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In general, standard necessary optimality conditions cannot be formulated in a straightforward manner for semi-smooth shape optimization problems. In this paper, we consider shape optimization problems constrained by variational…

Optimization and Control · Mathematics 2020-12-17 Daniel Luft , Volker H. Schulz , Kathrin Welker

We study the optimal transport problem on globally hyperbolic spacetimes associated with Orlicz-type Lorentzian cost functions of the form $u \circ \ell$, where $u$ is a suitable monotonically increasing and concave function, and $\ell$ is…

Differential Geometry · Mathematics 2026-05-14 Argam Ohanyan , Marta Sálamo Candal

The goal of this paper is to settle the study of non-commutative optimal transport problems with convex regularization, in their static and finite-dimensional formulations. We consider both the balanced and unbalanced problem and show in…

Mathematical Physics · Physics 2025-06-27 Emanuele Caputo , Augusto Gerolin , Nataliia Monina , Lorenzo Portinale

We propose a new general framework for recovering low-rank structure in optimal transport using Schatten-$p$ norm regularization. Our approach extends existing methods that promote sparse and interpretable transport maps or plans, while…

Machine Learning · Statistics 2025-10-15 Tyler Maunu

We consider the problem of optimal location of a Dirichlet region in a $d$-dimensional domain $\Omega$ subjected to a given right-hand side $f$ in order to minimize some given functional of the configuration. While in the literature the…

Optimization and Control · Mathematics 2013-04-17 Giuseppe Buttazzo , Al-hassem Nayam

Statistical inference based on optimal transport offers a different perspective from that of maximum likelihood, and has increasingly gained attention in recent years. In this paper, we study univariate nonparametric shape-constrained…

Statistics Theory · Mathematics 2026-04-13 Takeru Matsuda , Ting-Kam Leonard Wong

Motivated by the Swampland Distance Conjecture, we study distances in field space using the framework of Optimal Transport. The associated optimisation problem naturally leads to a notion of distance in terms of a (generalised) Wasserstein…

High Energy Physics - Theory · Physics 2026-04-29 Saskia Demulder , Dieter Lust , Carmine Montella , Thomas Raml

In this short note, we show that given a cost function $c$, any coupling $\pi$ of two probability measures where the second is a discrete measure can be associated to a certain bipartite graph containing a perfect matching, based on the…

Optimization and Control · Mathematics 2020-07-17 Mohit Bansil , Jun Kitagawa

This thesis deals with shape optimization for contact mechanics. More specifically, the linear elasticity model is considered under the small deformations hypothesis, and the elastic body is assumed to be in contact (sliding or with Tresca…

Optimization and Control · Mathematics 2022-08-30 Bastien Chaudet-Dumas

We consider a quasi-variational inequality governed by a moving set. We employ the assumption that the movement of the set has a small Lipschitz constant. Under this requirement, we show that the quasi-variational inequality has a unique…

Optimization and Control · Mathematics 2019-09-09 Gerd Wachsmuth

We generalize the shape optimization problem for the existence of stable equilibrium configurations of nematic and cholesteric liquid crystal drops surrounded by an isotropic solution to include a broader family of admissible domains with…

Analysis of PDEs · Mathematics 2024-08-29 Alessandro Giacomini , Silvia Paparini

In this paper, we describe the structure of shape derivatives around sets which are only assumed to be of finite perimeter in $\R^N$. This structure allows us to define a useful notion of positivity of the shape derivative and we show it…

Optimization and Control · Mathematics 2007-05-23 Jimmy Lamboley , Michel Pierre

Making sense of Wasserstein distances between discrete measures in high-dimensional settings remains a challenge. Recent work has advocated a two-step approach to improve robustness and facilitate the computation of optimal transport, using…

Machine Learning · Computer Science 2019-09-04 François-Pierre Paty , Marco Cuturi

Topology optimization is concerned with the identification of optimal shapes of deformable bodies with respect to given target functionals. The focus of this paper is on a topology optimization problem for a time-evolving elastoplastic…

Analysis of PDEs · Mathematics 2021-06-21 Stefano Almi , Ulisse Stefanelli

We present first a brief review of the existing literature on shape optimization, stressing the recent use of Hamiltonian systems in topology optimization. In the second section, we collect some preliminaries on the implicit parametrization…

Optimization and Control · Mathematics 2022-11-23 Cornel Marius Murea , Dan Tiba

Cross-domain alignment between image objects and text sequences is key to many visual-language tasks, and it poses a fundamental challenge to both computer vision and natural language processing. This paper investigates a novel approach for…

Computer Vision and Pattern Recognition · Computer Science 2020-08-18 Siyang Yuan , Ke Bai , Liqun Chen , Yizhe Zhang , Chenyang Tao , Chunyuan Li , Guoyin Wang , Ricardo Henao , Lawrence Carin

The optimal transport (OT) problem is a classical optimization problem having the form of linear programming. Machine learning applications put forward new computational challenges in its solution. In particular, the OT problem defines a…

Optimization and Control · Mathematics 2022-10-25 Nazarii Tupitsa , Pavel Dvurechensky , Darina Dvinskikh , Alexander Gasnikov

We study stability and sample complexity properties of divergence regularized optimal transport (DOT). First, we obtain quantitative stability results for optimizers of DOT measured in Wasserstein distance, which are applicable to a wide…

Optimization and Control · Mathematics 2024-01-17 Erhan Bayraktar , Stephan Eckstein , Xin Zhang

Minimizing the so-called "Dirichlet energy" with respect to the domain under a volume constraint is a standard problem in shape optimization which is now well understood. This article is devoted to a prototypal non-linear version of the…

Optimization and Control · Mathematics 2020-05-19 Antoine Henrot , Idriss Mazari , Yannick Privat

Optimization problems arising in data science have given rise to a number of new derivative-based optimization methods. Such methods often use standard smoothness assumptions -- namely, global Lipschitz continuity of the gradient function…

Optimization and Control · Mathematics 2024-04-16 Christian Varner , Vivak Patel