High-Dimensional Structure Theory Team Seminar (Talk by Christophe Quentin Valvason, University of Geneva)
RIKEN AIP online seminar: optimal transport methods for building nonparametric confidence intervals that hold up in small samples.
- When
- Tue, September 29, 2026 · 16:00–17:00 JST
- Where
- Online
- Organizer
- RIKEN Center for Advanced Intelligence Project
- Language
- EN
- Source
- Doorkeeper
Summary
An online seminar hosted by the High-Dimensional Structure Theory Team at RIKEN AIP, featuring Christophe Quentin Valvason of the University of Geneva. The talk, titled "Optimal Transport for Nonparametric Inference: Improving Confidence Intervals", addresses the difficulty of reliable statistical inference in small samples, where standard confidence procedures can deviate substantially from their nominal coverage.
The speaker presents a method that recasts confidence interval construction as an optimal transport problem between a discrete source measure and an estimate of the sampling distribution. The talk covers finite-sample bounds on non-coverage probability tied to the geometry of the dual potential, asymptotic validity including consistency in the Hausdorff metric, a regularization view of why finite support stabilizes the construction, and simulation studies showing coverage closer to nominal than standard bootstrap procedures.
About the community
The High-Dimensional Structure Theory Team is a research group within a national AI research center that runs a recurring seminar series, inviting researchers from Japan and abroad to present work in mathematical statistics, machine learning theory, and high-dimensional analysis. Talks are research-level, typically about an hour, delivered online and open to the public.
#optimal-transport#statistics#nonparametric-inference#machine-learning-theory#research-seminar#riken-aip