2013
NIPS
NeurIPS 2013
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.
🧭
Keyword Pioneer
— randomized dependence
🐝
Cross-Pollinator
— Artificial Intelligence, Deep Learning, Interdisciplinary, Machine Learning, Mathematics & Optimization
🌉
Interdisciplinary Bridge
— Machine Learning and Mathematics & Optimization
📈
Trend Setter
— Statistics