Litcius/Paper detail

An entropic generalization of Caffarelli’s contraction theorem via covariance inequalities

Sinho Chewi, Aram-Alexandre Pooladian

2023Comptes Rendus Mathématique21 citationsDOIOpen Access PDF

Abstract

The optimal transport map between the standard Gaussian measure and an <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>α</mml:mi> </mml:math> -strongly log-concave probability measure is <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mi>α</mml:mi> <mml:mrow> <mml:mo>-</mml:mo> <mml:mn>1</mml:mn> <mml:mo>/</mml:mo> <mml:mn>2</mml:mn> </mml:mrow> </mml:msup> </mml:math> -Lipschitz, as first observed in a celebrated theorem of Caffarelli. In this paper, we apply two classical covariance inequalities (the Brascamp–Lieb and Cramér–Rao inequalities) to prove a sharp bound on the Lipschitz constant of the map that arises from entropically regularized optimal transport. In the limit as the regularization tends to zero, we obtain an elegant and short proof of Caffarelli’s original result. We also extend Caffarelli’s theorem to the setting in which the Hessians of the log-densities of the measures are bounded by arbitrary positive definite commuting matrices.

Topics & Concepts

MathematicsLipschitz continuityGaussian measureProbability measureConcentration of measureCovarianceBounded functionGaussianMeasure (data warehouse)Regularization (linguistics)Pure mathematicsMathematical analysisApplied mathematicsCombinatoricsStatisticsQuantum mechanicsDatabaseArtificial intelligencePhysicsComputer scienceGeometric Analysis and Curvature FlowsMarkov Chains and Monte Carlo MethodsAnalytic and geometric function theory
An entropic generalization of Caffarelli’s contraction theorem via covariance inequalities | Litcius