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» Optimal feature selection for support vector machines
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SADM
2010
128views more  SADM 2010»
13 years 6 months ago
Online training on a budget of support vector machines using twin prototypes
: This paper proposes twin prototype support vector machine (TVM), a constant space and sublinear time support vector machine (SVM) algorithm for online learning. TVM achieves its ...
Zhuang Wang, Slobodan Vucetic
ISBI
2004
IEEE
14 years 8 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...
DAGM
2009
Springer
14 years 2 months ago
Pedestrian Detection by Probabilistic Component Assembly
We present a novel pedestrian detection system based on probabilistic component assembly. A part-based model is proposed which uses three parts consisting of head-shoulder, torso a...
Martin Rapus, Stefan Munder, Gregory Baratoff, Joa...
IJCNN
2007
IEEE
14 years 1 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
ICML
2004
IEEE
14 years 8 months ago
Text categorization with many redundant features: using aggressive feature selection to make SVMs competitive with C4.5
Text categorization algorithms usually represent documents as bags of words and consequently have to deal with huge numbers of features. Most previous studies found that the major...
Evgeniy Gabrilovich, Shaul Markovitch