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KDD
2004
ACM
118views Data Mining» more  KDD 2004»
14 years 10 months ago
Parallel computation of high dimensional robust correlation and covariance matrices
The computation of covariance and correlation matrices are critical to many data mining applications and processes. Unfortunately the classical covariance and correlation matrices...
James Chilson, Raymond T. Ng, Alan Wagner, Ruben H...
ICDM
2009
IEEE
125views Data Mining» more  ICDM 2009»
14 years 4 months ago
A Fully Automated Method for Discovering Community Structures in High Dimensional Data
—Identifying modules, or natural communities, in large complex networks is fundamental in many fields, including social sciences, biological sciences and engineering. Recently s...
Jianhua Ruan
AUSDM
2007
Springer
193views Data Mining» more  AUSDM 2007»
14 years 4 months ago
Are Zero-suppressed Binary Decision Diagrams Good for Mining Frequent Patterns in High Dimensional Datasets?
Mining frequent patterns such as frequent itemsets is a core operation in many important data mining tasks, such as in association rule mining. Mining frequent itemsets in high-di...
Elsa Loekito, James Bailey
SDM
2004
SIAM
253views Data Mining» more  SDM 2004»
13 years 11 months ago
Density-Connected Subspace Clustering for High-Dimensional Data
Several application domains such as molecular biology and geography produce a tremendous amount of data which can no longer be managed without the help of efficient and effective ...
Peer Kröger, Hans-Peter Kriegel, Karin Kailin...
ICCV
2007
IEEE
14 years 11 months ago
3D Variational Brain Tumor Segmentation using a High Dimensional Feature Set
Tumor segmentation from MRI data is an important but time consuming task performed manually by medical experts. Automating this process is challenging due to the high diversity in...
Albert Murtha, Dana Cobzas, Mark Schmidt, Martin J...