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» Maximal Vector Computation in Large Data Sets
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IJON
2008
173views more  IJON 2008»
13 years 6 months ago
Support vector machine classification for large data sets via minimum enclosing ball clustering
Support vector machine (SVM) is a powerful technique for data classification. Despite of its good theoretic foundations and high classification accuracy, normal SVM is not suitabl...
Jair Cervantes, Xiaoou Li, Wen Yu, Kang Li
JMLR
2007
104views more  JMLR 2007»
13 years 6 months ago
Comments on the "Core Vector Machines: Fast SVM Training on Very Large Data Sets"
In a recently published paper in JMLR, Tsang et al. (2005) present an algorithm for SVM called Core Vector Machines (CVM) and illustrate its performances through comparisons with ...
Gaëlle Loosli, Stéphane Canu
CSDA
2010
133views more  CSDA 2010»
13 years 3 months ago
Optimized fixed-size kernel models for large data sets
A modified active subset selection method based on quadratic R
Kris De Brabanter, Jos De Brabanter, Johan A. K. S...
ICDM
2009
IEEE
110views Data Mining» more  ICDM 2009»
14 years 1 months ago
Finding Maximal Fully-Correlated Itemsets in Large Databases
—Finding the most interesting correlations among items is essential for problems in many commercial, medical, and scientific domains. Much previous research focuses on finding ...
Lian Duan, William Nick Street
SIGMOD
2003
ACM
152views Database» more  SIGMOD 2003»
14 years 6 months ago
Using Sets of Feature Vectors for Similarity Search on Voxelized CAD Objects
In modern application domains such as multimedia, molecular biology and medical imaging, similarity search in database systems is becoming an increasingly important task. Especial...
Hans-Peter Kriegel, Stefan Brecheisen, Peer Kr&oum...