3 citations · 11 across the 15 of their papers we have counts for
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stat.ME2021
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…
cs.LG2021★ 1 cited
Online Selective Classification with Limited Feedback
Aditya Gangrade, Anil Kag, Ashok Cutkosky +1
Motivated by applications to resource-limited and safety-critical domains, we study selective classification in the online learning model, wherein a predictor may abstain from clas…