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ICML
2005
IEEE
16 years 5 months ago
Semi-supervised graph clustering: a kernel approach
Semi-supervised clustering algorithms aim to improve clustering results using limited supervision. The supervision is generally given as pairwise constraints; such constraints are...
Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Ray...
ICDM
2009
IEEE
133views Data Mining» more  ICDM 2009»
15 years 11 months ago
On K-Means Cluster Preservation Using Quantization Schemes
This work examines under what conditions compression methodologies can retain the outcome of clustering operations. We focus on the popular k-Means clustering algorithm and we dem...
Deepak S. Turaga, Michail Vlachos, Olivier Versche...
AUSAI
2009
Springer
15 years 11 months ago
A Graph Distance Based Structural Clustering Approach for Networks
In the era of information explosion, structured data emerge on a large scale. As a description of structured data, network has drawn attention of researchers in many subjects. Netw...
Xin Su, Chunping Li
SDM
2004
SIAM
225views Data Mining» more  SDM 2004»
15 years 5 months ago
Active Semi-Supervision for Pairwise Constrained Clustering
Semi-supervised clustering uses a small amount of supervised data to aid unsupervised learning. One typical approach specifies a limited number of must-link and cannotlink constra...
Sugato Basu, Arindam Banerjee, Raymond J. Mooney
SDM
2003
SIAM
125views Data Mining» more  SDM 2003»
15 years 5 months ago
Scalable, Balanced Model-based Clustering
This paper presents a general framework for adapting any generative (model-based) clustering algorithm to provide balanced solutions, i.e., clusters of comparable sizes. Partition...
Shi Zhong, Joydeep Ghosh