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...
| Main Authors: | , |
|---|---|
| Formato: | Conference item |
| Idioma: | English |
| Publicado em: |
MIT Press
2019
|