2025
Active feature acquisition via explainability-driven ranking
ICML 2025poster
In many practical applications, including medicine, acquiring all relevant data for machine learning models is often infeasible due to constraints on time, cost, and resources. This makes it important to selectively acquire only the most informative features, yet traditional static feature selection…