Showing 2026 · stat.MLShow all
3 papers · 2 filters
stat.ML2026
Uniform Statistical Convergence of Empirical Sinkhorn Potentials with Exponential and Polynomial Dependence on the Regularization Parameter
Denis Belomestny
We study the empirical Sinkhorn estimator of the entropic optimal transport potentials under the uniform loss. Since the potentials are only unique up to additive constants, we mea…
stat.ML2026
Beyond Marginal Validity: Finite-Sample Guarantees for Localized Conformal Prediction
Anton Conrad, Rustam Isaev, Denis Belomestny +2
Conformal prediction endows arbitrary black-box predictors with finite-sample, distribution-free marginal coverage, yet marginal validity can hide severe covariate-specific miscali…
stat.ML2026
Schrödinger bridge problem via empirical risk minimization
Denis Belomestny, Alexey Naumov, Nikita Puchkin +1
We study the Schrödinger bridge problem when the endpoint distributions are available only through samples. Classical computational approaches estimate Schrödinger potentials via S…