On Efficient Optimal Transport: An Analysis of Greedy and Accelerated Mirror Descent Algorithms

Authors: Tianyi Lin, Nhat Ho, Michael Jordan

Abstract

We provide theoretical analyses for two algorithms that solve the regularized optimal transport (OT) problem between two discrete probability measures with at most $n$ atoms. We show that a greedy variant of the classical Sinkhorn algorithm, known as the

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