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» Optimization on Support Vector Machines
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ICDM
2008
IEEE
160views Data Mining» more  ICDM 2008»
15 years 4 months ago
Direct Zero-Norm Optimization for Feature Selection
Zero-norm, defined as the number of non-zero elements in a vector, is an ideal quantity for feature selection. However, minimization of zero-norm is generally regarded as a combi...
Kaizhu Huang, Irwin King, Michael R. Lyu
ACCV
2010
Springer
14 years 5 months ago
Efficient Structured Support Vector Regression
Support Vector Regression (SVR) has been a long standing problem in machine learning, and gains its popularity on various computer vision tasks. In this paper, we propose a structu...
Ke Jia, Lei Wang, Nianjun Liu
SCHOLARPEDIA
2008
89views more  SCHOLARPEDIA 2008»
14 years 8 months ago
Support vector clustering
We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...
Asa Ben-Hur
ISBI
2004
IEEE
15 years 10 months ago
Population Classification Based on Structural Morphometry of Cortical Sulci
This paper describes a classification system discriminating male and female brains from morphometric features of cortical sulci. This system is tested on a database of 143 brains,...
Edouard Duchesnay, Jean-Francois Mangin, Alexis Ro...
CIARP
2010
Springer
14 years 7 months ago
A New Algorithm for Training SVMs Using Approximate Minimal Enclosing Balls
Abstract. It has been shown that many kernel methods can be equivalently formulated as minimal-enclosing-ball (MEB) problems in certain feature space. Exploiting this reduction eff...
Emanuele Frandi, Maria Grazia Gasparo, Stefano Lod...