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stat.ML2026
Highly Adaptive Principal Component Regression
Mingxun Wang, Alejandro Schuler, Mark van der Laan +1
The Highly Adaptive Lasso (HAL) is a nonparametric regression method that achieves almost dimension-free convergence rates under minimal smoothness assumptions, but its implementat…
stat.ML2024
Highly Adaptive Ridge
Alejandro Schuler, Alexander Hagemeister, Mark van der Laan
In this paper we propose the Highly Adaptive Ridge (HAR): a regression method that achieves a dimension-free L2 convergence rate in the class of right-continuous functio…