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» Nonlinear functional regression: a functional RKHS approach
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SCALESPACE
1999
Springer
13 years 11 months ago
A Geometric Functional for Derivatives Approximation
We develop on estimation method, for the derivative field of an image based on Bayesian approach which is formulated in a geometric way. The Maximum probability configuration of ...
Nir A. Sochen, Robert M. Haralick, Yehoshua Y. Zee...
TSMC
2008
99views more  TSMC 2008»
13 years 7 months ago
Robust Regularized Kernel Regression
Robust regression techniques are critical to fitting data with noise in real-world applications. Most previous work of robust kernel regression is usually formulated into a dual fo...
Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu
ICRA
2009
IEEE
143views Robotics» more  ICRA 2009»
14 years 2 months ago
Randomized model predictive control for robot navigation
— We suggest a new navigation approach to mobile robots, within a nonlinear model predictive control framework where a navigation function is used as a control Lyapunov function....
Jorge L. Piovesan, Herbert G. Tanner
SIAMNUM
2010
131views more  SIAMNUM 2010»
13 years 2 months ago
A Rational Interpolation Scheme with Superpolynomial Rate of Convergence
The purpose of this study is to construct a high-order interpolation scheme for arbitrary scattered datasets. The resulting function approximation is an interpolation function when...
Qiqi Wang, Parviz Moin, Gianluca Iaccarino
IJCNN
2007
IEEE
14 years 1 months ago
Generalised Kernel Machines
Abstract— The generalised linear model (GLM) is the standard approach in classical statistics for regression tasks where it is appropriate to measure the data misfit using a lik...
Gavin C. Cawley, Gareth J. Janacek, Nicola L. C. T...