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stat.ML2025
Model-Free Kernel Conformal Depth Measures Algorithm for Uncertainty Quantification in Regression Models in Separable Hilbert Spaces
Marcos Matabuena, Rahul Ghosal, Pavlo Mozharovskyi +2
Depth measures are powerful tools for defining level sets in emerging, non--standard, and complex random objects such as high-dimensional multivariate data, functional data, and ra…
stat.ML2025
Nonparametric Additive Value Functions: Interpretable Reinforcement Learning with an Application to Surgical Recovery
Patrick Emedom-Nnamdi, Timothy R. Smith, Jukka-Pekka Onnela +1
We propose a nonparametric additive model for estimating interpretable value functions in reinforcement learning, with an application in optimizing postoperative recovery through p…