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Continuous surrogate-based optimization algorithms are well-suited for expensive discrete problems
Efficient Surrogate Model Generation
339 - Surrogate Optimization explained using simple python code
Johannes Wiebe: A robust approach to warped Gaussian process-constrained optimization
Black-Box Combinatorial Optimization with Monotone Structure
GECCO2021 - wksp119 - WS - SAEOpt - Black-box Mixed-Variable Optimisation Using a Surrogate [...]
Gaussian Process Based Surrogate Models
Dr. Andrew Duncan | Budget-Limited Parametric Estimation for Expensive Black Box Engineering Models
Extracting Decision Paths via Surrogate Modeling for Explainability of Black Box Classifiers
Surrogate-Assisted Multi-Objective Optimization with Constraints | Manuel Berkemeier | JuliaCon 2023
Carl Henrik Ek - Modulated surrogate models for Bayesian Optimization
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Last Updated: August 20, 2026
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