标题： 学习独立获得的数据之间的关系 显示英文标题

标题： Learning relationships between data obtained independently

摘要： 本文的目的是提供一种新的方法来学习独立获得的数据之间的关系。与现有方法（如匹配）不同，所提出的技术不需要任何上下文信息，前提是感兴趣的变量之间的依赖关系是单调的。因此，它可以很容易地与匹配结合以利用两种方法的优势。该技术可以被描述为分位数匹配和反褶积的混合。我们为其提供了理论验证和经验验证。 显示英文摘要

摘要： The aim of this paper is to provide a new method for learning the relationships between data that have been obtained independently. Unlike existing methods like matching, the proposed technique does not require any contextual information, provided that the dependency between the variables of interest is monotone. It can therefore be easily combined with matching in order to exploit the advantages of both methods. This technique can be described as a mix between quantile matching, and deconvolution. We provide for it a theoretical and an empirical validation.