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» Boosting Methods for Regression
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ICML
2006
IEEE
14 years 9 months ago
Bayesian regression with input noise for high dimensional data
This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
Jo-Anne Ting, Aaron D'Souza, Stefan Schaal
ESEM
2008
ACM
13 years 10 months ago
Fit data selection for software effort estimation models
To construct a better multivariate regression model for software effort estimation, this paper proposes a method to select projects as a fit data from a given project data set bas...
Koji Toda, Akito Monden, Ken-ichi Matsumoto
ICASSP
2007
IEEE
14 years 2 months ago
Integrating Relevance Feedback in Boosting for Content-Based Image Retrieval
Many content-based image retrieval applications suffer from small sample set and high dimensionality problems. Relevance feedback is often used to alleviate those problems. In thi...
Jie Yu, Yijuan Lu, Yuning Xu, Nicu Sebe, Qi Tian
DAGM
2008
Springer
13 years 10 months ago
Boosting for Model-Based Data Clustering
In this paper a novel and generic approach for model-based data clustering in a boosting framework is presented. This method uses the forward stagewise additive modeling to learn t...
Amir Saffari, Horst Bischof
NIPS
2003
13 years 10 months ago
Mutual Boosting for Contextual Inference
Mutual Boosting is a method aimed at incorporating contextual information to augment object detection. When multiple detectors of objects and parts are trained in parallel using A...
Michael Fink 0002, Pietro Perona