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arXiv · 1809.05572

Entropic optimal transport is maximum-likelihood deconvolution

Philippe Rigollet·Jonathan Weed
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Abstract

We give a statistical interpretation of entropic optimal transport by showing that performing maximum-likelihood estimation for Gaussian deconvolution corresponds to calculating a projection with respect to the entropic optimal transport distance. This structural result gives theoretical support for the wide adoption of these tools in the machine learning community.

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Philippe Rigollet, Jonathan Weed. 2018-09-14. Entropic optimal transport is maximum-likelihood deconvolution. https://arxiv.org/abs/1809.05572

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