3 citations · 3 across the 4 of their papers we have counts for
7 papers
Asymptotic Normality of Infinite Centered Random Forests -Application to Imbalanced Classification
Moria Mayala, Erwan Scornet, Charles Tillier +1
Many classification tasks involve imbalanced data, in which a class is largely underrepresented. Several techniques consists in creating a rebalanced dataset on which a classifier…
Infinite random forests for imbalanced classification tasks
Moria Mayala, Olivier Wintenberger, Charles Tillier +1
We study predictive probability inference in classification tasks using random forests under class imbalance. We focus on two simplified variants of Breiman's algorithm, namely sub…
Hidden regular variation for point processes and the single/multiple large point heuristic
Clément Dombry, Charles Tillier, Olivier Wintenberger
We consider regular variation for marked point processes with independent heavy-tailed marks and prove a single large point heuristic: the limit measure is concentrated on the cone…
Multivariate boundary regression models
Leonie Selk, Charles Tillier, Orlando Marigliano
In this work, we consider a multivariate regression model with one-sided errors. We assume for the regression function to lie in a general Hölder class and estimate it via a nonpar…
Weighted Empirical Risk Minimization: Sample Selection Bias Correction based on Importance Sampling
Robin Vogel, Mastane Achab, Stéphan Clémençon +1
We consider statistical learning problems, when the distribution of the training observations differs from the distribution involved in the risk o…
Semi-parametric transformation boundary regression models
Natalie Neumeyer, Leonie Selk, Charles Tillier
In the context of nonparametric regression models with one-sided errors, we consider parametric transformations of the response variable in order to obtain independence between the…