# Unbiased estimators for the variance of MMD estimators

@article{Sutherland2019UnbiasedEF, title={Unbiased estimators for the variance of MMD estimators}, author={Danica J. Sutherland}, journal={ArXiv}, year={2019}, volume={abs/1906.02104} }

The maximum mean discrepancy (MMD) is a kernel-based distance between probability distributions useful in many applications (Gretton et al. 2012), bearing a simple estimator with pleasing computational and statistical properties. Being able to efficiently estimate the variance of this estimator is very helpful to various problems in two-sample testing. Towards this end, Bounliphone et al. (2016) used the theory of U-statistics to derive estimators for the variance of an MMD estimator, and…

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## 5 Citations

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