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» Comparisons Between Data Clustering Algorithms
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TNN
2010
155views Management» more  TNN 2010»
13 years 3 months ago
Incorporating the loss function into discriminative clustering of structured outputs
Clustering using the Hilbert Schmidt independence criterion (CLUHSIC) is a recent clustering algorithm that maximizes the dependence between cluster labels and data observations ac...
Wenliang Zhong, Weike Pan, James T. Kwok, Ivor W. ...
MM
2005
ACM
122views Multimedia» more  MM 2005»
14 years 2 months ago
Image clustering with tensor representation
We consider the problem of image representation and clustering. Traditionally, an n1 × n2 image is represented by a vector in the Euclidean space Rn1×n2 . Some learning algorith...
Xiaofei He, Deng Cai, Haifeng Liu, Jiawei Han
PRL
2006
117views more  PRL 2006»
13 years 9 months ago
Feature selection in robust clustering based on Laplace mixture
A wrapped feature selection process is proposed in the context of robust clustering based on Laplace mixture models. The clustering approach we consider is a generalization of the...
Aurélien Cord, Christophe Ambroise, Jean Pi...
ISBI
2002
IEEE
14 years 9 months ago
Parcellation of brain images with anatomical and functional constraints for fMRI data analysis
In this paper we propose a methodology for brain parcellation with anatomical and functional constraints dedicated to fMRI data analysis. The aim is to provide a representation of...
Denis Rivière, Ferath Kherif, Guillaume Fla...
SAC
2009
ACM
14 years 3 months ago
Visualization of clustered directed acyclic graphs with node interleaving
Graph drawing and visualization represent structural information ams of abstract graphs and networks. An important subset of graphs is directed acyclic graphs (DAGs). E-Spring alg...
Pushpa Kumar, Kang Zhang