论文标题
关于评估统计接近性的几个权衡曲线的理论等效性
On the Theoretical Equivalence of Several Trade-Off Curves Assessing Statistical Proximity
论文作者
论文摘要
强大的生成模型的最新出现触发了定量措施的新开发，以评估两个概率分布的接近性。随着标量特征的成立距离仍然很流行，几种方法探索了计算整个曲线，这揭示了第一个分布相对于第二个分布的忠诚度和可变性之间的权衡。已经独立提出了一些此类变体，虽然在直觉上相似，但尚未明确提出它们的关系。为了使生成性评估的新兴图片更加清晰，我们提出了四个曲线的统一，分别称为：Precision-Recall（PR）曲线，Lorenz曲线，接收器操作特征（ROC）曲线和RényiDivergence Frontiers的特殊情况。此外，我们讨论了PR / Lorenz曲线之间的可能联系，并与域适应边界的推导有关。
The recent advent of powerful generative models has triggered the renewed development of quantitative measures to assess the proximity of two probability distributions. As the scalar Frechet inception distance remains popular, several methods have explored computing entire curves, which reveal the trade-off between the fidelity and variability of the first distribution with respect to the second one. Several of such variants have been proposed independently and while intuitively similar, their relationship has not yet been made explicit. In an effort to make the emerging picture of generative evaluation more clear, we propose a unification of four curves known respectively as: the precision-recall (PR) curve, the Lorenz curve, the receiver operating characteristic (ROC) curve and a special case of Rényi divergence frontiers. In addition, we discuss possible links between PR / Lorenz curves with the derivation of domain adaptation bounds.
