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JMLR
2006
136views more  JMLR 2006»
14 years 9 months ago
Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis
In this paper we consider a novel Bayesian interpretation of Fisher's discriminant analysis. We relate Rayleigh's coefficient to a noise model that minimises a cost base...
Tonatiuh Peña Centeno, Neil D. Lawrence
66
Voted
ICASSP
2009
IEEE
15 years 4 months ago
A regularized kernel-based approach to unsupervised audio segmentation
We introduce a regularized kernel-based rule for unsupervised change detection based on a simpler version of the recently proposed kernel Fisher discriminant ratio. Compared to ot...
Zaïd Harchaoui, Felicien Vallet, Alexandre Lu...
NIPS
2007
14 years 11 months ago
An Analysis of Inference with the Universum
We study a pattern classification algorithm which has recently been proposed by Vapnik and coworkers. It builds on a new inductive principle which assumes that in addition to pos...
Fabian H. Sinz, Olivier Chapelle, Alekh Agarwal, B...
100
Voted
CVPR
2005
IEEE
15 years 11 months ago
Coupled Kernel-Based Subspace Learning
It was prescriptive that an image matrix was transformed into a vector before the kernel-based subspace learning. In this paper, we take the Kernel Discriminant Analysis (KDA) alg...
Shuicheng Yan, Dong Xu, Lei Zhang, Benyu Zhang, Ho...
ICANN
2005
Springer
15 years 3 months ago
Handwritten Digit Recognition with Nonlinear Fisher Discriminant Analysis
Abstract. To generalize the Fisher Discriminant Analysis (FDA) algorithm to the case of discriminant functions belonging to a nonlinear, finite dimensional function space F (Nonli...
Pietro Berkes