1 citations · 1 across the 2 of their papers we have counts for
3 papers
stat.ML2026
Null importance: Disentangling relevance for interpretable machine learning
Garvesh Raskutti, Kris Sankaran, Jiaxin Ye
Feature importance is central to interpretable machine learning, but the term "importance" encompasses several fundamentally different notions of relevance. We develop a unified pe…
stat.ME2025
Joint Adaptive Penalty for Unbalanced Mediation Pathways
Hanying Jiang, Kris Sankaran, Yinqiu He
Mediation analysis has been widely used to investigate how a treatment influences an outcome through intermediate variables, known as mediators. Analyzing a mediation mechanism typ…
stat.ML2024★ 1 cited
Data Science Principles for Interpretable and Explainable AI
Kris Sankaran
Society's capacity for algorithmic problem-solving has never been greater. Artificial Intelligence is now applied across more domains than ever, a consequence of powerful abstracti…