FlexHB: a More Efficient and Flexible Framework for Hyperparameter Optimization

arXiv:2402.13641v1 Announce Type: new
Abstract: Given a Hyperparameter Optimization(HPO) problem, how to design an algorithm to find optimal configurations efficiently? Bayesian Optimization(BO) and the multi-fidelity BO methods employ surrogate models to sample configurations based on history evaluations. More recent studies obtain better performance by integrating BO with HyperBand(HB), which accelerates evaluation by early stopping mechanism. However, these methods ignore the advantage of a suitable evaluation scheme over the default HyperBand, and the capability of BO is still constrained by skewed …

abstract algorithm arxiv bayesian cs.lg design fidelity framework history hyperparameter optimization performance sample studies type