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DAGM
2006
Springer
15 years 1 months ago
Model Selection in Kernel Methods Based on a Spectral Analysis of Label Information
Abstract. We propose a novel method for addressing the model selection problem in the context of kernel methods. In contrast to existing methods which rely on hold-out testing or t...
Mikio L. Braun, Tilman Lange, Joachim M. Buhmann
TITB
2008
102views more  TITB 2008»
14 years 9 months ago
Nonlinear Support Vector Machine Visualization for Risk Factor Analysis Using Nomograms and Localized Radial Basis Function Kern
Nonlinear classifiers, e.g., support vector machines (SVMs) with radial basis function (RBF) kernels, have been used widely for automatic diagnosis of diseases because of their hig...
Baek Hwan Cho, Hwanjo Yu, Jong Shill Lee, Young Jo...
ICASSP
2011
IEEE
14 years 1 months ago
Stochastic behavior analysis of the Gaussian Kernel Least Mean Square algorithm
Like its linear counterpart, the Kernel Least Mean Square (KLMS) algorithm is also becoming popular in nonlinear adaptive filtering due to its simplicity and robustness. The “k...
Wemerson D. Parreira, José Carlos M. Bermud...
NIPS
2007
14 years 11 months ago
Learning with Transformation Invariant Kernels
This paper considers kernels invariant to translation, rotation and dilation. We show that no non-trivial positive definite (p.d.) kernels exist which are radial and dilation inv...
Christian Walder, Olivier Chapelle
ESANN
2004
14 years 11 months ago
Sparse Bayesian kernel logistic regression
In this paper we present a simple hierarchical Bayesian treatment of the sparse kernel logistic regression (KLR) model based MacKay's evidence approximation. The model is re-p...
Gavin C. Cawley, Nicola L. C. Talbot