6 papers · 1 filter
Conformalized Quantile Regression and Minimax Limits of Fixed-Score Calibration under Known Covariate Shift
Rustam Isaev, Anton Conrad, Denis Belomestny +2
In this paper, we study nonasymptotic error bounds for interval length and conditional coverage in split conformalized quantile regression (CQR). Our bounds rely on local reg…
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…
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…
Mathematical methods of reinforcement learning
Denis Belomestny, Alexander Gasnikov, Egor Gladin +5
Reinforcement learning (RL) is increasingly grounded in tools from probability, optimization, and operator theory. This survey organizes the mathematical structures that underpin t…
Your GFlowNet Secretly Learns an Optimal Transport Plan
Ian Maksimov, Nikita Morozov, Denis Belomestny +1
Generative Flow Networks (GFlowNets) are a framework for sampling structured objects via stochastic trajectories in a directed graph. In this work, we establish a theoretical conne…
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…