Post-ADC inference supplies valid p-values and confidence intervals for data-dependent targets after active data collection by extending selective inference to correct for both adaptive sampling bias and post-hoc target selection, relying only on noise assumptions.
Post-selection adaptive inference for least angle regression and the lasso.arXiv preprint arXiv:1401.3889, 354
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 2verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
A conditional adaptive perturbation approach enables valid in-sample inference for machine learning-identified subgroups with nonregular boundaries via triple robustness.
citing papers explorer
-
Post-ADC Inference: Valid Inference After Active Data Collection
Post-ADC inference supplies valid p-values and confidence intervals for data-dependent targets after active data collection by extending selective inference to correct for both adaptive sampling bias and post-hoc target selection, relying only on noise assumptions.