2 citations · 2 across the 5 of their papers we have counts for
3 papers · 1 filter
Extrapolation in Statistical Learning with Extreme Value Theory
Sebastian Engelke, Nicola Gnecco, Anne Sabourin
Extreme value theory provides rigorous theory and statistical tools for extrapolation in machine learning, particularly in settings where traditional methods struggle due to data s…
Achievable distributional robustness when the robust risk is only partially identified
Julia Kostin, Nicola Gnecco, Fanny Yang
In safety-critical applications, machine learning models should generalize well under worst-case distribution shifts, that is, have a small robust risk. Invariance-based algorithms…
Boosted Control Functions: Distribution generalization and invariance in confounded models
Nicola Gnecco, Jonas Peters, Sebastian Engelke +1
Modern machine learning methods and the availability of large-scale data have significantly advanced our ability to predict target quantities from large sets of covariates. However…