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PAKDD
2011
ACM
209views Data Mining» more  PAKDD 2011»
12 years 10 months ago
Spectral Analysis for Billion-Scale Graphs: Discoveries and Implementation
Abstract. Given a graph with billions of nodes and edges, how can we find patterns and anomalies? Are there nodes that participate in too many or too few triangles? Are there clos...
U. Kang, Brendan Meeder, Christos Faloutsos
EUSFLAT
2009
152views Fuzzy Logic» more  EUSFLAT 2009»
13 years 5 months ago
Learning Fuzzy Rule Based Classifier in High Performance Computing Environment
-- An approach to estimate the number of rules by spectral analysis of the training dataset has been recently proposed [1]. This work presents an analysis of such a method in high ...
Vinicius da F. Vieira, Alexandre Evsukoff, Beatriz...
DIS
2006
Springer
13 years 11 months ago
Clustering Pairwise Distances with Missing Data: Maximum Cuts Versus Normalized Cuts
Abstract. Clustering algorithms based on a matrix of pairwise similarities (kernel matrix) for the data are widely known and used, a particularly popular class being spectral clust...
Jan Poland, Thomas Zeugmann
SDM
2009
SIAM
225views Data Mining» more  SDM 2009»
14 years 4 months ago
Integrated KL (K-means - Laplacian) Clustering: A New Clustering Approach by Combining Attribute Data and Pairwise Relations.
Most datasets in real applications come in from multiple sources. As a result, we often have attributes information about data objects and various pairwise relations (similarity) ...
Fei Wang, Chris H. Q. Ding, Tao Li
ICML
2006
IEEE
14 years 8 months ago
Discriminative cluster analysis
Clustering is one of the most widely used statistical tools for data analysis. Among all existing clustering techniques, k-means is a very popular method because of its ease of pr...
Fernando De la Torre, Takeo Kanade