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» Maximal Vector Computation in Large Data Sets
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VLUDS
2010
184views Visualization» more  VLUDS 2010»
13 years 4 months ago
Advanced Visualization and Interaction Techniques for Large High-Resolution Displays
Large high-resolution displays combine the images of multiple smaller display devices to form one large display area. A total resolution that can easily comprise several hundred m...
Sebastian Thelen
ICANN
2007
Springer
14 years 3 months ago
Sparse Least Squares Support Vector Regressors Trained in the Reduced Empirical Feature Space
Abstract. In this paper we discuss sparse least squares support vector regressors (sparse LS SVRs) defined in the reduced empirical feature space, which is a subspace of mapped tr...
Shigeo Abe, Kenta Onishi
OL
2007
103views more  OL 2007»
13 years 8 months ago
Support vector machine via nonlinear rescaling method
In this paper we construct the linear support vector machine (SVM) based on the nonlinear rescaling (NR) methodology (see [9, 11, 10] and references therein). The formulation of t...
Roman A. Polyak, Shen-Shyang Ho, Igor Griva
ICDE
2003
IEEE
160views Database» more  ICDE 2003»
14 years 10 months ago
HD-Eye - Visual Clustering of High dimensional Data
Clustering of large data bases is an important research area with a large variety of applications in the data base context. Missing in most of the research efforts are means for g...
Alexander Hinneburg, Daniel A. Keim, Markus Wawryn...
IMSCCS
2006
IEEE
14 years 3 months ago
Estimation Of Cross-Hybridization Signals Using Support Vector Regression
Microarray technology is a powerful biotechnology tool which allows researchers to simultaneously evaluate the expression of thousands of genes, if not the entire expressed genome...
Yijun Sun, Li Liu, Mick Popp, William G. Farmerie