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CORR
2011
Springer
193views Education» more  CORR 2011»
8 years 1 months ago
The Rate of Convergence of AdaBoost
The AdaBoost algorithm was designed to combine many “weak” hypotheses that perform slightly better than random guessing into a “strong” hypothesis that has very low error....
Indraneel Mukherjee, Cynthia Rudin, Robert E. Scha...
COLT
2010
Springer
8 years 8 months ago
The Convergence Rate of AdaBoost
Abstract. We pose the problem of determining the rate of convergence at which AdaBoost minimizes exponential loss. Boosting is the problem of combining many "weak," high-...
Robert E. Schapire
JMLR
2002
140views more  JMLR 2002»
8 years 9 months ago
On Boosting with Polynomially Bounded Distributions
We construct a framework which allows an algorithm to turn the distributions produced by some boosting algorithms into polynomially smooth distributions (w.r.t. the PAC oracle...
Nader H. Bshouty, Dmitry Gavinsky
ML
2000
ACM
144views Machine Learning» more  ML 2000»
8 years 10 months ago
MultiBoosting: A Technique for Combining Boosting and Wagging
MultiBoosting is an extension to the highly successful AdaBoost technique for forming decision committees. MultiBoosting can be viewed as combining AdaBoost with wagging. It is abl...
Geoffrey I. Webb
SIGKDD
2008
150views more  SIGKDD 2008»
8 years 10 months ago
Learning to improve area-under-FROC for imbalanced medical data classification using an ensemble method
This paper presents our solution for KDD Cup 2008 competition that aims at optimizing the area under ROC for breast cancer detection. We exploited weighted-based classification me...
Hung-Yi Lo, Chun-Min Chang, Tsung-Hsien Chiang, Ch...
IJCV
2007
113views more  IJCV 2007»
8 years 10 months ago
Boosting Sex Identification Performance
This paper presents a method based on AdaBoost to identify the sex of a person from a low resolution grayscale picture of their face. The method described here is implemented in a...
Shumeet Baluja, Henry A. Rowley
CORR
2008
Springer
159views Education» more  CORR 2008»
8 years 10 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,...
APIN
2010
108views more  APIN 2010»
8 years 10 months ago
A low variance error boosting algorithm
Abstract. This paper introduces a robust variant of AdaBoost, cwAdaBoost, that uses weight perturbation to reduce variance error, and is particularly effective when dealing with da...
Ching-Wei Wang, Andrew Hunter
NIPS
2003
8 years 11 months ago
On the Dynamics of Boosting
In order to understand AdaBoost’s dynamics, especially its ability to maximize margins, we derive an associated simplified nonlinear iterated map and analyze its behavior in lo...
Cynthia Rudin, Ingrid Daubechies, Robert E. Schapi...
NIPS
2003
8 years 11 months ago
Boosting versus Covering
We investigate improvements of AdaBoost that can exploit the fact that the weak hypotheses are one-sided, i.e. either all its positive (or negative) predictions are correct. In pa...
Kohei Hatano, Manfred K. Warmuth
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