Research map / Learning theory and algorithms / Sample complexity
Coresets for Regressions with Panel Data
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use sensitivity-based CGLSE coreset instead of uniform sampling | GLSE coreset · Synthetic (Gaussian) | max empirical error | Helped |
| use sensitivity-based CGLSE coreset instead of uniform sampling | GLSE coreset · Synthetic (Cauchy) | max empirical error: .998 -> .096 at eps=0.5 | Helped |
| use sensitivity-based CGLSE coreset instead of uniform sampling | GLSE coreset · Real-world credit card | max empirical error: 1.107 -> .294 at eps=0.5 | Helped |
| use coreset instead of full data to solve GLSE | IRLS for GLSE · GLSE solving time | speed-up: 1.2x-108x | Helped |
| use CGLSE instead of uniform sampling | GLSE coreset · all datasets | average empirical error | Mixed |
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