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相关论文: Stability of Entropic Optimal Transport and Schr\"…

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We study the convergence of entropically regularized optimal transport to optimal transport. The main result is concerned with the convergence of the associated optimizers and takes the form of a large deviations principle quantifying the…

最优化与控制 · 数学 2022-01-25 Espen Bernton , Promit Ghosal , Marcel Nutz

We study the stability of entropically regularized optimal transport with respect to the marginals. Given marginals converging weakly, we establish a strong convergence for the Schr\"odinger potentials describing the density of the optimal…

概率论 · 数学 2022-01-26 Marcel Nutz , Johannes Wiesel

The optimal transport problem has recently developed into a powerful framework for various applications in estimation and control. Many of the recent advances in the theory and application of optimal transport are based on regularizing the…

最优化与控制 · 数学 2021-03-12 Isabel Haasler , Axel Ringh , Yongxin Chen , Johan Karlsson

We study the stability of entropically regularized optimal transport with respect to the marginals. Lipschitz continuity of the value and H\"older continuity of the optimal coupling in $p$-Wasserstein distance are obtained under general…

最优化与控制 · 数学 2022-07-06 Stephan Eckstein , Marcel Nutz

This paper exploit the equivalence between the Schr\"odinger Bridge problem and the entropy penalized optimal transport in order to find a different approach to the duality, in the spirit of optimal transport. This approach results in a…

概率论 · 数学 2019-11-19 Simone Di Marino , Augusto Gerolin

A basic idea in optimal transport is that optimizers can be characterized through a geometric property of their support sets called cyclical monotonicity. In recent years, similar "monotonicity principles" have found applications in other…

最优化与控制 · 数学 2023-08-31 Julio Backhoff-Veraguas , Mathias Beiglböck , Giovanni Conforti

Replacing positivity constraints by an entropy barrier is popular to approximate solutions of linear programs. In the special case of the optimal transport problem, this technique dates back to the early work of Schr\"odinger. This approach…

偏微分方程分析 · 数学 2017-01-10 Guillaume Carlier , Vincent Duval , Gabriel Peyré , Bernhard Schmitzer

In this work, we develop a collection of novel methods for the entropic-regularised optimal transport problem, which are inspired by existing mirror descent interpretations of the Sinkhorn algorithm used for solving this problem. These are…

最优化与控制 · 数学 2025-07-17 Vishwak Srinivasan , Qijia Jiang

This paper introduces a dynamic formulation of divergence-regularized optimal transport with weak targets on the path space. In our formulation, the classical relative entropy penalty is replaced by a general convex divergence, and terminal…

概率论 · 数学 2026-03-31 Camilo Hernández , Ludovic Tangpi

We provide the stability of $C^{1,\alpha}$ regularity of Schr\"odinger potentials of Boltzmann-Shannon entropy regularized Optimal Transport under the classical assumption of marginals supported on bounded convex sets and whose densities…

最优化与控制 · 数学 2025-06-12 Sumiya Baasandorj , Simone Di Marino , Augusto Gerolin

The \emph{Schr\"odinger problem} is obtained by replacing the mean square distance with the relative entropy in the Monge-Kantorovich problem. It was first addressed by Schr\"odinger as the problem of describing the most likely evolution of…

概率论 · 数学 2018-06-22 Giovanni Conforti

We establish the uniform in time stability, w.r.t. the marginals, of the Iterative Proportional Fitting Procedure, also known as Sinkhorn algorithm, used to solve entropy-regularised Optimal Transport problems. Our result is quantitative…

机器学习 · 统计学 2021-10-25 George Deligiannidis , Valentin De Bortoli , Arnaud Doucet

The function that maps a family of probability measures to the solution of the dual entropic optimal transport problem is known as the Schr\"odinger map. We prove that when the cost function is $\mathcal{C}^{k+1}$ with $k\in \mathbb{N}^*$…

最优化与控制 · 数学 2024-03-04 Guillaume Carlier , Lénaïc Chizat , Maxime Laborde

We study stability of optimizers and convergence of Sinkhorn's algorithm for the entropic optimal transport problem. In the special case of the quadratic cost, our stability bounds imply that if one of the two entropic potentials is…

概率论 · 数学 2025-10-06 Alberto Chiarini , Giovanni Conforti , Giacomo Greco , Luca Tamanini

We develop a mathematical theory of entropic regularisation of unbalanced optimal transport problems. Focusing on static formulation and relying on the formalism developed for the unregularised case, we show that unbalanced optimal…

最优化与控制 · 数学 2023-05-05 Maciej Buze , Manh Hong Duong

We show continuity of the martingale optimal transport optimisation problem as a functional of its marginals. This is achieved via an estimate on the projection in the nested/causal Wasserstein distance of an arbitrary coupling on to the…

概率论 · 数学 2022-06-22 Johannes Wiesel

We study the vanishing-regularization limit of entropically regularized optimal transport (EOT) for the Euclidean distance cost $c(x,y)=\|x-y\|$ in dimension $d>1$. We develop a comprehensive variational convergence framework that entails…

最优化与控制 · 数学 2026-04-29 Marcel Nutz , Chenyang Zhong

We study Sinkhorn's algorithm for solving the entropically regularized optimal transport problem. Its iterate $\pi_{t}$ is shown to satisfy $H(\pi_{t}|\pi_{*})+H(\pi_{*}|\pi_{t})=O(t^{-1})$ where $H$ denotes relative entropy and $\pi_{*}$…

最优化与控制 · 数学 2025-04-08 Promit Ghosal , Marcel Nutz

In this paper we determine quantitative stability bounds for the Hessian of entropic potentials, \ie, the dual solution to the entropic optimal transport problem. To the authors' knowledge this is the first work addressing this second-order…

概率论 · 数学 2025-11-14 Giacomo Greco , Luca Tamanini

We consider network routing under random link failures with a desired final distribution. We provide a mathematical formulation of a relaxed transport problem where the final distribution only needs to be close to the desired one. The…

最优化与控制 · 数学 2018-01-25 Yongxin Chen , Tryphon Georgiou , Michele Pavon , Allen Tannenbaum
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