3 papers
stat.ML2026
A Bregman Perspective on Classification and Regression Trees
Mathias Bourel
Classification and Regression Trees (CART) constitute one of the most influential paradigms in statistical learning. Although a variety of impurity measures have been proposed for…
stat.ML2026
Geometric Domain Adaptation via Optimal Transport for Linear Regression in R^2
Brian Britos, Mathias Bourel
Optimal Transport has become recently a powerful method for domain adaptation by aligning source and target distributions. We study a supervised domain adaptation problem where sou…
stat.ML2025
Optimal Transport-Based Domain Adaptation for Rotated Linear Regression
Brian Britos, Mathias Bourel
Optimal Transport (OT) has proven effective for domain adaptation (DA) by aligning distributions across domains with differing statistical properties. Building on the approach of C…