English(EN) Cost-aware Bayesian Optimization via the Pandora's Box Gittins Index

新的 Gittins 指数方法增强了成本感知贝叶斯优化

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-27 04:00

研究人员通过将经济学中的 Pandora's Box 问题联系起来，开发了一种新颖的成本感知贝叶斯优化方法。这种新方法利用 Gittins 指数（通常用于不确定性下的决策制定）作为获取函数。实证结果表明，这种基于 Gittins 指数的获取函数表现良好，尤其是在更高维度的情况下，并且即使没有明确的成本考虑，其优势也扩展到了标准的贝叶斯优化任务。 AI

影响这项研究可能通过优化超参数调整期间的资源分配，从而实现更高效的 AI 模型训练。

排序理由该集群包含一篇详细介绍贝叶斯优化新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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报道来源 [1]

arXiv stat.ML TIER_1 English(EN) · Qian Xie, Raul Astudillo, Peter I. Frazier, Ziv Scully, Alexander Terenin · 2026-10-27 04:00

通过 Pandora's Box Gittins 指数实现成本感知贝叶斯优化

arXiv:2406.20062v4 Announce Type: replace-cross Abstract: Bayesian optimization is a technique for efficiently optimizing unknown functions in a black-box manner. To handle practical settings where gathering data requires use of finite resources, it is desirable to explicitly inc…

本文如何被排名

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通过 Pandora's Box Gittins 指数实现成本感知贝叶斯优化

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