CO2 reduces coreset selection for any smooth divergence to MMD minimization and proves that Sinkhorn divergence coresets of size m=ω(log^d n) match the error of the full empirical measure.
Data-driven regularization of wasserstein barycenters with an application to multivariate density registration, 2019
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Coreset selection for the Sinkhorn divergence and generic smooth divergences
CO2 reduces coreset selection for any smooth divergence to MMD minimization and proves that Sinkhorn divergence coresets of size m=ω(log^d n) match the error of the full empirical measure.