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» Variable selection using neural-network models
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108
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IJCNN
2006
IEEE
15 years 6 months ago
Small-catchment flood forecasting and drainage network extraction using computational intelligence
— Forecast, detection and warning of severe weather and related hydro-geological risks is becoming one of the major issues for civil protection. The use of computational intellig...
Erika Coppola, Barbara Tomassetti, Marco Verdecchi...
100
Voted
ICMLA
2008
15 years 2 months ago
Estimation of Exercise Energy Expenditure Using a Wrist-Worn Accelerometer: A Linear Mixed Model Approach with Fixed-Effect Vari
This article presents an approach to estimating exercise energy expenditure based on acceleration measurements from a wrist-worn biaxial sensor. The method uses the linear mixed m...
Eija Haapalainen, Perttu Laurinen, Juha Rönin...
75
Voted
SAC
2002
ACM
15 years 8 days ago
On Bayesian model and variable selection using MCMC
Petros Dellaportas, Jonathan J. Forster, Ioannis N...
ICAISC
2010
Springer
15 years 5 months ago
Quasi-parametric Recovery of Hammerstein System Nonlinearity by Smart Model Selection
In the paper we recover a Hammerstein system nonlinearity. Hammerstein systems, incorporating nonlinearity and dynamics, play an important role in various applications, and e¤ecti...
Zygmunt Hasiewicz, Grzegorz Mzyk, Przemyslaw Sliwi...
110
Voted
TIT
1998
126views more  TIT 1998»
15 years 8 days ago
An Asymptotic Property of Model Selection Criteria
—Probability models are estimated by use of penalized log-likelihood criteria related to AIC and MDL. The accuracies of the density estimators are shown to be related to the trad...
Yuhong Yang, Andrew R. Barron