structured-learning

This paper proposes a structured reinforcement learning framework for Bayesian persuasion in interactive driving, where a lead vehicle selectively reveals traffic information to guide connected vehicles. The method introduces MAPL and SQP algorithms, achieving 30% cost efficiency over existing methods.

QDSP is an interpretable structured learning framework for predicting death or cerebral palsy in very low birth weight infants, integrating Quota-guided Subspace Sampling and Differentiable-decision-guided Structure Perception. It outperforms baselines like XGBoost, TabNet, and TabPFN on a real cohort and external datasets, identifying clinically relevant predictors such as cPVL and birth weight.