The Randomized Dependence Coefficient
Abstract
We introduce the Randomized Dependence Coefficient (RDC), a measure of non-linear dependence between random variables of arbitrary dimension based on the Hirschfeld-Gebelein-Rényi Maximum Correlation Coefficient. RDC is defined in terms of correlation of random non-linear copula projections; it is invariant with respect to marginal distribution transformations, has low computational cost and is easy to implement: just five lines of R code, included at the end of the paper.
Cite
Text
Lopez-Paz et al. "The Randomized Dependence Coefficient." Neural Information Processing Systems, 2013.Markdown
[Lopez-Paz et al. "The Randomized Dependence Coefficient." Neural Information Processing Systems, 2013.](https://mlanthology.org/neurips/2013/lopezpaz2013neurips-randomized/)BibTeX
@inproceedings{lopezpaz2013neurips-randomized,
title = {{The Randomized Dependence Coefficient}},
author = {Lopez-Paz, David and Hennig, Philipp and Schölkopf, Bernhard},
booktitle = {Neural Information Processing Systems},
year = {2013},
pages = {1-9},
url = {https://mlanthology.org/neurips/2013/lopezpaz2013neurips-randomized/}
}