Boosting (machine learning)

Known as: Boost, Boosting (meta-algorithm), Boosting methods for object categorization 
Boosting is a machine learning ensemble meta-algorithm for primarily reducing bias, and also variance in supervised learning, and a family of machine… (More)
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Topic mentions per year

Topic mentions per year

1977-2018
05010015019772018

Papers overview

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Highly Cited
2010
Highly Cited
2010
Transfer learning allows leveraging the knowledge of source domains, available a priori, to help training a classifier for a… (More)
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Highly Cited
2009
Highly Cited
2009
Semi-supervised learning has attracted a significant amount of attention in pattern recognition and machine learning. Most… (More)
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Highly Cited
2007
Highly Cited
2007
Traditional machine learning makes a basic assumption: the training and test data should be under the same distribution. However… (More)
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Highly Cited
2006
Highly Cited
2006
In this paper, we propose a novel ensemble-based approach to boost performance of traditional Linear Discriminant Analysis (LDA… (More)
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Highly Cited
2006
Highly Cited
2006
The Maximum Margin Planning (MMP) (Ratliff et al., 2006) algorithm solves imitation learning problems by learning linear mappings… (More)
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Highly Cited
2004
Highly Cited
2004
Learning from imbalanced data sets, where the number of examples of one (majority) class is much higher than the others, presents… (More)
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Highly Cited
2000
Highly Cited
2000
We present an approach for image retrieval using a very large number of highly selective features and efficient learning of… (More)
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Highly Cited
1999
Highly Cited
1999
Gradient boosting constructs additive regression models by sequentially tting a simple parameterized function (base learner) to… (More)
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Highly Cited
1999
Highly Cited
1999
Boosting is a general method for improving the accuracy of any given learning algorithm. This short paper introduces the boosting… (More)
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Highly Cited
1996
Highly Cited
1996
Breiman's bagging and Freund and Schapire's boosting are recent methods for improving the predictive power of classiier learning… (More)
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