4 papers
E-Values For Multiplicity Control In Multiverse Analysis
Paul Rognon-Vael, David Rossell
Multiverse analysis refers to a common situation where one wishes to assess the association between multiple possible treatment definitions and multiple possible outcome definition…
Improving variable selection properties with data integration and transfer learning
Paul Rognon-Vael, David Rossell, Piotr Zwiernik
We study variable selection (also called support recovery) in high-dimensional sparse linear regression when one has external information on which variables are likely to be associ…
Empirical Bayes for Data Integration
Paul Rognon-Vael, David Rossell
We discuss the use of empirical Bayes for data integration, in the sense of transfer learning. Our main interest is in settings where one wishes to learn structure (e.g. feature se…
Sparse Nonparametric Contextual Bandits
Hamish Flynn, Julia Olkhovskaya, Paul Rognon-Vael
We study the benefits of sparsity in nonparametric contextual bandit problems, in which the set of candidate features is countably or uncountably infinite. Our contribution is two-…