45 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Centre de Mathématiques Appliquées de l'École polytechniqueFR2 papers
- Centre National de la Recherche ScientifiqueFR2 papers
- École PolytechniqueFR2 papers
- Institut national de recherche en sciences et technologies du numériqueFR2 papers
- Laboratoire de Probabilités, Statistique et ModélisationFR2 papers
- Apple (United States)US1 paper
- California Institute of TechnologyUS1 paper
- CELESTE: statistique mathématique et apprentissageFR1 paper
- Centre de Recherche en Économie et StatistiqueFR1 paper
- Centre de recherches mathématiquesCA1 paper
- Centre Inria de SaclayFR1 paper
- École Nationale de la Statistique et de l'Analyse de l'InformationFR1 paper
6 papers
R-NL: Covariance Matrix Estimation for Elliptical Distributions based on Nonlinear Shrinkage
Simon Hediger, Jeffrey Näf, Michael Wolf
We combine Tyler's robust estimator of the dispersion matrix with nonlinear shrinkage. This approach delivers a simple and fast estimator of the dispersion matrix in elliptical mod…
Reweighting the RCT for generalization: finite sample error and variable selection
Bénédicte Colnet, Julie Josse, Gaël Varoquaux +1
Randomized Controlled Trials (RCTs) may suffer from limited scope. In particular, samples may be unrepresentative: some RCTs over- or under- sample individuals with certain charact…
Model-based Clustering with Missing Not At Random Data
Aude Sportisse, Matthieu Marbac, Fabien Laporte +4
Model-based unsupervised learning, as any learning task, stalls as soon as missing data occurs. This is even more true when the missing data are informative, or said missing not at…
Causal effect on a target population: a sensitivity analysis to handle missing covariates
Bénédicte Colnet, Julie Josse, Erwan Scornet +1
Randomized Controlled Trials (RCTs) are often considered the gold standard for estimating causal effect, but they may lack external validity when the population eligible to the RCT…
Missing Data Imputation using Optimal Transport
Boris Muzellec, Julie Josse, Claire Boyer +1
Missing data is a crucial issue when applying machine learning algorithms to real-world datasets. Starting from the simple assumption that two batches extracted randomly from the s…
Goodness-of-fit tests for Laplace, Gaussian and exponential power distributions based on -th power skewness and kurtosis
Alain Desgagné, Pierre Lafaye de Micheaux, Frédéric Ouimet
Temperature data, like many other measurements in quantitative fields, are usually modeled using a normal distribution. However, some distributions can offer a better fit while avo…