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Hessian stability and convergence rates for entropic and Sinkhorn potentials via semiconcavity

Published: April 15, 2025 | arXiv ID: 2504.11133v1

By: Giacomo Greco, Luca Tamanini

Potential Business Impact:

Makes computer learning faster and more accurate.

Business Areas:
Sustainability Sustainability

In this paper we determine quantitative stability bounds for the Hessian of entropic potentials, i.e., the dual solution to the entropic optimal transport problem. Up to authors' knowledge this is the first work addressing this second-order quantitative stability estimate in general unbounded settings. Our proof strategy relies on semiconcavity properties of entropic potentials and on the representation of entropic transport plans as laws of forward and backward diffusion processes, known as Schr\"odinger bridges. Moreover, our approach allows to deduce a stochastic proof of quantitative stability entropic estimates and integrated gradient estimates as well. Finally, as a direct consequence of these stability bounds, we deduce exponential convergence rates for gradient and Hessian of Sinkhorn iterates along Sinkhorn's algorithm, a problem that was still open in unbounded settings. Our rates have a polynomial dependence on the regularization parameter.

Page Count
30 pages

Category
Mathematics:
Probability