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Under the prevalent potential outcome model in causal inference, each unit is associated with multiple potential outcomes but at most one of which is observed, leading to many causal quantities being only partially identified. The inherent…

Methodology · Statistics 2024-09-16 Zijun Gao , Shu Ge , Jian Qian

Suppose that $c(x,y)$ is the cost of transporting a unit of mass from $x\in X$ to $y\in Y$ and suppose that a mass distribution $\mu$ on $X$ is transported optimally (so that the total cost of transportation is minimal) to the mass…

Functional Analysis · Mathematics 2014-05-20 Sedi Bartz , Simeon Reich

This paper deals with the existence of optimal transport maps for some optimal transport problems with a convex but non strictly convex cost. We give a decomposition strategy to address this issue. As part of our strategy, we have to treat…

Classical Analysis and ODEs · Mathematics 2009-09-16 Guillaume Carlier , Luigi De Pascale , Filippo Santambrogio

It is shown that optimal network plans can be obtained, naturally, as a limit of easier problems of point allocations. These problems are obtained by minimizing the mass transportation on the set of atomic measures of prescribed number of…

Optimization and Control · Mathematics 2009-10-15 Gershon Wolansky

In this paper we investigate the impact of path additions to transport networks with optimised traffic routing. In particular, we study the behaviour of total travel time, and consider both self-interested routing paradigms, such as User…

Multiagent Systems · Computer Science 2022-07-12 Matteo Bettini , Amanda Prorok

The duality theory of the Monge--Kantorovich transport problem is analyzed in a general setting. The spaces $X, Y$ are assumed to be polish and equipped with Borel probability measures $\mu$ and $\nu$. The transport cost function $c:X\times…

Optimization and Control · Mathematics 2010-09-07 Mathias Beiglboeck , Christian Leonard , Walter Schachermayer

We investigate the small regularization limit of entropic optimal transport when the cost function is the Euclidean distance in dimensions $d > 1$, and the marginal measures are absolutely continuous with respect to the Lebesgue measure.…

Probability · Mathematics 2025-08-15 Shrey Aryan , Promit Ghosal

We develop a general condition on the cost function which is sufficient to imply Monge solution and uniqueness results in the multi-marginal optimal transport problem. This result unifies and generalizes several results in the rather…

Analysis of PDEs · Mathematics 2013-07-25 Young-Heon Kim , Brendan Pass

This paper focuses on martingale optimal transport problems when the martingales are assumed to have bounded quadratic variation. First, we give a result that characterizes the existence of a probability measure satisfying some convex…

Probability · Mathematics 2020-03-18 Erhan Bayraktar , Xin Zhang , Zhou Zhou

We study a multi-marginal optimal transport problem with surplus $b(x_{1}, \ldots, x_{m})=\sum_{\{i,j\}\in P} x_{i}\cdot x_{j}$, where $P\subseteq Q:=\{\{i,j\}: i, j \in \{1,2,...m\}, i \neq j\}$. We reformulate this problem by associating…

Optimization and Control · Mathematics 2021-11-10 Brendan Pass , Adolfo Vargas-Jiménez

In this note, we extend the regularity theory for monotone measure-preserving maps, also known as optimal transports for the quadratic cost optimal transport problem, to the case when the support of the target measure is an arbitrary convex…

Analysis of PDEs · Mathematics 2023-05-17 Alessio Figalli , Yash Jhaveri

We investigate the minimum cost of a wide class of combinatorial optimization problems over random bipartite geometric graphs in $\mathbb{R}^d$ where the edge cost between two points is given by a $p$-th power of their Euclidean distance.…

Probability · Mathematics 2023-07-20 Michael Goldman , Dario Trevisan

Discrete optimal transportation problems arise in various contexts in engineering, the sciences and the social sciences. Often the underlying cost criterion is unknown, or only partly known, and the observed optimal solutions are corrupted…

Optimization and Control · Mathematics 2019-05-13 Andrew M. Stuart , Marie-Therese Wolfram

The main result of this paper is the existence of an optimal transport map $T$ between two given measures $\mu$ and $\nu$, for a cost which considers the maximal oscillation of $T$ at scale $\delta$, given by…

Optimization and Control · Mathematics 2021-04-14 Didier Lesesvre , Paul Pegon , Filippo Santambrogio

We consider the optimal transport problem over convex costs arising from optimal control of linear time-invariant(LTI) systems when the initial and target measures are assumed to be supported on the set of equilibrium points of the LTI…

Optimization and Control · Mathematics 2023-12-19 Karthik Elamvazhuthi , Matt Jacobs

We study network design with a cost structure motivated by redundancy in data traffic. We are given a graph, g groups of terminals, and a universe of data packets. Each group of terminals desires a subset of the packets from its respective…

Data Structures and Algorithms · Computer Science 2013-07-31 Siddharth Barman , Shuchi Chawla , Seeun Umboh

We determine the optimal structure of couplings for the \emph{Martingale transport problem} between radially symmetric initial and terminal laws $\mu, \nu$ on $\R^d$ and show the uniqueness of optimizer. Here optimality means that such…

Optimization and Control · Mathematics 2019-07-25 Tongseok Lim

We consider the Minimum Multi-Commodity Flow Subgraph (MMCFS) problem: given a directed graph $G$ with edge capacities $\mathit{cap}$ and a retention ratio $\alpha\in(0,1)$, find an edge-wise minimum subgraph $G' \subseteq G$ such that for…

Data Structures and Algorithms · Computer Science 2025-09-17 Markus Chimani , Max Ilsen

We establish novel quantitative stability results for optimal transport problems with respect to perturbations in the target measure. We provide explicit bounds on the stability of optimal transport potentials and maps, which are relevant…

Functional Analysis · Mathematics 2026-05-12 Octave Mischler , Dario Trevisan

We introduce a novel neural network-based algorithm to compute optimal transport (OT) plans for general cost functionals. In contrast to common Euclidean costs, i.e., $\ell^1$ or $\ell^2$, such functionals provide more flexibility and allow…

Machine Learning · Computer Science 2024-05-31 Arip Asadulaev , Alexander Korotin , Vage Egiazarian , Petr Mokrov , Evgeny Burnaev