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Sequential stopping rules for the multistart algorithm in global optimisation
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Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-0-387-44956-2_22openalex-snapshot
Recognizing the Maximum of a Sequence
inferredcites →https://doi.org/10.1007/bf01584254openalex-snapshot
A statistical estimate of the structure of multi-extremal problems
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A survey on the global optimization problem: General theory and computational approaches
inferredcites →https://doi.org/10.1007/bf02591684openalex-snapshot
Bayesian stopping rules for multistart global optimization methods
inferredcites →https://doi.org/10.1080/01621459.1966.10502008openalex-snapshot
Recognizing the Maximum of a Sequence
inferredcites →https://doi.org/10.1080/02331938608843184openalex-snapshot
Bayesian nonparametrie inference and monte carlo optimization
inferredcites →https://doi.org/10.1214/aop/1176996703openalex-snapshot
Tailfree and Neutral Random Probabilities and Their Posterior Distributions
inferredcites →https://doi.org/10.1214/aos/1176342360openalex-snapshot
A Bayesian Analysis of Some Nonparametric Problems
inferredcites →https://doi.org/10.1214/aos/1176342662openalex-snapshot
Empirical Probability Plots and Statistical Inference for Nonlinear Models in the Two-Sample Case
inferredcites →https://doi.org/10.1214/aos/1176344562openalex-snapshot
Bayesian Nonparametric Estimation Based on Censored Data
inferredcites →https://doi.org/10.4064/-16-1-37-42openalex-snapshot
A sequential Bayesian approach to estimating the dimension of a multinomial distribution
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Bayesian Global Optimization
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Stochastic Global Optimization: Stopping Rules
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Neural Network Approach to Design of Distributed Hard Real-Time Systems
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Bayesian Global Optimization
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Stochastic Global Optimization: Stopping Rules
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Two-Phase Methods for Global Optimization
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Bayesian Global Optimization
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Stochastic techniques for global optimization: A survey of recent advances
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Bayesian methods in global optimization
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On when to stop sampling for the maximum
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On a new stochastic global optimization algorithm based on censored observations
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Multistart method with estimation scheme for global satisfycing problems
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On the role of continuously differentiable exact penalty functions in constrained global optimization
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The repulsion algorithm, a new multistart method for global optimization
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Global optimization using accurate approximations in design synthesis
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Optimal and sub-optimal stopping rules for the Multistart algorithm in global optimization
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Global optimization on convex sets
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Global optimization with a limited solution time
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Statistical optimum estimation techniques for combinatorial optimization problems: a review and critique
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Bayesian Stopping Rules for Greedy Randomized Procedures
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Stopping and restarting strategy for stochastic sequential search in global optimization
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Stochastic optimization with adaptive restart: a framework for integrated local and global learning
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Parallel genetic algorithms with local search
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A Non-myopic Utility Function for Statistical Global Optimization Algorithms
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Trace-Based Methods for Solving Nonlinear Global Optimization and Satisfiability Problems
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Stopping eules for the multistart method when different local minima have different function values
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Adaptive LQG Control of Input-Output Systems---A Cost-biased Approach
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Sequential Stopping Rules for Random Optimization Methods with Applications to Multistart Local Search
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Global optimization algorithms for bound constrained problems
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Reliability-Based Optimization of Uncertain Systems in Structural Dynamics
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Global optimization using accurate approximations in design synthesis
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Automatic Differentiation-Based Multi-Start for Gradient-Based Optimization Methods
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Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap
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