Stefan Van Aelst | DeepAI

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Featured Co-authors

Yixin Wang
32 publications
Andreas Christmann
12 publications
Ioannis Kalogridis
9 publications
Gerda Claeskens
8 publications
Matias Salibian-Barrera
8 publications
Ruben Zamar
6 publications
Anthony-Alexander Christidis
2 publications
Anthony Christidis
2 publications
Holger Cevallos Valdiviezo
1 publication
Kris Peremans
1 publication

∙ 04/17/2022

Multi-Model Ensemble Optimization

Methodology and optimization algorithms for sparse regression are extend...

0 Anthony-Alexander Christidis, et al. ∙

∙ 01/27/2022

Robust and efficient estimation of nonparametric generalized linear models

Generalized linear models are flexible tools for the analysis of diverse...

0 Gerda Claeskens, et al. ∙

∙ 02/17/2021

Split Modeling for High-Dimensional Logistic Regression

A novel method is proposed to learn an ensemble of logistic classificati...

0 Anthony-Alexander Christidis, et al. ∙

∙ 12/24/2020

Robust penalized spline estimation with difference penalties

Penalized spline estimation with discrete difference penalties (P-spline...

0 Ioannis Kalogridis, et al. ∙

∙ 08/03/2020

Robust optimal estimation of the mean function from discretely sampled functional data

Estimating the mean of functional data is a central problem in functiona...

0 Ioannis Kalogridis, et al. ∙

∙ 08/23/2019

M-type penalized splines for functional linear regression

Functional data analysis is a fast evolving branch of modern statistics,...

0 Ioannis Kalogridis, et al. ∙

∙ 06/20/2019

M-type penalized splines with auxiliary scale estimation

Penalized spline smoothing is a popular and flexible method of obtaining...

0 Ioannis Kalogridis, et al. ∙

∙ 12/13/2018

Split regression modeling

In this note we study the benefits of splitting variables variables for ...

0 Anthony Christidis, et al. ∙

∙ 06/30/2018

Robust functional regression based on principal components

Functional data analysis is a fast evolving branch of modern statistics ...

0 Ioannis Kalogridis, et al. ∙

∙ 03/27/2018

Fast Computation of Robust Subspace Estimators

Dimension reduction is often an important step in the analysis of high-d...

0 Holger Cevallos Valdiviezo, et al. ∙

∙ 01/15/2018

Robust Inference for Seemingly Unrelated Regression Models

Seemingly unrelated regression models generalize linear regression model...

0 Kris Peremans, et al. ∙

∙ 11/27/2017

Robust variable screening for regression using factor profiling

Sure Independence Screening is a fast procedure for variable selection i...

0 Yixin Wang, et al. ∙

∙ 11/08/2011

On the stability of bootstrap estimators

It is shown that bootstrap approximations of an estimator which is based...

0 Andreas Christmann, et al. ∙

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