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JMLR
2010
143views more  JMLR 2010»
13 years 2 months ago
Regularized Discriminant Analysis, Ridge Regression and Beyond
Fisher linear discriminant analysis (FDA) and its kernel extension--kernel discriminant analysis (KDA)--are well known methods that consider dimensionality reduction and classific...
Zhihua Zhang, Guang Dai, Congfu Xu, Michael I. Jor...
CVPR
2007
IEEE
14 years 9 months ago
Face Recognition Using Kernel Ridge Regression
In this paper, we present novel ridge regression (RR) and kernel ridge regression (KRR) techniques for multivariate labels and apply the methods to the problem of face recognition...
Senjian An, Wanquan Liu, Svetha Venkatesh
ESANN
2003
13 years 9 months ago
Approximately unbiased estimation of conditional variance in heteroscedastic kernel ridge regression
In this paper we extend a form of kernel ridge regression for data characterised by a heteroscedastic noise process (introduced in Foxall et al. [1]) in order to provide approxima...
Gavin C. Cawley, Nicola L. C. Talbot, Robert J. Fo...
PROCEDIA
2010
109views more  PROCEDIA 2010»
13 years 2 months ago
Ridge regression ensemble for toxicity prediction
Traditional methods of assessing chemical toxicity of various compounds require tests on animals, which raises ethical concerns and is expensive. Current legislation may lead to a...
Marcin Budka, Bogdan Gabrys
TIT
2002
164views more  TIT 2002»
13 years 7 months ago
On the generalization of soft margin algorithms
Generalization bounds depending on the margin of a classifier are a relatively recent development. They provide an explanation of the performance of state-of-the-art learning syste...
John Shawe-Taylor, Nello Cristianini