Marco Carone — accepted AI-conference papers

2023

Causal Isotonic Calibration for Heterogeneous Treatment Effects

Lars van der Laan, Ernesto Ulloa-Perez, Marco Carone, Alex Luedtke

ICML 2023poster

We propose causal isotonic calibration, a novel nonparametric method for calibrating predictors of heterogeneous treatment effects. Furthermore, we introduce cross-calibration, a data-efficient variant of calibration that eliminates the need for hold-out calibration sets. Cross-calibration leverages…

Cited by 18 Source ↗PDF ↗code ↗Scholar ↗

2018

Nonparametric variable importance using an augmented neural network with multi-task learning

Jean Feng, Brian Williamson, Noah Simon, Marco Carone

ICML 2018oral

In predictive modeling applications, it is often of interest to determine the relative contribution of subsets of features in explaining the variability of an outcome. It is useful to consider this variable importance as a function of the unknown, underlying data-generating mechanism rather than the…

Cited by 16 Source ↗PDF ↗code ↗Scholar ↗