Fair and Green Hyperparameter Optimization via Multi-objective and Multiple Information Source Bayesian Optimization. (arXiv:2205.08835v1 [cs.LG])

There is a consensus that focusing only on accuracy in searching for optimal
machine learning models amplifies biases contained in the data, leading to
unfair predictions and decision supports. Recently, multi-objective
hyperparameter optimization has been proposed to search for machine learning
models which offer equally Pareto-efficient trade-offs between accuracy and
fairness. Although these approaches proved to be more versatile than
fairness-aware machine learning algorithms -- which optimize accuracy
constrained to some threshold on fairness -- they could drastically increase
the …

arxiv bayesian information optimization