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TKDE
2008
148views more  TKDE 2008»
9 years 11 months ago
Semisupervised Clustering with Metric Learning using Relative Comparisons
Semisupervised clustering algorithms partition a given data set using limited supervision from the user. The success of these algorithms depends on the type of supervision and also...
Nimit Kumar, Krishna Kummamuru
PKDD
2015
Springer
16views Data Mining» more  PKDD 2015»
4 years 7 months ago
A Kernel-Learning Approach to Semi-supervised Clustering with Relative Distance Comparisons
We consider the problem of clustering a given dataset into k clusters subject to an additional set of constraints on relative distance comparisons between the data items. The addit...
Ehsan Amid, Aristides Gionis, Antti Ukkonen
PR
2010
156views more  PR 2010»
9 years 10 months ago
Semi-supervised clustering with metric learning: An adaptive kernel method
Most existing representative works in semi-supervised clustering do not sufficiently solve the violation problem of pairwise constraints. On the other hand, traditional kernel met...
Xuesong Yin, Songcan Chen, Enliang Hu, Daoqiang Zh...
SDM
2009
SIAM
225views Data Mining» more  SDM 2009»
10 years 8 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
ECML
2006
Springer
10 years 3 months ago
Subspace Metric Ensembles for Semi-supervised Clustering of High Dimensional Data
A critical problem in clustering research is the definition of a proper metric to measure distances between points. Semi-supervised clustering uses the information provided by the ...
Bojun Yan, Carlotta Domeniconi
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