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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.
Highly Cited
2011
Highly Cited
2011
Classifying eye and head movement artifacts in EEG signals
Brain Computer Interfaces has some exciting prospects such as controlling devices at the speed of thought. However BCI technology… 
2011
2011
Boosted Exemplar Learning for Action Recognition and Annotation
Human action recognition and annotation is an active research topic in computer vision. How to model various actions, varying… 
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… 
Highly Cited
2008
Highly Cited
2008
Efficient scan-window based object detection using GPGPU
We describe an efficient design for scan-window based object detectors using a general purpose graphics hardware computing (GPGPU… 
2008
2008
Constructions at work or at rest?
Abstract We question whether Adele Goldberg fulfills her self-declared goal in “Constructions at Work”, i.e. to develop a usage… 
Highly Cited
2007
Highly Cited
2007
Detecting Pedestrians by Learning Shapelet Features
I introduce in this paper a method of detecting pedestrians, presented by Payam Sabzmeydani and Greg Mori [1]. Local gradient… 
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
Highly Cited
2004
Highly Cited
2004
Text classification by boosting weak learners based on terms and concepts
Document representations for text classification are typically based on the classical bag-of-words paradigm. This approach comes… 
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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