mlsanityData to 14 Oct 2026

A simpler condition for consistency of a kernel independence test

arXiv 1501.06103 ↗First posted 25 Jan 2015stat.MLcited by 10

Not on the map. Why?

Abstract (arXiv)

A statistical test of independence may be constructed using the Hilbert-Schmidt Independence Criterion (HSIC) as a test statistic. The HSIC is defined as the distance between the embedding of the joint distribution, and the embedding of the product of the marginals, in a Reproducing Kernel Hilbert Space (RKHS). It has previously been shown that when the kernel used in defining the joint embedding is characteristic (that is, the embedding of the joint distribution to the feature space is injective), then the HSIC-based test is consistent. In particular, it is sufficient for the product of kernels on the individual domains to be characteristic on the joint domain. In this note, it is established via a result of Lyons (2013) that HSIC-based independence tests are consistent when kernels on the marginals are characteristic on their respective domains, even when the product of kernels is not characteristic on the joint domain.

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). First posted on arXiv 25 Jan 2015.

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Citing papers per year: 2021: 1; 2022: 3; 2023: 1; 2024: 2; 2025: 0; 2026: 3.

10 papers.