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» A Boosting Algorithm for Regression
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COLT
2000
Springer
15 years 1 months ago
Leveraging for Regression
In this paper we examine master regression algorithms that leverage base regressors by iteratively calling them on modified samples. The most successful leveraging algorithm for c...
Nigel Duffy, David P. Helmbold
ICML
2007
IEEE
15 years 10 months ago
Gradient boosting for kernelized output spaces
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 ...
Florence d'Alché-Buc, Louis Wehenkel, Pierr...
ISBI
2011
IEEE
14 years 1 months ago
Hippocampus segmentation using a stable maximum likelihood classifier ensemble algorithm
We develop a new algorithm to segment the hippocampus from MR images. Our method uses a new classifier ensemble algorithm to correct segmentation errors produced by a multi-atlas...
Hongzhi Wang, Jung Wook Suh, Sandhitsu R. Das, Mur...
IJCAI
2007
14 years 11 months ago
Simple Training of Dependency Parsers via Structured Boosting
Recently, significant progress has been made on learning structured predictors via coordinated training algorithms such as conditional random fields and maximum margin Markov ne...
Qin Iris Wang, Dekang Lin, Dale Schuurmans
78
Voted
ML
2007
ACM
106views Machine Learning» more  ML 2007»
14 years 9 months ago
Surrogate maximization/minimization algorithms and extensions
Abstract Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. A...
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung