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» Nonlinear functional regression: a functional RKHS approach
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ESANN
2006
13 years 7 months ago
Variants of Unsupervised Kernel Regression: General cost functions
We present an extension to a recent method for learning of nonlinear manifolds, which allows to incorporate general cost functions. We focus on the -insensitive loss and visually d...
Stefan Klanke, Helge Ritter
CVPR
2006
IEEE
14 years 14 days ago
Estimating Intrinsic Component Images using Non-Linear Regression
Images can be represented as the composition of multiple intrinsic component images, such as shading, albedo, and noise images. In this paper, we present a method for estimating i...
Marshall F. Tappen, Edward H. Adelson, William T. ...
ERSA
2009
387views Hardware» more  ERSA 2009»
13 years 4 months ago
Implementation of the Gauss-Newton Algorithm for Non-linear Least-mean-squares Fitting in FPGA Devices
Abstract-- The paper presents the implementation of nonlinear least-squares regression in a Field Programmable Gate Array (FPGA) device. The implemented algorithm is very performan...
Andrea Abba, Antonio Manenti, Andrea Suardi, Angel...
CSDA
2006
145views more  CSDA 2006»
13 years 6 months ago
Improved predictions penalizing both slope and curvature in additive models
A new method is proposed to estimate the nonlinear functions in an additive regression model. Usually, these functions are estimated by penalized least squares, penalizing the cur...
Magne Aldrin
NN
2008
Springer
143views Neural Networks» more  NN 2008»
13 years 4 months ago
A new nonlinear similarity measure for multichannel signals
We propose a novel similarity measure, called the correntropy coefficient, sensitive to higher order moments of the signal statistics based on a similarity function called the cro...
Jian-Wu Xu, Hovagim Bakardjian, Andrzej Cichocki, ...