Pages that link to "Item:Q2274848"
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The following pages link to Bi-objective decision making in global optimization based on statistical models (Q2274848):
Displaying 16 items.
- Optimizing an objective function under a bivariate probability model (Q858457) (← links)
- A non-myopic utility function for statistical global optimization algorithms (Q1304756) (← links)
- Multi-objective optimization using statistical models (Q1728516) (← links)
- Visualization of a statistical approximation of the Pareto front (Q1732235) (← links)
- A framework for optimization under limited information (Q1945509) (← links)
- Gaussian process optimization with failures: classification and convergence proof (Q2022175) (← links)
- Nonconvex constrained optimization by a filtering branch and bound (Q2038915) (← links)
- An improved arithmetic optimization algorithm with forced switching mechanism for global optimization problems (Q2130099) (← links)
- Development of an adaptive infill criterion for constrained multi-objective asynchronous surrogate-based optimization (Q2200087) (← links)
- A hybrid of Bayesian-based global search with Hooke–Jeeves local refinement for multi-objective optimization problems (Q5080393) (← links)
- A statistical model-based algorithm for ‘black-box’ multi-objective optimisation (Q5172540) (← links)
- On the use of Wasserstein distance in the distributional analysis of human decision making under uncertainty (Q6113067) (← links)
- An adaptive batch Bayesian optimization approach for expensive multi-objective problems (Q6122320) (← links)
- Keyword-level Bayesian online bid optimization for sponsored search advertising (Q6559525) (← links)
- Dynamic exploration-exploitation Pareto approach for high-dimensional expensive black-box optimization (Q6568408) (← links)
- A new Bayesian approach to global optimization on parametrized surfaces in \(\mathbb{R}^3\) (Q6614697) (← links)
