Laura Azzimonti

Int. J. Approx. Reason., 2022

Using Mixed-Effect Models to Learn Bayesian Networks from Related Data Sets.

[BibT_eX]

[DOI]

Christopher Marquis

CoRR, 2022

Using Mixed-Effects Models to Learn Bayesian Networks from Related Data Sets.

[BibT_eX]

[DOI]

Christopher Marquis

Proceedings of the International Conference on Probabilistic Graphical Models, 2022

2020

Correction to: Efficient feature selection using shrinkage estimators.

[BibT_eX]

[DOI]

Konstantinos Sechidis

Mach. Learn., 2020

Structure Learning from Related Data Sets with a Hierarchical Bayesian Score.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Probabilistic Graphical Models, 2020

2019

Efficient feature selection using shrinkage estimators.

[BibT_eX]

[DOI]

Konstantinos Sechidis

Mach. Learn., 2019

Modeling spatially dependent functional data via regression with differential regularization.

[BibT_eX]

[DOI]

J. Multivar. Anal., 2019

Hierarchical estimation of parameters in Bayesian networks.

[BibT_eX]

[DOI]

Marco Zaffalon

Comput. Stat. Data Anal., 2019

2017

Hierarchical Multinomial-Dirichlet Model for the Estimation of Conditional Probability Tables.

[BibT_eX]

[DOI]

Marco Zaffalon

Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

2014

Mixed Finite Elements for Spatial Regression with PDE Penalization.

[BibT_eX]

[DOI]

SIAM/ASA J. Uncertain. Quantification, 2014

2013

Nonlinear nonparametric mixed-effects models for unsupervised classification.

[BibT_eX]

[DOI]