PPAT residualizes losses via a prediction-powered control variate inside LURE, yielding lower-variance unbiased risk estimates, tailored acquisition, and asymptotic CIs that cover with fewer labels.
Robins and Andrea Rotnitzky and Lue Ping Zhao
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3representative citing papers
Reordering flows in regression by composition changes the implied conditional distributions, model parameter interpretations, and associated estimation problems.
A discussion paper examining variation-independent regression through composition of statistical models.
citing papers explorer
-
Prediction-Powered Active Testing
PPAT residualizes losses via a prediction-powered control variate inside LURE, yielding lower-variance unbiased risk estimates, tailored acquisition, and asymptotic CIs that cover with fewer labels.
-
Order Dependence in Regression by Composition: Discussion on "Regression by Composition'' by Farewell, Daniel, Stensrud, and Huitfeldt
Reordering flows in regression by composition changes the implied conditional distributions, model parameter interpretations, and associated estimation problems.
-
Toward Variation-Independent Regression by Composition
A discussion paper examining variation-independent regression through composition of statistical models.