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KDD
2008
ACM
16 years 3 months ago
2008
ACM
We propose a family of novel cost-sensitive boosting methods for multi-class classification by applying the theory of gradient boosting to p-norm based cost functionals. We establ...
139
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ICML
2007
IEEE
16 years 3 months ago
2007
IEEE
A general framework is proposed for gradient boosting in supervised learning problems where the loss function is defined using a kernel over the output space. It extends boosting ...
148
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CVPR
2009
IEEE
15 years 6 months ago
2009
IEEE
Face detection plays an important role in many vision applications. Since Viola and Jones [1] proposed the first real-time AdaBoost based object detection system, much effort has ...
120
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IR
2010
15 years 1 months ago
2010
Abstract We present a new ranking algorithm that combines the strengths of two previous methods: boosted tree classification, and LambdaRank, which has been shown to be empiricall...
CVPR
2005
IEEE
16 years 4 months ago
2005
IEEE
We present and analyze a novel regularization technique based on enhancing our dataset with corrupted copies of our original data. The motivation is that since the learning algori...