mlsanityData to 14 Oct 2026

Relaxation of optimal transport problem via strictly convex functions

arXiv 2102.07336 ↗First posted 15 Feb 2021math.OC stat.MLcited by 1

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Abstract (arXiv)

An optimal transport problem on finite spaces is a linear program. Recently, a relaxation of the optimal transport problem via strictly convex functions, especially via the Kullback--Leibler divergence, sheds new light on data sciences. This paper provides the mathematical foundations and an iterative process based on a gradient descent for the relaxed optimal transport problem via Bregman divergences.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 3 of its 7 references that are in the map. First posted on arXiv 15 Feb 2021.

Builds on

3 of 7 references.

References · 3

  1. 2013Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distancescited by 2,316
  2. 2018Computational Optimal Transportcited by 780
  3. 2016Regularized Optimal Transport and the Rot Mover's Distancecited by 24

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Citing papers per year: 2023: 1.

1 paper.

  1. 2023Convergence rate of Tsallis entropic regularized optimal transportcited by 0