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» Graph Mining based on a Data Partitioning Approach
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124
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IDEAL
2009
Springer
15 years 10 months ago
Supervised Feature Extraction Using Hilbert-Schmidt Norms
We propose a novel, supervised feature extraction procedure, based on an unbiased estimator of the Hilbert-Schmidt independence criterion (HSIC). The proposed procedure can be dire...
Povilas Daniusis, Pranas Vaitkus
109
Voted
ICDM
2008
IEEE
109views Data Mining» more  ICDM 2008»
15 years 10 months ago
Learning by Propagability
In this paper, we present a novel feature extraction framework, called learning by propagability. The whole learning process is driven by the philosophy that the data labels and o...
Bingbing Ni, Shuicheng Yan, Ashraf A. Kassim, Loon...
142
Voted
DMIN
2006
137views Data Mining» more  DMIN 2006»
15 years 5 months ago
Discovering of Frequent Itemsets with CP-mine Algorithm
Efficient algorithms to discover frequent patterns are crucial in data mining research. Several effective data structures, such as two-dimensional arrays, graphs, trees, and tries ...
Nuansri Denwattana, Yutthana Treewai
157
Voted
GIS
2010
ACM
15 years 1 months ago
Natural neighbor interpolation based grid DEM construction using a GPU
With modern LiDAR technology the amount of topographic data, in the form of massive point clouds, has increased dramatically. One of the most fundamental GIS tasks is to construct...
Alex Beutel, Thomas Mølhave, Pankaj K. Agar...
126
Voted
APWEB
2005
Springer
15 years 9 months ago
Mining Quantitative Associations in Large Database
Association Rule Mining algorithms operate on a data matrix to derive association rule, discarding the quantities of the items, which contains valuable information. In order to mak...
Chenyong Hu, Yongji Wang, Benyu Zhang, Qiang Yang,...