2 papers
stat.ML2024
Model-agnostic variable importance for predictive uncertainty: an entropy-based approach
Danny Wood, Theodore Papamarkou, Matt Benatan +1
In order to trust the predictions of a machine learning algorithm, it is necessary to understand the factors that contribute to those predictions. In the case of probabilistic and…
cs.LG2024
An adaptive approach to Bayesian Optimization with switching costs
Stefan Pricopie, Richard Allmendinger, Manuel Lopez-Ibanez +3
We investigate modifications to Bayesian Optimization for a resource-constrained setting of sequential experimental design where changes to certain design variables of the search s…