347 citations · 365 across the 11 of their papers we have counts for
3 papers · 1 filter
Optimizing with Low Budgets: a Comparison on the Black-box Optimization Benchmarking Suite and OpenAI Gym
Elena Raponi, Nathanael Rakotonirina Carraz, Jérémy Rapin +2
The growing ubiquity of machine learning (ML) has led it to enter various areas of computer science, including black-box optimization (BBO). Recent research is particularly concern…
Self-Adjusting Weighted Expected Improvement for Bayesian Optimization
Carolin Benjamins, Elena Raponi, Anja Jankovic +2
Bayesian Optimization (BO) is a class of surrogate-based, sample-efficient algorithms for optimizing black-box problems with small evaluation budgets. The BO pipeline itself is hig…
Comparison of High-Dimensional Bayesian Optimization Algorithms on BBOB
Maria Laura Santoni, Elena Raponi, Renato De Leone +1
Bayesian Optimization (BO) is a class of black-box, surrogate-based heuristics that can efficiently optimize problems that are expensive to evaluate, and hence admit only small eva…