Asymptotics of Entropy-Regularized Optimal Transport via Chaos Decomposition

• URL: http://arxiv.org/abs/2011.08963v1
• Date: Tue, 17 Nov 2020 21:55:46 GMT
• Title: Asymptotics of Entropy-Regularized Optimal Transport via Chaos Decomposition
• Authors: Zaid Harchaoui, Lang Liu, Soumik Pal
• Abstract summary: This paper is on the properties of a discrete Schr"odinger bridge as $N$ tends to infinity. We derive the first two error terms of orders $N-1/2$ and $N-1$, respectively. The kernels corresponding to the first and second order chaoses are given by Markov operators which have natural interpretations in the Sinkhorn algorithm.
• Score: 1.7188280334580195
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Consider the problem of estimating the optimal coupling (i.e., matching) between $N$ i.i.d. data points sampled from two densities $\rho_0$ and $\rho_1$ in $\mathbb{R}^d$. The cost of transport is an arbitrary continuous function that satisfies suitable growth and integrability assumptions. For both computational efficiency and smoothness, often a regularization term using entropy is added to this discrete problem. We introduce a modification of the commonly used discrete entropic regularization (Cuturi '13) such that the optimal coupling for the regularized problem can be thought of as the static Schr\"odinger bridge with $N$ particles. This paper is on the asymptotic properties of this discrete Schr\"odinger bridge as $N$ tends to infinity. We show that it converges to the continuum Schr\"odinger bridge and derive the first two error terms of orders $N^{-1/2}$ and $N^{-1}$, respectively. This gives us functional CLT, including for the cost of transport, and second order Gaussian chaos limits when the limiting Gaussian variance is zero, extending similar recent results derived for finite state spaces and the quadratic cost. The proofs are based on a novel chaos decomposition of the discrete Schr\"odinger bridge by polynomial functions of the pair of empirical distributions as a first and second order Taylor approximations in the space of measures. This is achieved by extending the Hoeffding decomposition from the classical theory of U-statistics. The kernels corresponding to the first and second order chaoses are given by Markov operators which have natural interpretations in the Sinkhorn algorithm.

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