4 papers
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…
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…
Concentration and excess risk bounds for imbalanced classification with synthetic oversampling
Touqeer Ahmad, Mohammadreza M. Kalan, François Portier +1
Synthetic oversampling of minority examples using SMOTE and its variants is a leading strategy for addressing imbalanced classification problems. Despite the success of this approa…
Speeding up Monte Carlo Integration: Control Neighbors for Optimal Convergence
Rémi Leluc, François Portier, Johan Segers +1
A novel linear integration rule called is proposed in which nearest neighbor estimates act as control variates to speed up the convergence rate of the…