Research map / Learning theory and algorithms / Sample complexity
Efficient Nonparametric Smoothness Estimation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Increase sample size from 10 to 100000 for estimating L2 distances | Sobolev estimator (s=0) on 1D and 3D distributions · synthetic Gaussians and uniform distributions | confidence interval width / accuracy of L2 distance estimate | Helped |
| Estimate smoother densities (Gaussians) instead of discontinuous ones (uniforms) for the same Sobolev quantity | Sobolev estimator · synthetic 1D distributions | sample requirement for accurate estimate | Helped |
| Estimate H^0 norm instead of H^1 norm | Sobolev estimator on N(0,1) · synthetic N(0,1) | sample requirement | Helped |
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