JapanTech

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