Initializing hyper-parameter tuning with a metaheuristic-ensemble method: a case study using time-series weather data

Author:

Öztürk Muhammed MarufORCID

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Vision and Pattern Recognition,Mathematics (miscellaneous)

Reference69 articles.

1. Feurer M, Springenberg J, Hutter F (2015) Initializing bayesian hyperparameter optimization via meta-learning. In Proceedings of the AAAI conference on artificial intelligence 29(1)

2. Maclaurin D, Duvenaud D, Adams R (2015) Gradient-based hyperparameter optimization through reversible learning. In International conference on machine learning 2113-2122

3. Li L, Jamieson K, DeSalvo G, Rostamizadeh A, Talwalkar A (2017) Hyperband: a novel bandit-based approach to hyperparameter optimization. J Mach Learn Res 18(1):6765–6816

4. Paine TL, Paduraru C, Michi A, Gulcehre C, Zolna K, Novikov A, Freitas ND. (2020) Hyperparameter selection for offline reinforcement learning. arXiv preprint arXiv:2007.09055

5. Smithson SC, Yang G, Gross WJ, Meyer BH (2016) Neural networks designing neural networks: multi-objective hyper-parameter optimization. In: Proceedings of the 35th international conference on computer-aided design 1-8. https://doi.org/10.1145/2966986.2967058

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