BOHB swMATH ID: 35481 Software Authors: Stefan Falkner, Aaron Klein, Frank Hutter Description: BOHB: Robust and Efficient Hyperparameter Optimization at Scale. Modern deep learning methods are very sensitive to many hyperparameters, and, due to the long training times of state-of-the-art models, vanilla Bayesian hyperparameter optimization is typically computationally infeasible. On the other hand, bandit-based configuration evaluation approaches based on random search lack guidance and do not converge to the best configurations as quickly. Here, we propose to combine the benefits of both Bayesian optimization and bandit-based methods, in order to achieve the best of both worlds: strong anytime performance and fast convergence to optimal configurations. We propose a new practical state-of-the-art hyperparameter optimization method, which consistently outperforms both Bayesian optimization and Hyperband on a wide range of problem types, including high-dimensional toy functions, support vector machines, feed-forward neural networks, Bayesian neural networks, deep reinforcement learning, and convolutional neural networks. Our method is robust and versatile, while at the same time being conceptually simple and easy to implement. Homepage: https://arxiv.org/abs/1807.01774 Source Code: https://github.com/automl/HpBandSter Related Software: Hyperband; Hyperopt; SMAC; Spearmint; BoTorch; Scikit; Adam; TensorFlow; UCI-ml; PyTorch; RoBO; GPflowOpt; AlexNet; ImageNet; OpenAI Gym; EGO; GitHub; RMSprop; OpenML; Tunability Cited in: 9 Publications all top 5 Cited by 49 Authors 2 Ammar, Haitham Bou 2 Cowen-Rivers, Alexander I. 2 Griffiths, Ryan-Rhys 2 Grosnit, Antoine 2 Tutunov, Rasul 2 Wang, Jun 1 Baldi, Pierre 1 Biedenkapp, André 1 Browne, James C. 1 Burns, Randal 1 Calandra, Roberto 1 Chen, Xiaoli 1 Chung, Jaewon 1 Duan, Jinqiao 1 Eimer, Theresa 1 Falk, Benjamin 1 Faust, Aleksandra 1 Gillen, Daniel L. 1 Grabocka, Josif 1 Hertel, Lars 1 Huber, Marco F. 1 Hutter, Frank 1 Jianye, Hao 1 Jomaa, Hadi S. 1 Karniadakis, George Em 1 Lindauer, Marius 1 Lyu, Wenlong 1 Maggioni, Mauro 1 Maraval, Alexandre Max 1 Miao, Yingjie 1 Nomura, Masahiro 1 Onishi, Masaki 1 Ozaki, Yoshihiko 1 Parker-Holder, Jack 1 Patsolic, Jesse L. 1 Peters, Jan 1 Priebe, Carey E. 1 Rajan, Raghu 1 Schmidt-Thieme, Lars 1 Shen, Cencheng 1 Song, Xingyou 1 Tanigaki, Yuki 1 Tomita, Tyler M. 1 Vogelstein, Joshua T. 1 Wang, Zhi 1 Watanabe, Shuhei 1 Yim, Jason 1 Zhang, Baohe 1 Zöller, Marc-André Cited in 5 Serials 4 The Journal of Artificial Intelligence Research (JAIR) 2 Journal of Machine Learning Research (JMLR) 1 European Journal of Applied Mathematics 1 Data Mining and Knowledge Discovery 1 Journal of Computational and Graphical Statistics Cited in 3 Fields 8 Computer science (68-XX) 1 Partial differential equations (35-XX) 1 Statistics (62-XX) Citations by Year