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Upala Junaida Islam, Kamran Paynabar, George Runger & Ashif Sikandar Iquebal. (2024) Dynamic exploration–exploitation trade-off in active learning regression with Bayesian hierarchical modeling. IISE Transactions 0:0, pages 1-15.
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Zhehui Chen, Simon Mak & C. F. Jeff Wu. (2023) A Hierarchical Expected Improvement Method for Bayesian Optimization. Journal of the American Statistical Association 0:0, pages 1-14.
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Yunfei Wei & Shifeng Xiong. (2019) Bayesian integrative analysis for multi-fidelity computer experiments. Journal of Applied Statistics 46:11, pages 1973-1987.
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Articles from other publishers (7)
Hanyan Huang, Zecong Liu, Hongyu Zheng, Xiaoyu Xu & Yanhui Duan. (2023) A proportional expected improvement criterion-based multi-fidelity sequential optimization method. Structural and Multidisciplinary Optimization 66:2.
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Raed Kontar, Naichen Shi, Xubo Yue, Seokhyun Chung, Eunshin Byon, Mosharaf Chowdhury, Jionghua Jin, Wissam Kontar, Neda Masoud, Maher Nouiehed, Chinedum E. Okwudire, Garvesh Raskutti, Romesh Saigal, Karandeep Singh & Zhi-Sheng Ye. (2021) The Internet of Federated Things (IoFT). IEEE Access 9, pages 156071-156113.
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Ray-Bing Chen, Yuan Wang & C. F. Jeff Wu. (2020) Finding optimal points for expensive functions using adaptive RBF-based surrogate model via uncertainty quantification. Journal of Global Optimization 77:4, pages 919-948.
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Yunxia Han, Yizhong Ma, Linhan Ouyang, Jianjun Wang & Yiliu Tu. (2019) Integrated multiresponse parameter and tolerance design with model parameter uncertainty. Quality and Reliability Engineering International 36:1, pages 414-433.
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Rajitha Meka, Adel Alaeddini, Sakiko Oyama & Kristina Langer. (2020) An Active Learning Methodology for Efficient Estimation of Expensive Noisy Black-Box Functions Using Gaussian Process Regression. IEEE Access 8, pages 111460-111474.
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