1 citations · 2 across the 8 of their papers we have counts for
3 papers · 1 filter
Falling Trees: A Model Class for Interpretable Risk Prioritization
Varun Babbar, Zachery Boner, Margo Seltzer +1
Many real-world decisions require prioritizing high-risk cases, such as clinicians prioritizing high-risk patients before lower-risk ones. Falling rule lists (FRLs), which are orde…
CLARITree: Cholesky and Lookahead Accelerations for Regression with Interpretable Piecewise Linear Trees
Yixiao Wang, Hayden McTavish, Varun Babbar +2
Regression trees are among the most interpretable yet expressive model classes in machine learning. Historically, greedy induction has been the dominant approach for constructing w…
From Rashomon Theory to PRAXIS: Efficient Decision Tree Rashomon Sets
Zakk Heile, Hayden McTavish, Varun Babbar +2
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…