ملف الباحث
Georgios Makrygiorgos
ورقة واحدة في مجموعة PaperMetrix
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Towards Scalable Bayesian Optimization via Gradient-Informed Bayesian Neural Networks
2025 · arXiv (Cornell University)
Bayesian optimization (BO) is a widely used method for data-driven optimization that generally relies on zeroth-order data of objective function to construct probabilistic surrogate models. These surrogates guide the exploration-exploitation process toward finding global optimum. …