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We derive strong variance-based uncertainty relations for arbitrary two and more unitary operators by re-examining the mathematical foundation of the uncertainty relation. This is achieved by strengthening the celebrated Cauchy-Schwarz…

Quantum Physics · Physics 2022-01-25 Xiaoli Hu , Naihuan Jing

The stability of solutions to optimal transport problems under variation of the measures is fundamental from a mathematical viewpoint: it is closely related to the convergence of numerical approaches to solve optimal transport problems and…

Numerical Analysis · Mathematics 2022-07-25 Anatole Gallouët , Quentin Mérigot , Boris Thibert

In this paper a new class of modified-Hessian equations, closely related to the Optimal Transportation Equation, will be introduced and studied. In particular, the existence of globally smooth, classical solutions of these equations…

Analysis of PDEs · Mathematics 2013-01-31 Greg T. von Nessi

We study estimators of the optimal transport (OT) map between two probability distributions. We focus on plugin estimators derived from the OT map between estimates of the underlying distributions. We develop novel stability bounds for OT…

Statistics Theory · Mathematics 2025-02-19 Sivaraman Balakrishnan , Tudor Manole

Whilst optimal transport (OT) is increasingly being recognized as a powerful and flexible approach for dealing with fairness issues, current OT fairness methods are confined to the use of discrete OT. In this paper, we leverage recent…

Machine Learning · Computer Science 2021-01-07 Silvia Chiappa , Aldo Pacchiano

This work studies the distributionally robust evaluation of expected values over temporal data. A set of alternative measures is characterized by the causal optimal transport. We prove the strong duality and recast the causality constraint…

Mathematical Finance · Quantitative Finance 2025-06-18 Bingyan Han

We express each Fr\'echet class of multivariate Bernoulli distributions with given margins as the convex hull of a set of densities, which belong to the same Fr\'echet class. This characterisation allows us to establish whether a given…

Statistics Theory · Mathematics 2017-06-06 Roberto Fontana , Patrizia Semeraro

We analyze optimal transport problems with additional entropic cost evaluated along curves in the Wasserstein space which join two probability measures $m_0,m_1$. The effect of the additional entropy functional results into an elliptic…

Analysis of PDEs · Mathematics 2022-11-18 Alessio Porretta

This article connects the theory of extremal doubly stochastic measures to the geometry and topology of optimal transportation. We begin by reviewing an old question (# 111) of Birkhoff in probability and statistics [4], which is to give a…

Probability · Mathematics 2010-04-26 Najma Ahmad , Hwa Kil Kim , Robert J. McCann

Estimating parameters from samples of an optimal probability distribution is essential in applications ranging from socio-economic modeling to biological system analysis. In these settings, the probability distribution arises as the…

Machine Learning · Computer Science 2025-08-19 Francisco Andrade , Gabriel Peyré , Clarice Poon

By using optimal mass transport theory we prove a sharp isoperimetric inequality in ${\sf CD} (0,N)$ metric measure spaces assuming an asymptotic volume growth at infinity. Our result extends recently proven isoperimetric inequalities for…

Differential Geometry · Mathematics 2022-02-22 Zoltán M. Balogh , Alexandru Kristály

This work is devoted to direct mass transportation proofs of families of functional inequalities in the context of one-dimensional free probability, avoiding random matrix approximation. The inequalities include the free form of the…

Functional Analysis · Mathematics 2009-03-24 Michel Ledoux , Ionel Popescu

The fundamental theorem of classical optimal transport establishes strong duality and characterizes optimizers through a complementary slackness condition. Milestones such as Brenier's theorem and the Kantorovich-Rubinstein formula are…

Probability · Mathematics 2025-01-28 Mathias Beiglböck , Gudmund Pammer , Lorenz Riess , Stefan Schrott

We study optimal transport-based distributionally robust optimization problems where a fictitious adversary, often envisioned as nature, can choose the distribution of the uncertain problem parameters by reshaping a prescribed reference…

Optimization and Control · Mathematics 2025-10-16 Soroosh Shafiee , Liviu Aolaritei , Florian Dörfler , Daniel Kuhn

Portfolio selection problems that optimize expected utility are usually difficult to solve. If the number of assets in the portfolio is large, such expected utility maximization problems become even harder to solve numerically. Therefore,…

Portfolio Management · Quantitative Finance 2026-02-17 Nuerxiati Abudurexiti , Erhan Bayraktar , Takaki Hayashi , Hasanjan Sayit

Given two probability measures on sequential data, we investigate the transport problem with time-inconsistent preferences in a discrete-time setting. Motivating examples are nonlinear objectives, state-dependent costs, and regularized…

Optimization and Control · Mathematics 2025-06-23 Erhan Bayraktar , Bingyan Han

This paper connects discrete optimal transport to a certain class of multi-objective optimization problems. In both settings, the decision variables can be organized into a matrix. In the multi-objective problem, the notion of Pareto…

Optimization and Control · Mathematics 2017-12-04 Johannes M. Schumacher

We show that a class of Poincar\'e-Wirtinger inequalities on bounded convex sets can be obtained by means of the dynamical formulation of Optimal Transport. This is a consequence of a more general result valid for convex sets, possibly…

Analysis of PDEs · Mathematics 2016-01-05 Lorenzo Brasco , Filippo Santambrogio

This paper considers two types of boundary control problems for linear transport equations. The first one shows that transport solutions on a subdomain of a domain X can be controlled exactly from incoming boundary conditions for X under…

Analysis of PDEs · Mathematics 2021-04-19 Guillaume Bal , Alexandre Jollivet

This article focuses on a class of distributionally robust optimization (DRO) problems where, unlike the growing body of the literature, the objective function is potentially nonlinear in the distribution. Existing methods to optimize…

Machine Learning · Statistics 2024-11-07 Mohammed Rayyan Sheriff , Peyman Mohajerin Esfahani
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