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William Stephenson

2 accepted papers

2020

Approximate Cross-Validation in High Dimensions with Guarantees

AISTATS 2020poster

Leave-one-out cross-validation (LOOCV) can be particularly accurate among cross-validation (CV) variants for machine learning assessment tasks – e.g., assessing methods’ error or variability. But it is expensive to re-fit a model $N$ times for a dataset of size $N$. Previous work has shown that appr…

2019

A Swiss Army Infinitesimal Jackknife

AISTATS 2019poster

The error or variability of machine learning algorithms is often assessed by repeatedly refitting a model with different weighted versions of the observed data. The ubiquitous tools of cross-validation (CV) and the bootstrap are examples of this technique. These methods are powerful in large part du…