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math.ST2021★ 17 cited
Valid inferential models for prediction in supervised learning problems
Leonardo Cella, Ryan Martin
Prediction, where observed data is used to quantify uncertainty about a future observation, is a fundamental problem in statistics. Prediction sets with coverage probability guaran…
math.ST2021★ 10 cited
Direct and approximately valid probabilistic inference on a class of statistical functionals
Leonardo Cella, Ryan Martin
Existing frameworks for probabilistic inference assume the quantity of interest is the parameter of a posited statistical model. In machine learning applications, however, often th…