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» Nonlinear functional regression: a functional RKHS approach
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IJCAI
2007
13 years 8 months ago
Kernel Conjugate Gradient for Fast Kernel Machines
We propose a novel variant of the conjugate gradient algorithm, Kernel Conjugate Gradient (KCG), designed to speed up learning for kernel machines with differentiable loss functio...
Nathan D. Ratliff, J. Andrew Bagnell
NIPS
2003
13 years 8 months ago
Nonlinear Filtering of Electron Micrographs by Means of Support Vector Regression
Nonlinear filtering can solve very complex problems, but typically involve very time consuming calculations. Here we show that for filters that are constructed as a RBF network ...
Roland Vollgraf, Michael Scholz, Ian A. Meinertzha...
ECML
2004
Springer
14 years 3 days ago
Experiments in Value Function Approximation with Sparse Support Vector Regression
Abstract. We present first experiments using Support Vector Regression as function approximator for an on-line, sarsa-like reinforcement learner. To overcome the batch nature of S...
Tobias Jung, Thomas Uthmann
ISCI
2008
165views more  ISCI 2008»
13 years 6 months ago
Support vector regression from simulation data and few experimental samples
This paper considers nonlinear modeling based on a limited amount of experimental data and a simulator built from prior knowledge. The problem of how to best incorporate the data ...
Gérard Bloch, Fabien Lauer, Guillaume Colin...
ICCV
2011
IEEE
12 years 6 months ago
Regression from Local Features for Viewpoint and Pose Estimation
In this paper we propose a framework for learning a regression function form a set of local features in an image. The regression is learned from an embedded representation that re...
Marwan Torki, Ahmed Elgammal