Uniqueness of optimal plans for multi-marginal mass transport problems via a reduction argument
Mohammad Ali Ahmadpoor, Abbas Moameni

TL;DR
This paper introduces a reduction method for multi-marginal optimal transport problems, enabling the recovery of global optimal plans from lower-dimensional problems and establishing new uniqueness results.
Contribution
The paper presents a novel reduction argument that links the uniqueness of multi-marginal optimal plans to lower-dimensional marginal problems, extending existing results and introducing new applications.
Findings
Recovery of global optimal plans from lower-dimensional marginal problems
New conditions for uniqueness of multi-marginal optimal plans
Extension of classical results including Gangbo-Święch's work
Abstract
For a family of probability spaces and a cost function we consider the Monge-Kantorovich problem \begin{align*}\tag{MK}\label{MONKANT} \inf_{\lambda\in\Pi(\mu_1,\ldots,\mu_N)}\int_{\prod_{k=1}^N X_k}c\,d\lambda. \end{align*} Then for each ordered subset with we create a new cost function corresponding to the original cost function defined on . This new cost function enjoys many of the features of the original cost while it has the property that any optimal plan of \eqref{MONKANT} restricted to is also an optimal plan to the problem \begin{align*}\tag{RMK}\label{REDMONKANT} \inf_{\tau\in\Pi(\mu_{i_1},\ldots\mu_{i_p})}\int_{\prod_{k=1}^p…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsNonlinear Partial Differential Equations
