Apr 24, 2021 · Abstract:This paper concerns the convergence of empirical measures in high dimensions. We propose a new class of probability metrics and ...

This paper concerns the convergence of empirical measures in high dimensions. We propose a new class of probability metrics and show that under such metrics ...

Sep 16, 2023 · Abstract. This paper concerns the convergence of empirical measures in high dimensions. We propose a new class of probability metrics and ...

Jun 1, 2024 · This paper concerns the convergence of empirical measures in high dimensions. We propose a new class of metrics and show that under such ...

We prove the convergence for the proposed algorithm. Using the generalized maximum mean discrepancy (GMMD) metric proposed in [25] , the difference between ...

A class of dimension-free metrics for the convergence of empirical measures ... dimensionality (CoD) by using a class of integral probability metrics ...

This paper concerns the convergence of empirical measures in high dimensions. We propose a new class of metrics and show that under such metrics, ...

May 23, 2022 · Abstract: In this talk, we first propose a new class of metrics ... dimensions is free of the curse of dimensionality, in contrast to Wasserstein ...

A class of dimension-free metrics for the convergence of empirical measures ... Weed, Sharp asymptotic and finite-sample rates of convergence of empirical ...

Sep 13, 2021 · Abstract: In this talk, we first propose a new class of metrics ... dimensions is free of the curse of dimensionality, in contrast to Wasserstein ...