Multi-Objective Hyperparameter Optimization -- An Overview. (arXiv:2206.07438v1 [cs.LG])

Web: http://arxiv.org/abs/2206.07438

Hyperparameter optimization constitutes a large part of typical modern
machine learning workflows. This arises from the fact that machine learning
methods and corresponding preprocessing steps often only yield optimal
performance when hyperparameters are properly tuned. But in many applications,
we are not only interested in optimizing ML pipelines solely for predictive
accuracy; additional metrics or constraints must be considered when determining
an optimal configuration, resulting in a multi-objective optimization problem.
This is often neglected in practice, due to a lack …

arxiv lg optimization overview