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ICML
2004
IEEE
14 years 9 months ago
Bayesian inference for transductive learning of kernel matrix using the Tanner-Wong data augmentation algorithm
In kernel methods, an interesting recent development seeks to learn a good kernel from empirical data automatically. In this paper, by regarding the transductive learning of the k...
Zhihua Zhang, Dit-Yan Yeung, James T. Kwok
ICDM
2006
IEEE
146views Data Mining» more  ICDM 2006»
14 years 2 months ago
Boosting Kernel Models for Regression
This paper proposes a general boosting framework for combining multiple kernel models in the context of both classification and regression problems. Our main approach is built on...
Ping Sun, Xin Yao
ESANN
2008
13 years 10 months ago
GeoKernels: modeling of spatial data on geomanifolds
This paper presents a review of methodology for semi-supervised modeling with kernel methods, when the manifold assumption is guaranteed to be satisfied. It concerns environmental ...
Alexei Pozdnoukhov, Mikhail F. Kanevski
KDD
2002
ACM
109views Data Mining» more  KDD 2002»
14 years 9 months ago
MARK: a boosting algorithm for heterogeneous kernel models
Kristin P. Bennett, Michinari Momma, Mark J. Embre...