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Urban transportation is a complex phenomenon. Since many agents are constantly interacting in parallel, it is difficult to predict the future state of a transportation system. Because of this, optimization techniques tend to give obsolete…

Adaptation and Self-Organizing Systems · Physics 2012-03-16 Carlos Gershenson

In this paper, we explore a scenario where a sender provides an information policy and a receiver, upon observing a realization of this policy, decides whether to take a particular action, such as making a purchase. The sender's objective…

Numerical Analysis · Mathematics 2024-12-13 Jorge Justiniano , Andreas Kleiner , Benny Moldovanu , Martin Rumpf , Philipp Strack

We consider the model of a transportation problem with the objective of finding a minimum-cost transportation plan for shipping a given commodity from a set of supply centers to the customers. Since the exact values of supply and demand and…

Optimization and Control · Mathematics 2023-01-31 Elif Garajová , Miroslav Rada

Optimal transport has been one of the most exciting subjects in mathematics, starting from the 18th century. As a powerful tool to transport between two probability measures, optimal transport methods have been reinvigorated nowadays in a…

Machine Learning · Statistics 2021-05-21 Jingyi Zhang , Wenxuan Zhong , Ping Ma

This article gives an introduction to optimal transport, a mathematical theory that makes it possible to measure distances between functions (or distances between more general objects), to interpolate between objects or to enforce…

Analysis of PDEs · Mathematics 2017-10-10 Bruno Levy , Erica Schwindt

The theory of optimal transportation has developed into a powerful and elegant framework for comparing probability distributions, with wide-ranging applications in all areas of science. The fundamental idea of analyzing probabilities by…

Methodology · Statistics 2025-03-14 Florian F Gunsilius

Entropic optimal transport (OT) and the Sinkhorn algorithm have made it practical for machine learning practitioners to perform the fundamental task of calculating transport distance between statistical distributions. In this work, we focus…

Optimization and Control · Mathematics 2024-03-11 Xun Tang , Holakou Rahmanian , Michael Shavlovsky , Kiran Koshy Thekumparampil , Tesi Xiao , Lexing Ying

Preference learning in Large Language Models (LLMs) has advanced significantly, yet existing methods remain limited by modest performance gains, high computational costs, hyperparameter sensitivity, and insufficient modeling of global…

Computation and Language · Computer Science 2026-04-03 Liang Zhu , Yuelin Bai , Xiankun Ren , Jiaxi Yang , Lei Zhang , Feiteng Fang , Hamid Alinejad-Rokny , Minghuan Tan , Min Yang

We consider the problem to transport resources/mass while abiding by constraints on the flow through constrictions along their path between specified terminal distributions. Constrictions, conceptualized as toll stations at specified…

Systems and Control · Electrical Eng. & Systems 2023-05-03 Anqi Dong , Arthur Stephanovitch , Tryphon T. Georgiou

We introduce an alternative approach for the analysis and numerical approximation of the optimal feedback control mapping. It consists in looking at a typical optimal control problem in such a way that feasible controls are mappings…

Optimization and Control · Mathematics 2017-06-09 Pablo Pedregal

Public transport is vital for meeting people's mobility needs. Providers need to plan their services well to offer high quality and low cost. Optimized planning can benefit providers, customers, and municipalities. The planning process for…

Optimization and Control · Mathematics 2023-10-23 Lucas Mertens , Lena-Antonia Wolbeck , David Rößler , Lin Xie , Natalia Kliewer

There is a relatively small amount of research covering urban freight movements. Most research dealing with the subject of urban mobility focuses on passenger vehicles, not commercial vehicles hauling freight. However, in many ways, urban…

Artificial Intelligence · Computer Science 2014-09-02 Amir Zidi , Amna Bouhana , Afef Fekih , Mourad Abed

A variant of the classical optimal transportation problem is: among all joint measures with fixed marginals and which are dominated by a given density, find the optimal one. Existence and uniqueness of solutions to this variant were…

Optimization and Control · Mathematics 2018-01-23 Jonathan Korman , Robert J. McCann

Many real-life optimization problems frequently contain one or more constraints or objectives for which there are no explicit formulas. If data is however available, these data can be used to learn the constraints. The benefits of this…

Machine Learning · Computer Science 2022-09-23 Adejuyigbe Fajemisin , Donato Maragno , Dick den Hertog

Transformers have achieved state-of-the-art performance in numerous tasks. In this paper, we propose a continuous-time formulation of transformers. Specifically, we consider a dynamical system whose governing equation is parametrized by…

Machine Learning · Computer Science 2025-02-03 Kelvin Kan , Xingjian Li , Stanley Osher

Optimal transport (OT) is a powerful framework to compare probability measures, a fundamental task in many statistical and machine learning problems. Substantial advances have been made in designing OT variants which are either…

Machine Learning · Computer Science 2025-02-04 Clément Bonet , Kimia Nadjahi , Thibault Séjourné , Kilian Fatras , Nicolas Courty

We propose new variational principles for traffic assignment problems. So to find equillibrium we have to solve large-scale convex optimization problem of special type. We propose some kind of "algebra" on different models and corresponding…

Optimization and Control · Mathematics 2017-02-28 Alexander Gasnikov

Optimal transport is a framework that facilitates the most efficient allocation of a limited amount of resources. However, the most efficient allocation scheme does not necessarily preserve the most fairness. In this paper, we establish a…

Optimization and Control · Mathematics 2021-04-01 Jason Hughes , Juntao Chen

Optimal transport (OT) theory describes general principles to define and select, among many possible choices, the most efficient way to map a probability measure onto another. That theory has been mostly used to estimate, given a pair of…

Machine Learning · Computer Science 2023-04-03 Charlotte Bunne , Andreas Krause , Marco Cuturi

We study a multimodal journey planning scenario consisting of a public transit network and a transfer graph which represents a secondary transportation mode (e.g., walking, cycling, e-scooter). The objective is to compute Pareto-optimal…

Data Structures and Algorithms · Computer Science 2023-02-02 Moritz Baum , Valentin Buchhold , Jonas Sauer , Dorothea Wagner , Tobias Zündorf
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