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IJCNN
2007
IEEE
14 years 4 months ago
Probability Density Function Estimation Using Orthogonal Forward Regression
— Using the classical Parzen window estimate as the target function, the kernel density estimation is formulated as a regression problem and the orthogonal forward regression tec...
Sheng Chen, Xia Hong, Chris J. Harris
JMLR
2010
102views more  JMLR 2010»
13 years 4 months ago
Unsupervised Supervised Learning I: Estimating Classification and Regression Errors without Labels
Estimating the error rates of classifiers or regression models is a fundamental task in machine learning which has thus far been studied exclusively using supervised learning tech...
Pinar Donmez, Guy Lebanon, Krishnakumar Balasubram...
BMCBI
2010
158views more  BMCBI 2010»
13 years 10 months ago
Validation of differential gene expression algorithms: Application comparing fold-change estimation to hypothesis testing
Background: Sustained research on the problem of determining which genes are differentially expressed on the basis of microarray data has yielded a plethora of statistical algorit...
Corey M. Yanofsky, David R. Bickel
MOC
2002
81views more  MOC 2002»
13 years 9 months ago
Optimal a priori error estimates for the hp-version of the local discontinuous Galerkin method for convection--diffusion problem
We study the convergence properties of the hp-version of the local discontinuous Galerkin finite element method for convection-diffusion problems; we consider a model problem in a ...
Paul Castillo, Bernardo Cockburn, Dominik Schö...
ANNPR
2006
Springer
14 years 1 months ago
Support Vector Regression Using Mahalanobis Kernels
Abstract. In our previous work we have shown that Mahalanobis kernels are useful for support vector classifiers both from generalization ability and model selection speed. In this ...
Yuya Kamada, Shigeo Abe