Sparsity of Quadratically Regularized Optimal Transport: Scalar Case

Abstract

The quadratically regularized optimal transport problem is empirically known to have sparse solutions: its optimal coupling $π_{\varepsilon}$ has sparse support for small regularization parameter $\varepsilon$, in contrast to entropic regularization whose solutions have full support for any $\varepsilon>0$. Focusing on continuous and scalar marginals, we provide the first precise description of this sparsity. Namely, we show that the support of $π_{\varepsilon}$ shrinks to the Monge graph at the sharp rate $\varepsilon^{1/3}$. This result is based on a detailed analysis of the dual potential $f_{\varepsilon}$ for small $\varepsilon$. In particular, we prove that $f_{\varepsilon}$ is twice differentiable a.s. and bound the second derivative uniformly in $\varepsilon$, showing that $f_{\varepsilon}$ is uniformly strongly convex. Convergence rates for $f_{\varepsilon}$ and its derivative are also obtained.

Theorems & Definitions (26)

• Theorem 2.2: Regularity
• Remark 2.3: Necessity of \ref{['as:main']}
• Remark 2.4: Multivariate case
• Theorem 2.5: Sparsity
• Theorem 2.6: Convergence
• Corollary 2.7
• Remark 2.8
• Remark 2.9
• Lemma 3.1
• proof