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stat.ME2026
Adaptive Off-Policy Inference for M-Estimators Under Model Misspecification
James Leiner, Robin Dunn, Aaditya Ramdas
When data are collected adaptively, such as in bandit algorithms, classical statistical approaches such as ordinary least squares and -estimation will often fail to achieve asym…
stat.ME2024
Universal Inference Meets Random Projections: A Scalable Test for Log-concavity
Robin Dunn, Aditya Gangrade, Larry Wasserman +1
Shape constraints yield flexible middle grounds between fully nonparametric and fully parametric approaches to modeling distributions of data. The specific assumption of log-concav…