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Bayesian methods in global optimization
Journal of Global Optimization, 1991The paper reviews methods which have been proposed for solving global optimization problems in the framework of the Bayesian paradigm. Three main approaches are singled out. In the first approach, called the Random Function Approach, methods are based on the idea of introducing a probabilistic model for the objective function in the form of a random ...
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Global Optimization by Monotonic Transformation
Computational Optimization and Applications, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Global Optimization on Funneling Landscapes
Journal of Global Optimization, 2000zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Global Optimization in the COCONUT Project
2004In this article, a solver platform for global optimization is presented, as it is developed in the COCONUT project. After a short introduction, a short description is given of the basic algorithmic concept and of all relevant components, the strategy engine, inference engines, and the remaining modules. A compact description of the search graph and its
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A collaborative neurodynamic approach to global and combinatorial optimization
Neural Networks, 2019Jun Wang, Hangjun Che
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Global patterns in excess body weight and the associated cancer burden
Ca-A Cancer Journal for Clinicians, 2019Ahmedin Jemal, Susan Gapstur
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Application of Bayesian approach to numerical methods of global and stochastic optimization
Journal of Global Optimization, 1994Jonas Mockus
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