Statistical bounds for entropic optimal transport: sample complexity and the central limit theorem
We prove several fundamental statistical bounds for entropic OT with the squared Euclidean cost between subgaussian probability measures in arbitrary dimension. First, through a new sample complexity result we establish the rate of convergence of entropic OT for empirical measures. Our analysis impr...
| Автори: | , |
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| Формат: | Conference item |
| Мова: | English |
| Опубліковано: |
MIT Press
2019
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