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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… 
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Related topics

Related topics

34 relations
Adaptive algorithmBackfitting algorithmBackpropagationBag-of-words model in computer vision

Broader (1)

Ensemble learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2011
2011
Complexity Reduced Face Detection Using Probability-Based Face Mask Prefiltering and Pixel-Based Hierarchical-Feature Adaboosting
The Adaboosting has attracted attention for its efficient face-detection performance. However, in the training process, the large… 
2011
2011
Likelihood ratio based features for a trained biometric score fusion
2010
2010
Face and iris localization using templates designed by particle swarm optimization
2009
2009
The individual borrowers recognition: Single and ensemble trees
2008
2008
Wavelet energy signature and GLCM features-based fingerprint anti-spoofing
This paper proposes a texture-based method to spoof-proof a fingerprint biometric system. The fundamental basis of this anti… 
2007
2007
Boosting the Performance of Web Spam Detection with Ensemble Under-Sampling Classification
Anti-spam has become one of the top challenges for the Web search. In this paper, we explore the Web spam detection as a binary… 
Review
2006
Review
2006
Scaling large margin classifiers for spoken language understanding
2006
2006
A Real-Time Facial Expression Recognition using the STAAM
This paper proposes a real-time person independent facial expression recognition in two folds. One is using the stereo active… 
2005
2005
Research of English text classification methods based on semantic meaning
To overcome the limitations of traditional text classification approaches based on bag-of-words representation and to effectively… 
2003
2003
‘ Fuzzy ’ vs ‘ Non-fuzzy ’ in Combining Classifiers Designed by Boosting
Boosting is recognized as one of the most successful techniques for generating classifier ensembles. Typically, the classifier… 
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