methods that mimic the natural biological evolution and/or the social behavior of species. Such algorithms have been developed ...
Emad Elbeltagi, Tarek Hegazy, Donald E. Grierson
CVPR
2009
IEEE
1133views Computer Vision» more  CVPR 2009»
16 years 11 months ago
Sparse Subspace Clustering
We propose a method based on sparse representation (SR) to cluster data drawn from multiple low-dimensional linear or affine subspaces embedded in a high-dimensional space. Our ...
Ehsan Elhamifar, René Vidal