Pages that link to "Item:Q2414108"
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The following pages link to Selection of a covariance function for a Gaussian random field aimed for modeling global optimization problems (Q2414108):
Displaying 10 items.
- Convergence properties of the expected improvement algorithm with fixed mean and covariance functions (Q988941) (← links)
- Gaussian process optimization with failures: classification and convergence proof (Q2022175) (← links)
- On the search of the shape parameter in radial basis functions using univariate global optimization methods (Q2022236) (← links)
- Modelling human active search in optimizing black-box functions (Q2156913) (← links)
- Development of an adaptive infill criterion for constrained multi-objective asynchronous surrogate-based optimization (Q2200087) (← links)
- A hybrid of Bayesian approach based global search with clustering aided local refinement (Q2206585) (← links)
- Bayesian optimization using deep Gaussian processes with applications to aerospace system design (Q2245694) (← links)
- A new construction of covariance functions for Gaussian random fields (Q6123502) (← links)
- A new Bayesian approach to global optimization on parametrized surfaces in \(\mathbb{R}^3\) (Q6614697) (← links)
- Optimization of expensive black-box problems with penalized expected improvement (Q6663338) (← links)
