mlsanityData to 7 Oct 2026

Hilbert's projective metric for functions of bounded growth and exponential convergence of Sinkhorn's algorithm

arXiv 2311.04041 ↗First posted 7 Nov 2023math.PR math.OC stat.MLcited by 8

Not on the map. Why?

Abstract (arXiv)

Motivated by the entropic optimal transport problem in unbounded settings, we study versions of Hilbert's projective metric for spaces of integrable functions of bounded growth. These versions of Hilbert's metric originate from cones which are relaxations of the cone of all non-negative functions, in the sense that they include all functions having non-negative integral values when multiplied with certain test functions. We show that kernel integral operators are contractions with respect to suitable specifications of such metrics even for kernels which are not bounded away from zero, provided that the decay to zero of the kernel is controlled. As an application to entropic optimal transport, we show exponential convergence of Sinkhorn's algorithm in settings where the marginal distributions have sufficiently light tails compared to the growth of the cost function.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 28 of its 75 references that are in the map. First posted on arXiv 7 Nov 2023.

Builds on

28 of 75 references.

References · 28

  1. 2020Unsupervised Learning of Visual Features by Contrasting Cluster Assignmentscited by 2,845
  2. 2013Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distancescited by 2,277
  3. 2018Computational Optimal Transportcited by 765
  4. 2013Fast Computation of Wasserstein Barycenterscited by 216
  5. 2016Stochastic Optimization for Large-scale Optimal Transportcited by 188
  6. 2021OTA: Optimal Transport Assignment for Object Detectioncited by 177
  7. 2021Proximal Optimal Transport Modeling of Population Dynamicscited by 91
  8. 2021Entropic estimation of optimal transport mapscited by 87
  9. 2019Statistical bounds for entropic optimal transport: sample complexity and the central limit theoremcited by 85
  10. 2020Faster Wasserstein Distance Estimation with the Sinkhorn Divergencecited by 73
  11. 2016Stabilized Sparse Scaling Algorithms for Entropy Regularized Transport Problemscited by 69
  12. 2015Entropic and displacement interpolation: a computational approach using the Hilbert metriccited by 34
16 more
  1. 2021Entropic Optimal Transport: Convergence of Potentialscited by 30
  2. 2023Learning Gaussian Mixtures Using the Wasserstein-Fisher-Rao Gradient Flowcited by 25
  3. 2021Quantitative Stability of Regularized Optimal Transport and Convergence of Sinkhorn's Algorithmcited by 21
  4. 2021Entropic Optimal Transport: Geometry and Large Deviationscited by 20
  5. 2022An improved central limit theorem and fast convergence rates for entropic transportation costscited by 18
  6. 2022On the Convergence Rate of Sinkhorn's Algorithmcited by 16
  7. 2021Asymptotics for semi-discrete entropic optimal transportcited by 14
  8. 2022Stability of Schr"odinger Potentials and Convergence of Sinkhorn's Algorithmcited by 13
  9. 2023Quantitative contraction rates for Sinkhorn's algorithm: beyond bounded costs and compact marginalscited by 13
  10. 2021Quantitative Uniform Stability of the Iterative Proportional Fitting Procedurecited by 11
  11. 2022Convergence Rates for Regularized Optimal Transport via Quantizationcited by 11
  12. 2020Stochastic Optimization for Regularized Wasserstein Estimatorscited by 9
  13. 2022Convergence rate of general entropic optimal transport costscited by 9
  14. 2023Non-asymptotic convergence bounds for Sinkhorn iterates and their gradients: a coupling approachcited by 7
  15. 2023Estimating the Rate-Distortion Function by Wasserstein Gradient Descentcited by 5
  16. 2023Convergence rate of entropy-regularized multi-marginal optimal transport costscited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 3; 2026: 3.

8 papers.