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Mirror Descent with Relative Smoothness in Measure Spaces, with application to Sinkhorn and EM
We also show that Expectation Maximization (EM) can always formally be written as a mirror descent.
Faster Wasserstein Distance Estimation with the Sinkhorn Divergence
We also propose and analyze an estimator based on Richardson extrapolation of the Sinkhorn divergence which enjoys improved statistical and computational efficiency guarantees, under a condition on the regularity of the approximation error, which is in particular satisfied for Gaussian densities.
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