68 citations
- Centre de Recherche en Économie et StatistiqueFR25 papers
- ENSAE ParisFR22 papers
- Institut de recherche mathématique de RennesFR11 papers
- Centre for Research in Engineering Surface TechnologyIE10 papers
- Centre National de la Recherche ScientifiqueFR10 papers
- Université de RennesFR10 papers
- Institut National des Sciences Appliquées de RennesFR3 papers
- Orange (France)FR3 papers
- Université Paris-SaclayFR3 papers
- Astrophysique, Instrumentation et ModélisationFR2 papers
- Bocconi UniversityIT2 papers
- Département mathématiques, informatique, sciences de la donnée et technologies du numériqueFR2 papers
23 papers · 1 filter
A uniform relative deviation inequality for VC-subgraph classes
François Portier
We establish a new Bernstein-type deviation inequality for classes of functions whose complexity is characterized through subgraphs. The inequality is non-asymptotic, involves expl…
A Kernel Two-Sample Test Invariant under Group Action with Applications to Functional Data
Madison Giacofci, Anouar Meynaoui, Alex Podgorny
We introduce a kernel-based two-sample test for comparing probability distributions up to group actions. Our construction yields invariant kernels for locally compact -compact g…
Asymmetric conformal prediction with penalized kernel sum-of-squares
Louis Allain, Sébastien Da Veiga, Brian Staber
Conformal prediction (CP) is a distribution-free method to construct reliable prediction intervals that has gained significant attention in recent years. Despite its success and va…
Adaptive Algorithms for Infinitely Many-Armed Bandits: A Unified Framework
Emmanuel Pilliat
We consider a bandit problem where the buget is smaller than the number of arms, which may be infinite. In this regime, the usual objective in the literature is to minimize simple…
On the pointwise and sup-norm errors for local regression estimators
Jérémy Bettinger, François Portier, Adrien Saumard
In this paper, we analyze the behavior of various non-parametric local regression estimators, i.e. estimators that are based on local averaging, for estimating a Lipschitz regressi…
A model-based approach to density estimation in sup-norm
Guillaume Maillard
We define a general method for finding a quasi-best approximant in sup-norm to a target density belonging to a given model, based on independent samples drawn from distributions wh…