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IJON
2006
89views more  IJON 2006»
13 years 9 months ago
Flexible kernels for RBF networks
In this paper we propose a novel approach for modeling kernels in Radial Basis Function networks. The method provides an extra degree of flexibility to the kernel structure. This ...
André O. Falcão, Thibault Langlois, ...
ICAISC
2004
Springer
14 years 3 months ago
Optimization of Centers' Positions for RBF Nets with Generalized Kernels
The problem of locating centers for radial basis functions in neural networks is discussed. The proposed approach allows us to apply the results from the theory of optimum experime...
Ewaryst Rafajlowicz, Miroslaw Pawlak
TNN
2010
176views Management» more  TNN 2010»
13 years 4 months ago
Sparse approximation through boosting for learning large scale kernel machines
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...
Ping Sun, Xin Yao
ICRA
2007
IEEE
155views Robotics» more  ICRA 2007»
14 years 4 months ago
Value Function Approximation on Non-Linear Manifolds for Robot Motor Control
— The least squares approach works efficiently in value function approximation, given appropriate basis functions. Because of its smoothness, the Gaussian kernel is a popular an...
Masashi Sugiyama, Hirotaka Hachiya, Christopher To...
FGR
2006
IEEE
255views Biometrics» more  FGR 2006»
14 years 1 months ago
Incremental Kernel SVD for Face Recognition with Image Sets
Non-linear subspaces derived using kernel methods have been found to be superior compared to linear subspaces in modeling or classification tasks of several visual phenomena. Such...
Tat-Jun Chin, Konrad Schindler, David Suter