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ECAI
2010
Springer
14 years 11 months ago
Feature Selection by Approximating the Markov Blanket in a Kernel-Induced Space
The proposed feature selection method aims to find a minimum subset of the most informative variables for classification/regression by efficiently approximating the Markov Blanket ...
Qiang Lou, Zoran Obradovic
SIAMSC
2010
170views more  SIAMSC 2010»
14 years 8 months ago
Adaptive ADER Methods Using Kernel-Based Polyharmonic Spline WENO Reconstruction
An adaptive ADER finite volume method on unstructured meshes is proposed. The method combines high order polyharmonic spline WENO reconstruction with high order flux evaluation. Po...
Terhemen Aboiyar, Emmanuil H. Georgoulis, Armin Is...
ISNN
2007
Springer
15 years 7 months ago
Extensions of Manifold Learning Algorithms in Kernel Feature Space
Manifold learning algorithms have been proven to be capable of discovering some nonlinear structures. However, it is hard for them to extend to test set directly. In this paper, a ...
Yaoliang Yu, Peng Guan, Liming Zhang
ICAPR
2005
Springer
15 years 7 months ago
Missing Data Estimation Using Polynomial Kernels
Abstract. In this paper, we deal with the problem of partially observed objects. These objects are defined by a set of points and their shape variations are represented by a statis...
Maxime Berar, Michel Desvignes, Gérard Bail...
ICCV
2005
IEEE
15 years 7 months ago
Fast Global Kernel Density Mode Seeking with Application to Localisation and Tracking
We address the problem of seeking the global mode of a density function using the mean shift algorithm. Mean shift, like other gradient ascent optimisation methods, is susceptible...
Chunhua Shen, Michael J. Brooks, Anton van den Hen...