Speaker: Robert Tibshirani

Abstract: I discuss the problem of ``internal inference'': how to compare internally derived (trained) predictors to external predictors, based on the same data used for training. The methods that I will discuss for this problem include sample splitting, pre-validation and post-selectiion inference. This work is joint with Sam Gross and Jon Taylor.