Set Membership

Set membership focuses on determining whether a data point belongs to a specific set, addressing challenges in various fields from control systems to machine learning. Current research emphasizes developing efficient algorithms for set estimation and manipulation, particularly using ellipsoids and zonotopes, and applying these techniques to problems like target tracking, causal inference testing, and robust control. This work is significant because it provides rigorous uncertainty quantification and improves the explainability and reliability of complex systems, impacting areas such as autonomous vehicle navigation and the privacy of machine learning models.