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arXiv 2002.01189math.OC
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从最优输运到离散运输

From Optimal Transport to Discrepancy

Sebastian Neumayer, Gabriele Steidl

摘要:

量化测量之间的距离的常用方法是通过它们的差异,也称为最大平均差异(MMD)。离散性与Sinkhorn发散$S_\varepsilon$相关,具有适当的费用函数$\varepsilon \to \infty$。在相反的方向上,如果$\varepsilon \to 0$,Sinkhorn分歧接近另一个重要的测量之间的距离,即Wasserstein距离或更一般的最优输运,距离。在这一章中,我们研究了紧集上任意测度的极限过程和Lipschitz连续费用函数。特别是,我们感兴趣的行为相应的最佳电位$\hat φ_\varepsilon$,$\hat ψ_\varepsilon$和$\hat φ_K$出现在双制定的辛霍恩分歧和差异,分别。虽然部分结果是已知的,我们提供了严格的证明,我们还没有发现在这种一般性的文献中的一些关系。最后,我们证明了限制过程的数值例子,并显示的行为的距离时,用于近似的措施点措施的过程中称为抖动。

英文摘要:

A common way to quantify the ,,distance'' between measures is via their discrepancy, also known as maximum mean discrepancy (MMD). Discrepancies are related to Sinkhorn divergences $S_\varepsilon$ with appropriate cost functions as $\varepsilon \to \infty$. In the opposite direction, if $\varepsilon \to 0$, Sinkhorn divergences approach another important distance between measures, namely the Wasserstein distance or more generally optimal transport ,,distance''. In this chapter, we investigate the limiting process for arbitrary measures on compact sets and Lipschitz continuous cost functions. In particular, we are interested in the behavior of the corresponding optimal potentials $\hat φ_\varepsilon$, $\hat ψ_\varepsilon$ and $\hat φ_K$ appearing in the dual formulation of the Sinkhorn divergences and discrepancies, respectively. While part of the results are known, we provide rigorous proofs for some relations which we have not found in this generality in the literature. Finally, we demonstrate the limiting process by numerical examples and show the behavior of the distances when used for the approximation of measures by point measures in a process called dithering.

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