Hyper-parameter optimization based on soft actor critic and hierarchical mixture regularization [article]

Chaoyue Liu, Yulai Zhang
2021 arXiv   pre-print
Hyper-parameter optimization is a crucial problem in machine learning as it aims to achieve the state-of-the-art performance in any model. Great efforts have been made in this field, such as random search, grid search, Bayesian optimization. In this paper, we model hyper-parameter optimization process as a Markov decision process, and tackle it with reinforcement learning. A novel hyper-parameter optimization method based on soft actor critic and hierarchical mixture regularization has been
more » ... osed. Experiments show that the proposed method can obtain better hyper-parameters in a shorter time.
arXiv:2112.04084v1 fatcat:u3hgnr3vgrabhobuxoco6hj424