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» Boosting Methods for Regression
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111
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SDM
2009
SIAM
172views Data Mining» more  SDM 2009»
15 years 11 months ago
Travel-Time Prediction Using Gaussian Process Regression: A Trajectory-Based Approach.
This paper is concerned with the task of travel-time prediction for an arbitrary origin-destination pair on a map. Unlike most of the existing studies, which focus only on a parti...
Sei Kato, Tsuyoshi Idé
103
Voted
ICDM
2007
IEEE
154views Data Mining» more  ICDM 2007»
15 years 6 months ago
Cocktail Ensemble for Regression
This paper is motivated to improve the performance of individual ensembles using a hybrid mechanism in the regression setting. Based on an error-ambiguity decomposition, we formal...
Yang Yu, Zhi-Hua Zhou, Kai Ming Ting
CSDA
2010
111views more  CSDA 2010»
15 years 2 months ago
Mixtures of regressions with predictor-dependent mixing proportions
We extend the standard mixture of linear regressions model by allowing mixing proportions to be modeled nonparametrically as a function of the predictors. This framework allows fo...
D. S. Young, D. R. Hunter
DKE
2007
88views more  DKE 2007»
15 years 2 months ago
Regression analysis for massive datasets
In this paper, a two-stage block hypothesis testing following the idea of Fan, Lin and Cheng (2004) is proposed for massive data regression analysis. Variables selection criteria ...
Tsai-Hung Fan, Dennis K. J. Lin, Kuang-Fu Cheng
100
Voted
PR
2006
89views more  PR 2006»
15 years 2 months ago
Gaussian fields for semi-supervised regression and correspondence learning
Gaussian fields (GF) have recently received considerable attention for dimension reduction and semi-supervised classification. In this paper we show how the GF framework can be us...
Jakob J. Verbeek, Nikos A. Vlassis