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A Decomposition-Based Data-Driven Branch-and-Bound Approach for Black-Box Global Optimization
Many scientific and engineering applications require the global optimization of expensive black-box functions. In high-dimensional settings, however, achieving computational scalability is a major challenge. To address this challenge, we propose a distributed spatial branch-and-bound framework that
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