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» An e-Process Selection Model
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EWC
2010
91views more  EWC 2010»
15 years 3 months ago
Multiobjective global surrogate modeling, dealing with the 5-percent problem
When dealing with computationally expensive simulation codes or process measurement data, surrogate modeling methods are firmly established as facilitators for design space explor...
Dirk Gorissen, Ivo Couckuyt, Eric Laermans, Tom Dh...
ESANN
2008
15 years 6 months ago
A multiple testing procedure for input variable selection in neural networks
In this paper a novel procedure to select the input nodes in neural network modeling is presented and discussed. The approach is developed in a multiple testing framework and so it...
Michele La Rocca, Cira Perna
TIP
2011
114views more  TIP 2011»
14 years 11 months ago
Constrained Acquisition of Ink Spreading Curves From Printed Color Images
— Today’s spectral reflection prediction models are able to predict the reflection spectra of printed color images with an accuracy as high as the reproduction variability allo...
Thomas Bugnon, Roger D. Hersch
IJAR
2010
130views more  IJAR 2010»
15 years 3 months ago
Learning locally minimax optimal Bayesian networks
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
Tomi Silander, Teemu Roos, Petri Myllymäki
137
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SCIA
2007
Springer
122views Image Analysis» more  SCIA 2007»
15 years 10 months ago
Individual Discriminative Face Recognition Models Based on Subsets of Features
Abstract. The accuracy of data classification methods depends considerably on the data representation and on the selected features. In this work, the elastic net model selection i...
Line Harder Clemmensen, David Delgado Gomez, Bjarn...