Pages that link to "Item:Q3939608"

The following pages link to Axiomatic approach to statistical models and their use in multimodal optimization theory (Q3939608):

Displaying 18 items.

• On strong homogeneity of two global optimization algorithms based on statistical models of multimodal objective functions (Q440675) (← links)
• On a global optimization algorithm for bivariate smooth functions (Q481774) (← links)
• Concurrent stochastic methods for global optimization (Q908855) (← links)
• Fitting three-parameter lognormal models by numerical global optimization - an improved algorithm (Q1058282) (← links)
• Axiomatic characterization of a global optimization algorithm and investigation of its search strategy (Q1061007) (← links)
• Extended univariate algorithms for \(n\)-dimensional global optimization (Q1062427) (← links)
• Global optimization on convex sets (Q1089268) (← links)
• Bayesian methods in global optimization (Q1177909) (← links)
• Convergence qualification of adaptive partition algorithms in global optimization (Q1196187) (← links)
• On similarities between two models of global optimization: Statistical models and radial basis functions (Q1959246) (← links)
• Statistical modeling of directional data using a robust hierarchical von Mises distribution model: perspectives for wind energy (Q2095704) (← links)
• Small Sample Estimation of Parameters for Wiener Process with Noise (Q3098937) (← links)
• Stochastic Methods for Global Optimization (Q3220103) (← links)
• Existence of a stochastic function consistent with the conditional likelihood relation (Q3337334) (← links)
• Globally convergent methods for <i>n</i>-dimensional multiextremal optimization (Q3727749) (← links)
• Branch- and bound algorithms for solving global optimization problems with Lipschitzian structure (Q3789345) (← links)
• A statistical model-based algorithm for ‘black-box’ multi-objective optimisation (Q5172540) (← links)
• On an Asymptotic Property of a Simplicial Statistical Model of Global Optimization (Q5270524) (← links)