English(EN) Fixed Budget is No Harder Than Fixed Confidence in Best-Arm Identification up to Logarithmic Factors

新算法表明固定预算的AI问题难度不高于固定置信度

作者 PulseAugur 编辑部 · [1 个来源] · 2026-06-02 04:00

研究人员证明，在最佳臂识别问题中，固定预算设置的难度不高于固定置信度设置，最多相差对数因子。他们开发了一种名为FC2FB的元算法，可以将固定置信度算法转换为固定预算算法。通过利用现有的最先进的固定置信度算法，这种新方法可以提高各种固定预算问题的样本复杂度。 AI

影响这项研究可能为涉及机器学习中顺序决策和探索的问题带来更高效的算法。

排序理由这是一篇发表在arXiv上的研究论文，详细介绍了一种用于机器学习问题的新算法。[lever_c_demoted from research: ic=1 ai=1.0]

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

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arXiv stat.ML TIER_1 English(EN) · Kapilan Balagopalan, Yinan Li, Yao Zhao, Tuan Nguyen, Anton Daitche, Houssam Nassif, Kwang-Sung Jun · 2026-06-02 04:00

固定预算在最优臂识别中的难度不亚于固定置信度，误差可达对数因子

arXiv:2602.03972v3 Announce Type: replace Abstract: The best-arm identification (BAI) problem is one of the most fundamental problems in interactive machine learning, which has two flavors: the fixed-budget setting (FB) and the fixed-confidence setting (FC). For $K$-armed bandits…