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GD
2005
Springer
14 years 2 months ago
Drawing Clustered Graphs in Three Dimensions
Clustered graph is a very useful model for drawing large and complex networks. This paper presents a new method for drawing clustered graphs in three dimensions. The method uses a ...
Joshua Wing Kei Ho, Seok-Hee Hong
PAMI
2007
202views more  PAMI 2007»
13 years 8 months ago
Weighted Graph Cuts without Eigenvectors A Multilevel Approach
—A variety of clustering algorithms have recently been proposed to handle data that is not linearly separable; spectral clustering and kernel k-means are two of the main methods....
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
COMBINATORICS
2007
87views more  COMBINATORICS 2007»
13 years 8 months ago
Recognizing Cluster Algebras of Finite Type
We compute the list of all minimal 2-infinite diagrams, which are cluster algebraic analogues of extended Dynkin graphs.
Ahmet I. Seven
BIBE
2007
IEEE
195views Bioinformatics» more  BIBE 2007»
14 years 2 months ago
Finding Clusters of Positive and Negative Coregulated Genes in Gene Expression Data
— In this paper, we propose a system for finding partial positive and negative coregulated gene clusters in microarray data. Genes are clustered together if they show the same p...
Kerstin Koch, Stefan Schönauer, Ivy Jansen, J...
CVPR
2004
IEEE
14 years 10 months ago
Spatially Coherent Clustering Using Graph Cuts
Feature space clustering is a popular approach to image segmentation, in which a feature vector of local properties (such as intensity, texture or motion) is computed at each pixe...
Ramin Zabih, Vladimir Kolmogorov