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Dual-phase multiobjective Bayesian optimization method for estimating hepatocellular carcinoma dynamics parameters from PET/CT scans. [PDF]
Quant Imaging Med SurgXiong X, Huang J, Li S, He J, Wang S.
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Bayesian optimization of cortical neuroprosthetic vision using perceptual feedback
Küçükoğlu B +7 more
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Proceedings of the Companion Conference on Genetic and Evolutionary Computation, 2023
Bayesian optimization is a methodology for optimizing expensive objective functions that has proven success in the sciences, engineering, and beyond. This timely text provides a self-contained and comprehensive introduction to the subject, starting from scratch and carefully developing all the key ideas along the way.
Hao Wang, Kaifeng Yang
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Bayesian optimization is a methodology for optimizing expensive objective functions that has proven success in the sciences, engineering, and beyond. This timely text provides a self-contained and comprehensive introduction to the subject, starting from scratch and carefully developing all the key ideas along the way.
Hao Wang, Kaifeng Yang
+5 more sources
International Journal of Data Science and Analytics, 2017
Tuning hyperparameters of machine learning models is important for their performance. Bayesian optimization has recently emerged as a de-facto method for this task. The hyperparameter tuning is usually performed by looking at model performance on a validation set.
Thanh Dai Nguyen +3 more
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Tuning hyperparameters of machine learning models is important for their performance. Bayesian optimization has recently emerged as a de-facto method for this task. The hyperparameter tuning is usually performed by looking at model performance on a validation set.
Thanh Dai Nguyen +3 more
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Bayesian optimal knapsack procurement
European Journal of Operational Research, 2013zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ensthaler, Ludwig, Giebe, Thomas
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Economic Theory, 2017
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2022
Ivo Couckuyt +2 more
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Ivo Couckuyt +2 more
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2019
GO and BO have been considered first in “essentially unconstrained” conditions, where the solution was searched for within a bounded-box search space. Recently, due to methodological and application reasons, there has been an increasing interest in constrained global optimization (CGO).
Francesco Archetti, Antonio Candelieri
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GO and BO have been considered first in “essentially unconstrained” conditions, where the solution was searched for within a bounded-box search space. Recently, due to methodological and application reasons, there has been an increasing interest in constrained global optimization (CGO).
Francesco Archetti, Antonio Candelieri
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2016
Multi-stage cascade processes are fairly common, especially in manufacturing industry. Precursors or raw materials are transformed at each stage before being used as the input to the next stage. Setting the right control parameters at each stage is important to achieve high quality products at low cost.
Thanh Dai Nguyen +6 more
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Multi-stage cascade processes are fairly common, especially in manufacturing industry. Precursors or raw materials are transformed at each stage before being used as the input to the next stage. Setting the right control parameters at each stage is important to achieve high quality products at low cost.
Thanh Dai Nguyen +6 more
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Bayesian statistics and modelling
Nature Reviews Methods Primers, 2021Rens van de Schoot +2 more
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