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AdaBoost

Known as: Adaboosting 
AdaBoost, short for "Adaptive Boosting", is a machine learning meta-algorithm formulated by Yoav Freund and Robert Schapire who won the Gödel Prize… Expand
Wikipedia

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2013
Review
2013
Boosting is an approach to machine learning based on the idea of creating a highly accurate prediction rule by combining many… Expand
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Highly Cited
2008
Highly Cited
2008
The use of SVM (Support Vector Machine) as component classifier in AdaBoost may seem like going against the grain of the Boosting… Expand
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Highly Cited
2006
Highly Cited
2006
We present an algorithm that predicts musical genre and artist from an audio waveform. Our method uses the ensemble learner… Expand
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Highly Cited
2006
Highly Cited
2006
Our goal is to automatically segment and recognize basic human actions, such as stand, walk and wave hands, from a sequence of… Expand
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Highly Cited
2005
Highly Cited
2005
Boosting is a technique of combining a set weak classifiers to form one high-performance prediction rule. Boosting was… Expand
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Highly Cited
2004
Highly Cited
2004
Recently ensemble methods like ADABOOST have been applied successfully in many problems, while seemingly defying the problems of… Expand
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Highly Cited
2004
Highly Cited
2004
We give a unified account of boosting and logistic regression in which each learning problem is cast in terms of optimization of… Expand
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Highly Cited
2004
Highly Cited
2004
In this paper, we propose a rotation invariant multi-view face detection method based on Real Adaboost algorithm. Human faces are… Expand
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Highly Cited
2001
Highly Cited
2001
This paper develops a new approach for extremely fast detection in domains where the distribution of positive and negative… Expand
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Highly Cited
2000
Highly Cited
2000
We propse a new boosting algorithm that mends some of the problems that have been detected in the so far most successful boosting… Expand