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math.ST2026
Pointwise convergence of purely random partition estimators: from random trees to prototype rules
Jérémy Bettinger, François Portier, Adrien Saumard
We study pointwise convergence rates of purely random partition estimators in nonparametric regression, where the partition -- into hyper-rectangles by purely random trees, or into…
stat.ML2026
Riemannian Stochastic Optimization for Sufficient Dimension Reduction
Thibault Pautrel, François Portier
Sufficient dimension reduction (SDR) makes high-dimensional regression tractable by projecting the covariates onto a low-dimensional subspace that preserves the conditional mean of…