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AIEDAM
2008
127views more  AIEDAM 2008»
13 years 9 months ago
Evolving blackbox quantum algorithms using genetic programming
Although it is known that quantum computers can solve certain computational problems exponentially faster than classical computers, only a small number of quantum algorithms have ...
Ralf Stadelhofer, Wolfgang Banzhaf, Dieter Suter
CORR
2008
Springer
159views Education» more  CORR 2008»
13 years 9 months ago
Face Detection Using Adaboosted SVM-Based Component Classifier
: Boosting is a general method for improving the accuracy of any given learning algorithm. In this paper we employ combination of Adaboost with Support Vector Machine (SVM) as comp...
Seyyed Majid Valiollahzadeh, Abolghasem Sayadiyan,...
JFR
2008
87views more  JFR 2008»
13 years 9 months ago
Hough based terrain classification for realtime detection of drivable ground
The usability of mobile robots for surveillance, search and rescue missions can be significantly improved by intelligent functionalities decreasing the cognitive load on the opera...
Jann Poppinga, Andreas Birk 0002, Kaustubh Pathak
PAA
2002
13 years 9 months ago
Bagging, Boosting and the Random Subspace Method for Linear Classifiers
: Recently bagging, boosting and the random subspace method have become popular combining techniques for improving weak classifiers. These techniques are designed for, and usually ...
Marina Skurichina, Robert P. W. Duin
PR
2010
158views more  PR 2010»
13 years 8 months ago
Out-of-bag estimation of the optimal sample size in bagging
The performance of m-out-of-n bagging with and without replacement in terms of the sampling ratio (m/n) is analyzed. Standard bagging uses resampling with replacement to generate ...
Gonzalo Martínez-Muñoz, Alberto Su&a...