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» A Genetic Algorithm for Clustering on Very Large Data Sets
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VISUALIZATION
2005
IEEE
14 years 2 months ago
Distributed Data Management for Large Volume Visualization
We propose a distributed data management scheme for large data visualization that emphasizes efficient data sharing and access. To minimize data access time and support users wit...
Jinzhu Gao, Jian Huang, C. Ryan Johnson, Scott Atc...
KDD
2004
ACM
190views Data Mining» more  KDD 2004»
14 years 9 months ago
Kernel k-means: spectral clustering and normalized cuts
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
CORR
2007
Springer
132views Education» more  CORR 2007»
13 years 8 months ago
Fast Algorithm and Implementation of Dissimilarity Self-Organizing Maps
In many real-world applications, data cannot be accurately represented by vectors. In those situations, one possible solution is to rely on dissimilarity measures that enable a se...
Brieuc Conan-Guez, Fabrice Rossi, Aïcha El Go...
TEC
2002
81views more  TEC 2002»
13 years 8 months ago
Genetic object recognition using combinations of views
We investigate the application of genetic algorithms (GAs) for recognizing real two-dimensional (2-D) or three-dimensional (3-D) objects from 2-D intensity images, assuming that th...
George Bebis, Evangelos A. Yfantis, Sushil J. Loui...
KDD
2012
ACM
235views Data Mining» more  KDD 2012»
11 years 11 months ago
A near-linear time approximation algorithm for angle-based outlier detection in high-dimensional data
Outlier mining in d-dimensional point sets is a fundamental and well studied data mining task due to its variety of applications. Most such applications arise in high-dimensional ...
Ninh Pham, Rasmus Pagh