過去のHPO(Hyperparameter Optimization)に関する先行事例をAutomated Machine Learningから持ってきました。

King, R., Feng, C., Sutherland, A.: Statlog: comparison of classification algorithms on large
real-world problems. Applied Artificial Intelligence an International Journal 9(3), 289–333
(1995)
Lee, D., Sugiyama, M., von Luxburg, U., Guyon, I., Garnett, R. (eds.): Proceedings of
the 30th International Conference on Advances in Neural Information Processing Systems
(NeurIPS’16) (2016)
Michie, D., Spiegelhalter, D., Taylor, C., Campbell, J. (eds.): Machine Learning, Neural and
Statistical Classification. Ellis Horwood (1994)
Ripley, B.D.: Statistical aspects of neural networks. Networks and chaos—statistical and
probabilistic aspects 50, 40–123 (1993)
Escalante, H., Montes, M., Sucar, E.: Particle Swarm Model Selection. Journal of Machine
Learning Research 10, 405–440 (2009)
Mantovani, R., Horvath, T., Cerri, R., Vanschoren, J., Carvalho, A.: Hyper-Parameter Tuning
of a Decision Tree Induction Algorithm. In: 2016 5th Brazilian Conference on Intelligent
Systems (BRACIS). pp. 37–42. IEEE Computer Society Press (2016)
Olson, R., La Cava, W.,Mustahsan, Z., Varik, A., Moore, J.: Data-driven advice for applying
machine learning to bioinformatics problems. In: Proceedings of the Pacific Symposium in
Biocomputing 2018. pp. 192–203 (2018)
Sanders, S., Giraud-Carrier, C.: Informing the Use of Hyperparameter Optimization Through
Metalearning. In: Gottumukkala, R., Ning, X., Dong, G., Raghavan, V., Aluru, S., Karypis,
G., Miele, L., Wu, X. (eds.) 2017 IEEE International Conference on Big Data (Big Data).
IEEE Computer Society Press (2017)
Thornton, C., Hutter, F., Hoos, H., Leyton-Brown, K.: Auto-WEKA: combined selection and
hyperparameter optimization of classification algorithms. In: Dhillon, I., Koren, Y., Ghani,
R., Senator, T., Bradley, P., Parekh, R., He, J., Grossman, R., Uthurusamy, R. (eds.) The
19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
(KDD’13). pp. 847–855. ACM Press (2013)
1. Golovin, D., Solnik, B., Moitra, S., Kochanski, G., Karro, J., Sculley, D.: Google Vizier: A
  service for black-box optimization. In: Matwin, S., Yu, S., Farooq, F. (eds.) Proceedings of
  the 23rd ACM SIGKDD International Conference on Knowledge Discovery and DataMining
  (KDD). pp. 1487–1495. ACM Press (2017)

ここからはサービスの事例

Amazon: Automatic model tuning (2018), https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning.html
Li, F.F., Li, J.: Cloud AutoML: Making AI accessible to every business (2018), https://www.blog.google/products/google-cloud/cloud-automl-making-ai-accessible-every-business/
SIGOPT: Improve ML models 100x faster (2018), https://sigopt.com/

何か発表する時の裏取りに使おう。