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English(EN) How Many Initial Points Does Bayesian Optimization Need?

研究发现贝叶斯优化需要最优初始点

作者 PulseAugur 编辑部 · [1 个来源] ·

一篇新的arXiv论文探讨了贝叶斯优化（BO）所需的最佳初始点数量。研究表明，寻找全局最优值的总成本与初始批次大小（$n_0$）之间存在U形关系，这意味着过少或过多的初始点都会导致资源浪费。这种现象归因于BO在向内聚焦之前倾向于探索超立方体的边界。该研究提出了实际建议，包括在可用时使用多步前瞻BO，在无法调整$n_0$时使用Thompson采样，以及在可以调整时使用更大的$n_0$。 AI

影响 为优化贝叶斯优化（机器学习模型调优的关键技术）的效率提供了指导。

排序理由 关于特定机器学习技术的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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研究发现贝叶斯优化需要最优初始点

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关于特定机器学习技术的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Mujin Cheon, James Odgers, Dong-Yeun Koh, Calvin Tsay ·

    贝叶斯优化需要多少初始点？

    arXiv:2607.04356v1 Announce Type: new Abstract: Bayesian Optimization (BO) generally begins with an initialization phase: a batch of $n_0$ uninformed evaluations. The choice of $n_0$ remains largely heuristic, and we empirically observe that the total cost (random initial points …

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