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SDM
2011
SIAM
14 years 21 days ago
2011
SIAM
Sparse principal component analysis (PCA) imposes extra constraints or penalty terms to the standard PCA to achieve sparsity. In this paper, we first introduce an efficient algor...
AUSDM
2007
Springer
15 years 1 months ago
2007
Springer
Population based real-life datasets often contain smaller clusters of unusual sub-populations. While these clusters, called `hot spots', are small and sparse, they are usuall...
ICDM
2002
IEEE
15 years 2 months ago
2002
IEEE
Clustering large data sets of high dimensionality has always been a serious challenge for clustering algorithms. Many recently developed clustering algorithms have attempted to ad...
ICCS
2009
Springer
15 years 4 months ago
2009
Springer
A vast amount of documents in the Web have duplicates, which is a challenge for developing efficient methods that would compute clusters of similar documents. In this paper we use ...
DCC
2000
IEEE
15 years 2 months ago
2000
IEEE
As large-scale databases become commonplace, there has been signi cant interest in mining them for commercial purposes. One of the basic tasks that underlies many of these mining ...