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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, Mingxun Wang +1
In this paper we propose the Highly Adaptive Ridge (HAR): a regression method that achieves an dimension-free convergence rate (up to log factors) in the…