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Author

Yunsoo Ha

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Conference

Unifying Trust-region Algorithms with Adaptive Sampling for Nonconvex Simulation Optimization

Continuous simulation optimization is challenging due to its derivative-free and often nonconvex noisy setting. Trust-region methods have proven remarkable robustness for this class of problems. Each iteration of a trust-region method involves constructing a local model via interpolation or regression within a neighbor...

S. Shashaani, Yunsoo Ha, Quoc Tran-Dinh · 0 citations
Open access Aug 2026

Adaptive sampling-based bi-fidelity stochastic trust region method for stochastic derivative-free optimization

This paper proposes ASTRO-BFDF, an adaptive sampling trust-region method specifically designed for unconstrained bi-fidelity stochastic derivative-free optimization problems and proves that the iterates generated by ASTRO-BFDF converge to a first-order stationary point almost surely.

Yunsoo Ha, Juliane Müller · 0 citations

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