2 papers
cs.LG2025
Leveraging Axis-Aligned Subspaces for High-Dimensional Bayesian Optimization with Group Testing
Erik Hellsten, Carl Hvarfner, Leonard Papenmeier +1
Bayesian optimization (BO ) is an effective method for optimizing expensive-to-evaluate black-box functions. While high-dimensional problems can be particularly challenging, due to…
cs.LG2024
Vanilla Bayesian Optimization Performs Great in High Dimensions
Carl Hvarfner, Erik Orm Hellsten, Luigi Nardi
High-dimensional problems have long been considered the Achilles' heel of Bayesian optimization algorithms. Spurred by the curse of dimensionality, a large collection of algorithms…