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JMLR
2008
83views more  JMLR 2008»
13 years 10 months ago
Generalization from Observed to Unobserved Features by Clustering
We argue that when objects are characterized by many attributes, clustering them on the basis of a random subset of these attributes can capture information on the unobserved attr...
Eyal Krupka, Naftali Tishby
SDM
2007
SIAM
122views Data Mining» more  SDM 2007»
13 years 11 months ago
Incremental Spectral Clustering With Application to Monitoring of Evolving Blog Communities
In recent years, spectral clustering method has gained attentions because of its superior performance compared to other traditional clustering algorithms such as K-means algorithm...
Huazhong Ning, Wei Xu, Yun Chi, Yihong Gong, Thoma...
CVPR
2006
IEEE
14 years 4 months ago
Nonlinear Mean Shift for Clustering over Analytic Manifolds
The mean shift algorithm is widely applied for nonparametric clustering in Euclidean spaces. Recently, mean shift was generalized for clustering on matrix Lie groups. We further e...
Raghav Subbarao, Peter Meer
CPM
2004
Springer
108views Combinatorics» more  CPM 2004»
14 years 3 months ago
Quadratic Time Algorithms for Finding Common Intervals in Two and More Sequences
A popular approach in comparative genomics is to locate groups or clusters of orthologous genes in multiple genomes and to postulate functional association between the genes contai...
Thomas Schmidt, Jens Stoye
JBI
2006
107views Bioinformatics» more  JBI 2006»
13 years 10 months ago
Knowledge guided analysis of microarray data
To microarray expression data analysis, it is well accepted that biological knowledge-guided clustering techniques show more advantages than pure mathematical techniques. In this ...
Zhuo Fang, Jiong Yang, Yixue Li, Qing-ming Luo, Le...