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GECCO
2006
Springer
150views Optimization» more  GECCO 2006»
14 years 1 months ago
Nonlinear parametric regression in genetic programming
Genetic programming has been considered a promising approach for function approximation since it is possible to optimize both the functional form and the coefficients. However, it...
Yung-Keun Kwon, Sung-Soon Choi, Byung Ro Moon
SCFBM
2008
738views more  SCFBM 2008»
13 years 9 months ago
Purposeful selection of variables in logistic regression
The main problem in any model-building situation is to choose from a large set of covariates those that should be included in the "best" model. A decision to keep a vari...
Zoran Bursac, C. Heath Gauss, David Keith Williams...
NIPS
2001
13 years 11 months ago
Infinite Mixtures of Gaussian Process Experts
We present an extension to the Mixture of Experts (ME) model, where the individual experts are Gaussian Process (GP) regression models. Using an input-dependent adaptation of the ...
Carl Edward Rasmussen, Zoubin Ghahramani
DIS
2009
Springer
14 years 4 months ago
An Iterative Learning Algorithm for Within-Network Regression in the Transductive Setting
Within-network regression addresses the task of regression in partially labeled networked data where labels are sparse and continuous. Data for inference consist of entities associ...
Annalisa Appice, Michelangelo Ceci, Donato Malerba
CSDA
2006
97views more  CSDA 2006»
13 years 10 months ago
Bandwidth selection for a class of difference-based variance estimators in the nonparametric regression: A possible approach
A possible approach to bandwidth selection for difference-based variance estimators in the nonparametric regression is proposed. The approach is based on the crossvalidation-type ...
M. Levine