Making a case for (Hyper-)parameter tuning as benchmark problems
Carola Doerr, Johann Dréo, Pascal Kerschke · Proceedings of the Genetic and Evolutionary Computation Conference Companion · 2019
One of the biggest challenges in evolutionary computation concerns the selection and configuration of a best-suitable heuristic for a given problem. While in the past both of these problems have primarily been addressed by building on experts' experience, the last decade has witnessed a significant shift towards automated decision making, which capitalizes on techniques proposed in the machine learning literature.