Showing stat.MEShow all
3 papers · 1 filter
stat.ME2026
Fast Robust Regression via Orthogonal Block Updates
Anthony Christidis, Matias Salibian-Barrera
Robust regression methods, particularly MM-estimators, are essential for analyzing datasets where heavy-tailed noise or high-leverage outliers may be present. Algorithms to compute…
stat.ME2026
Fast and Scalable Cellwise-Robust Ensembles for High-Dimensional Data
Anthony Christidis, Jeyshinee Pyneeandee, Gabriela Cohen Freue
Variable selection and ensemble methods are central to high-dimensional modelling, enabling the identification of relevant predictors and the construction of stable predictive sign…
stat.ME2023
Robust Multi-Model Subset Selection
Anthony-Alexander Christidis, Gabriela Cohen-Freue
Outlying observations can be challenging to handle and adversely affect subsequent analyses, especially in data with increasing dimensional complexity. Although outliers are not al…