3 papers
math.ST2026
Non-asymptotic two-sample kernel testing with the spectrally truncated normalized MMD
Perrine Lacroix, Bertrand Michel, Franck Picard +1
Kernel methods provide a flexible and powerful framework for nonparametric statistical testing by embedding probability distributions into a reproducing kernel Hilbert space (RKHS)…
stat.AP2025
A comprehensive guideline for regularization-path variable selection in high-dimensional Gaussian linear regression
Perrine Lacroix, Mélina Gallopin, Marie-Laure Martin
This paper provides a comprehensive comparison of complete regularization-path-based variable selection procedures in high-dimensional Gaussian linear regression. Our simulation st…
math.ST2024
Trade-off between predictive performance and FDR control for high-dimensional Gaussian model selection
Perrine Lacroix, Marie-Laure Martin
In the context of high-dimensional Gaussian linear regression for ordered variables, we study the variable selection procedure via the minimization of the penalized least-squares c…