Discussion of `Multiscale Fisher’s Independence Test for Multivariate Dependence’
Schrab, Antonin;
Jitkrittum, Wittawat;
Szabó, Zoltán;
Sejdinovic, Dino;
Gretton, Arthur;
(2022)
Discussion of `Multiscale Fisher’s Independence Test for Multivariate Dependence’.
arXiv
![[thumbnail of 2206.11142v1.pdf]](https://discovery.ucl.ac.uk/style/images/fileicons/text.png) |
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Abstract
We discuss how MultiFIT, the Multiscale Fisher’s Independence Test for
Multivariate Dependence proposed by Gorsky and Ma (2022), compares to existing
linear-time kernel tests based on the Hilbert-Schmidt independence criterion
(HSIC). We highlight the fact that the levels of the kernel tests at any finite
sample size can be controlled exactly, as it is the case with the level of
MultiFIT. In our experiments, we observe some of the performance limitations of
MultiFIT in terms of test power.
| Type: | Article |
|---|---|
| Title: | Discussion of `Multiscale Fisher’s Independence Test for Multivariate Dependence’ |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.48550/arXiv.2206.11142 |
| Publisher version: | https://doi.org/10.48550/arXiv.2206.11142 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Methodology (stat.ME); Machine Learning (cs.LG); Applications (stat.AP); Computation (stat.CO); Machine Learning (stat.ML) |
| UCL classification: | UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science UCL > Provost and Vice Provost Offices > UCL BEAMS UCL |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10151077 |
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