2 citations · 3 across the 2 of their papers we have counts for
3 papers
Data-Driven Logistic Regression Ensembles With Applications in Genomics
Anthony-Alexander Christidis, Stefan Van Aelst, Ruben Zamar
Advances in data collecting technologies in genomics have significantly increased the need for tools designed to study the genetic basis of many diseases. Effective statistical met…
Objective-Driven Ensembles: Bridging the Gap Between Interpretable Sparsity and Algorithmic Prediction
Anthony Christidis, Stefan Van Aelst, Ruben Zamar
Sparse methods (e.g., Best Subset Selection, Elastic Net) are the standard approach for obtaining interpretable models, but they can suffer from high variance and vulnerability to…
Multi-Model Subset Selection
Anthony-Alexander Christidis, Stefan Van Aelst, Ruben Zamar
The two primary approaches for high-dimensional regression problems are sparse methods (e.g., best subset selection, which uses the L0-norm in the penalty) and ensemble methods (e.…