43 citations · 98 across the 13 of their papers we have counts for
4 papers · 1 filter
Towards Automated Design of Bayesian Optimization via Exploratory Landscape Analysis
Carolin Benjamins, Anja Jankovic, Elena Raponi +3
Bayesian optimization (BO) algorithms form a class of surrogate-based heuristics, aimed at efficiently computing high-quality solutions for numerical black-box optimization problem…
PI is back! Switching Acquisition Functions in Bayesian Optimization
Carolin Benjamins, Elena Raponi, Anja Jankovic +4
Bayesian Optimization (BO) is a powerful, sample-efficient technique to optimize expensive-to-evaluate functions. Each of the BO components, such as the surrogate model, the acquis…
Per-run Algorithm Selection with Warm-starting using Trajectory-based Features
Ana Kostovska, Anja Jankovic, Diederick Vermetten +4
Per-instance algorithm selection seeks to recommend, for a given problem instance and a given performance criterion, one or several suitable algorithms that are expected to perform…
Trajectory-based Algorithm Selection with Warm-starting
Anja Jankovic, Diederick Vermetten, Ana Kostovska +3
Landscape-aware algorithm selection approaches have so far mostly been relying on landscape feature extraction as a preprocessing step, independent of the execution of optimization…