Research map / Learning theory and algorithms / Optimal transport
Minimax Statistical Learning with Wasserstein distances
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use local minimax ERM with a Wasserstein ambiguity radius instead of ordinary ERM | Two-hypothesis illustrative example · Unif[0,1] example | probability of selecting the nonrobust hypothesis: (1 - \varrho\alpha^{1/p})^n | Helped |
| Use a larger Wasserstein ambiguity radius | Local minimax ERM under the single-smooth-hypothesis assumption · Generalization excess-risk bound | excess-risk bound: 24C_0(2\,\mathsf{diam}(\cZ))^p \left(1+\left(\frac{\mathsf{diam}(\cZ)}{\varrho}\right)^p\right) | Mixed |
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