Optimal Transport (OT) is a mathematical framework that first emerged in the eighteenth
century and has led to a plethora of methods for answering many theoretical and applied …

We compute exact second-order asymptotics for the cost of an optimal solution to the
entropic optimal transport problem in the continuous-to-discrete, or semidiscrete, setting. In …

We present several new complexity results for the entropic regularized algorithms that
approximately solve the optimal transport (OT) problem between two discrete probability …

We study the Unbalanced Optimal Transport (UOT) between two measures of possibly
different masses with at most n components, where the marginal constraints of standard …

In this study, we consider the application of the Hungarian algorithm for allocating positions
in robotic formations. Two modifications of the Hungarian algorithm are compared. The time …

We provide faster algorithms for approximating the optimal transport distance, eg earth
mover's distance, between two discrete probability distributions on n elements. We present …

We consider the population Wasserstein barycenter problem for random probability
measures supported on a finite set of points and generated by an online stream of data. This …

The recently introduced Genetic Column Generation (GenCol) algorithm has been
numerically observed to efficiently and accurately compute high-dimensional optimal …

Identifying optimal basic feasible solutions to linear programming problems is a critical task
for mixed integer programming and other applications. The crossover method, which aims at …

Capacity constrained optimal transport is a variant of optimal transport, which adds extra
constraints on the set of feasible couplings in the original optimal transport problem to limit …