- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
1 Online-Ressource.
- Language
-
Englisch
- Bibliographic citation
-
Regularized regressions for parametric models based on separated representations ; volume:10 ; number:1 ; day:9 ; month:3 ; year:2023 ; pages:1-26 ; date:12.2023
Advanced modeling and simulation in engineering sciences ; 10, Heft 1 (9.3.2023), 1-26, 12.2023
- Creator
- Contributor
-
SpringerLink (Online service)
- DOI
-
10.1186/s40323-023-00240-4
- URN
-
urn:nbn:de:101:1-2502211355302.029739398795
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:28 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Sancarlos, Abel
- Champaney, Victor
- Cueto, Elías
- Chinesta, Francisco
- SpringerLink (Online service)
Other Objects (12)
Enhanced parametric shape descriptions in PGD-based space separated representations
Flexible, non-parametric modeling using regularized neural networks
Regularized parametric survival modeling to improve risk prediction models
A modified EM-type algorithm to estimate semi-parametric mixtures of non-parametric regressions
Generalized kernel regularized least squares estimator with parametric error covariance
Separated representations of 3D elastic solutions in shell geometries
Multiple Regimes in Cross-Region Growth Regressions with Spatial Dependence: A Parametric and a Semi-parametric Approach
Artificial regressions
Artificial Regressions
Non-parametric Bayesian mixture of sparse regressions with application towards feature selection for statistical downscaling
Mean volatility regressions
Unconditional Quantile Regressions
Enhanced parametric shape descriptions in PGD-based space separated representations
Flexible, non-parametric modeling using regularized neural networks
Regularized parametric survival modeling to improve risk prediction models
A modified EM-type algorithm to estimate semi-parametric mixtures of non-parametric regressions
Generalized kernel regularized least squares estimator with parametric error covariance
Separated representations of 3D elastic solutions in shell geometries
Multiple Regimes in Cross-Region Growth Regressions with Spatial Dependence: A Parametric and a Semi-parametric Approach
Artificial regressions
Artificial Regressions
Non-parametric Bayesian mixture of sparse regressions with application towards feature selection for statistical downscaling
Mean volatility regressions
Unconditional Quantile Regressions
Enhanced parametric shape descriptions in PGD-based space separated representations
Flexible, non-parametric modeling using regularized neural networks
Regularized parametric survival modeling to improve risk prediction models
A modified EM-type algorithm to estimate semi-parametric mixtures of non-parametric regressions
Generalized kernel regularized least squares estimator with parametric error covariance
Separated representations of 3D elastic solutions in shell geometries
Multiple Regimes in Cross-Region Growth Regressions with Spatial Dependence: A Parametric and a Semi-parametric Approach
Artificial regressions
Artificial Regressions
Non-parametric Bayesian mixture of sparse regressions with application towards feature selection for statistical downscaling
Mean volatility regressions