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» On-line support vector machines and optimization strategies
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ICML
2004
IEEE
16 years 1 months ago
Multiple kernel learning, conic duality, and the SMO algorithm
While classical kernel-based classifiers are based on a single kernel, in practice it is often desirable to base classifiers on combinations of multiple kernels. Lanckriet et al. ...
Francis R. Bach, Gert R. G. Lanckriet, Michael I. ...
86
Voted
ICDM
2008
IEEE
160views Data Mining» more  ICDM 2008»
15 years 7 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
116
Voted
IJCAI
2007
15 years 2 months ago
Detection of Cognitive States from fMRI Data Using Machine Learning Techniques
Over the past decade functional Magnetic Resonance Imaging (fMRI) has emerged as a powerful technique to locate activity of human brain while engaged in a particular task or cogni...
Vishwajeet Singh, Krishna P. Miyapuram, Raju S. Ba...
ISBI
2004
IEEE
16 years 1 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...
125
Voted
CIARP
2010
Springer
14 years 10 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...