The authors of the paper on Strategic Conformal Prediction propose a framework designed for robust uncertainty quantification in settings where machine learning model predictions alter the environment because agents strategize to suit their own interests.

Authors

• Person: Samuel Tesfazgi, Leonhard Sprandl, Sandra Hirche Organization: AISTATS
  Track: Poster Session 3 - aistats 2026

Sources

• Track: Poster Session 3 - aistats 2026 virtual.aistats.org Samuel Tesfazgi, Leonhard Sprandl, Sandra Hirche · AISTATS via serper

Referenced by nodes (2)

• Uncertainty quantification concept
• machine learning concept