Kodera, Yuta Nagai, Tomoyuki Horikawa, Kota Matsui, Ichiro Takeuchi, and Toru Ujihara. Adaptive bayesian optimization for epitaxial growth of si thin films under various constraints. Materials Today Communications, 25:101538, 2020. [22] Carl Edward Rasmussen and Christopher KI Williams. Gaussian process for machine learning. MIT press, 2006. [23] Bobak Shahriari, Kevin Swersky, Ziyu Wang, Ryan P Adams, and Nando De Freitas. Taking the human out of the loop: A review of bayesian optimization. Proceedings of the IEEE, 104(1):148–175, 2016. [24] Jasper Snoek. Bayesian optimization and semiparametric models with applications to assistive technology. PhD thesis, Citeseer, 2013. [25] Jasper Snoek, Hugo Larochelle, and Ryan P Adams. Practical bayesian optimization of machine learning algorithms. NeurIPS, 2012. [26] Shinya Suzuki, Shion Takeno, Tomoyuki Tamura, Kazuki Shitara, and Masayuki Karasuyama. Multi-objective bayesian optimization using pareto-frontier entropy. ICML, 2020. [27] Ami Takahashi and Taiji Suzuki. Bayesian optimization for estimating the maximum tolerated dose in phase i clinical trials. Contemporary clinical trials communications, 21:100753, 2021. [28] Kazuaki Toyoura, Daisuke Hirano, Atsuto Seko, Motoki Shiga, Akihide Kuwabara, Masayuki Karasuyama, Kazuki Shitara, and Ichiro Takeuchi. Machine-learning-based selective sampling procedure for identifying the low-energy region in a potential energy surface: A case study on proton conduction in oxides. Physical Review B, 93(5):054112, 2016. [29] Zi Wang and Stefanie Jegelka. Max-value entropy search for efficient bayesian optimization. ICML, 2017. [30] Ziyu Wang, Masrour Zoghi, Frank Hutter, David Matheson, and Nando De Freitas. Bayesian optimization in high dimensions via random embeddings. IJCAI, 2013. [31] Marcela Zuluaga, Guillaume Sergent, Andreas Krause, and Markus Püschel. Active learning for multi-objective optimization. International Conference on Machine Learning, 2013. [32] 持橋大地, 大羽成征. ガウス過程と機械学習. 講談社, 2019. [33] 須山敦志. ベイズ推論による機械学習入門. 講談社, 2017. [34] 福水健次. カーネル法入門. 朝倉書店, 2010. [35] 穂積祥太, 松井孝太, 沓掛健太朗, 宇治原徹, 竹内一郎. Level set estimation を用いた太陽電池用シリコンのレッ ドゾーンの効率的推定. In 第 33 回人工知能学会 (JSAI) 全国大会, 2019. 松井 (名古屋大) 機械学習による適応的実験計画 151 / 151