From Rashomon Theory to PRAXIS: Efficient Decision Tree Rashomon Sets 事件

From Rashomon Theory to PRAXIS: Efficient Decision Tree Rashomon Sets arXiv:2606.00202v1 Announce Type: cross Abstract: Standard machine learning pipelines often admit many near-optimal models. These "Rashomon sets" pose a range of challenges and opportunities for uncertainty-aware, robust decision making. They allow users to incorporate domain knowledge and preferences that would otherwise be difficult to specify directly in an objective, and they quantify diversity among valid models for a gi