Divyam Madaan

Evaluation of Active Feature Acquisition Policies with Tabular Foundation Models

Active feature acquisition learns policies that sequentially acquire features to maximize information about a target variable. We study how to learn and evaluate such policies from finite offline data using prior-data fitted networks (PFNs), which are off-the-shelf models that output posterior predictive distributions...