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We prove the long standing conjecture in the theory of two-point boundary value problems that completeness and Dunford's spectrality imply Birkhoff regularity. In addition we establish the even order part of S.G.Krein's conjecture that…

Spectral Theory · Mathematics 2010-01-03 Arkadi Minkin

We develop a new theory for treating boundary problems for linear ordinary differential equations whose fundamental system may have a singularity at one of the two endpoints of the given interval. Our treatment follows an algebraic…

Classical Analysis and ODEs · Mathematics 2015-05-11 M. Rosenkranz , J. Liu , A. Maletzky , B. Buchberger

This work presents a universal accelerated first-order primal-dual method for affinely constrained convex optimization problems. It can handle both Lipschitz and H\"{o}lder gradients but does not need to know the smoothness level of the…

Optimization and Control · Mathematics 2022-11-09 Hao Luo

Our first result is a statement of a somewhat general form of a non-substitution theorem for linear programming problems, along with a very easy proof of the same. Subsequently, we provide an easy proof of theorem 1 in a 1979 paper of Olvi…

Optimization and Control · Mathematics 2025-04-08 Somdeb Lahiri

A system in a Birkhoff normal form with an irregular singularity of Poincare rank 1 at the origin and a regular singularity at infinity is through the Borel-Laplace transform dual to a system in an Okubo form. Schafke has showed that the…

Classical Analysis and ODEs · Mathematics 2015-11-04 Martin Klimes

The Birkhoff's theorem states that any doubly stochastic matrix lies inside a convex polytope with the permutation matrices at the corners. It can be proven that a similar theorem holds for unitary matrices with equal line sums for prime…

Mathematical Physics · Physics 2016-06-16 Alexis De Vos , Stijn De Baerdemacker

We present a method to extract temporal hypergraphs from sequences of 2-dimensional functions obtained as solutions to Optimal Transport problems. We investigate optimality principles exhibited by these solutions from the point of view of…

Discrete Mathematics · Computer Science 2023-01-10 Diego Baptista , Caterina De Bacco

We introduce the proximal optimal transport divergence, a novel discrepancy measure that interpolates between information divergences and optimal transport distances via an infimal convolution formulation. This divergence provides a…

Optimization and Control · Mathematics 2025-08-11 Ricardo Baptista , Panagiota Birmpa , Markos A. Katsoulakis , Luc Rey-Bellet , Benjamin J. Zhang

We propose an implicit neural formulation of optimal transport that eliminates adversarial min--max optimization and multi-network architectures commonly used in existing approaches. Our key idea is to parameterize a single potential in the…

Optimization and Control · Mathematics 2026-05-12 Yesom Park , Eric Gelphman , Stanley Osher , Samy Wu Fung

Continuously extending combinatorial optimization objectives is a powerful technique commonly applied to the optimization of set functions. However, few such methods exist for extending functions on permutations, despite the fact that many…

Data Structures and Algorithms · Computer Science 2025-11-13 Robert R. Nerem , Zhishang Luo , Akbar Rafiey , Yusu Wang

Efficient computation of the optimal transport distance between two distributions serves as an algorithm subroutine that empowers various applications. This paper develops a scalable first-order optimization-based method that computes…

Machine Learning · Computer Science 2024-06-21 Gen Li , Yanxi Chen , Yu Huang , Yuejie Chi , H. Vincent Poor , Yuxin Chen

In many applications, one is interested in classifying trajectories of Hamiltonian systems as invariant tori, islands, or chaos. The convergence rate of ergodic Birkhoff averages can be used to categorize these regions, but many iterations…

Dynamical Systems · Mathematics 2024-03-29 Maximilian Ruth , David Bindel

In this paper, the problem of finding optimal success probabilities of static linear optics quantum gates is linked to the theory of convex optimization. It is shown that by exploiting this link, upper bounds for the success probability of…

Quantum Physics · Physics 2009-11-10 J. Eisert

Inverse optimal transport (OT) refers to the problem of learning the cost function for OT from observed transport plan or its samples. In this paper, we derive an unconstrained convex optimization formulation of the inverse OT problem,…

Machine Learning · Computer Science 2021-07-06 Shaojun Ma , Haodong Sun , Xiaojing Ye , Hongyuan Zha , Haomin Zhou

In this work we propose a batch version of the Greenkhorn algorithm for multimarginal regularized optimal transport problems. Our framework is general enough to cover, as particular cases, some existing algorithms like Sinkhorn and…

Machine Learning · Statistics 2021-12-07 Vladimir Kostic , Saverio Salzo , Massimilano Pontil

Many problems in machine learning involve calculating correspondences between sets of objects, such as point clouds or images. Discrete optimal transport provides a natural and successful approach to such tasks whenever the two sets of…

Machine Learning · Statistics 2019-02-28 David Alvarez-Melis , Stefanie Jegelka , Tommi S. Jaakkola

The Birkhoff Ergodic Theorem asserts under mild conditions that Birkhoff averages (i.e. time averages computed along a trajectory) converge to the space average. For sufficiently smooth systems, our small modification of numerical Birkhoff…

The paper considers existence results of solution for a linear coupled system of Boltzmann transport equations and related inverse problem. The system models the evolution of three species of particles, photons, electrons and positrons.…

Analysis of PDEs · Mathematics 2019-12-02 Jouko Tervo

We develop a numerical method for the martingale analogue of the Benamou--Brenier optimal transport problem, which seeks a martingale interpolating two prescribed marginals which is closest to the Brownian motion. Recent contributions have…

Computational Finance · Quantitative Finance 2026-03-10 Manuel Hasenbichler , Benjamin Joseph , Gregoire Loeper , Jan Obloj , Gudmund Pammer

We give a universal formula describing derivation operators on a Hilbert space for a large class of interpolation methods. It is based on a simple new technique on ``critical points" where all the derivations attain the maximum. We deduce…

Functional Analysis · Mathematics 2023-12-01 Jesús Suárez