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English(EN) Bayesian Fixed-Confidence Best-Arm Identification with Abstention

用于具有弃权选项的最优臂识别的新型贝叶斯算法

研究人员开发了一种名为Screen-and-Confirm (S&C) 的新算法,用于固定置信度贝叶斯最优臂识别问题。该方法允许学习者在满足目标错误概率和弃权预算的前提下,选择不做出最终推荐。文章分析了该算法的预期停止时间,并推导了最小预期停止时间。对于高斯先验和奖励,研究建立了匹配的上下界,并指出几乎并列的情况会显著影响采样成本。 AI

影响 引入了一种新的算法方法,用于在具有弃权能力的机器学习环境中优化决策。

排序理由 该集群包含一篇详细介绍机器学习新算法的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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

用于具有弃权选项的最优臂识别的新型贝叶斯算法

本文如何被排名

Signal score
4 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
该集群包含一篇详细介绍机器学习新算法的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
paper, other
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
Same-day
Cluster formed today. Ranking reflects the current source set at time of score.

完整方法见我们的编辑标准。

报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Yuqi Huang, Yunlong Hou, Vincent Y. F. Tan ·

    Bayesian Fixed-Confidence Best-Arm Identification with Abstention

    arXiv:2610.30384v1 Announce Type: new Abstract: We study the Bayesian fixed-confidence best-arm identification problem in which a learner can abstain from making a terminal recommendation. Subject to a target error probability $\delta$ and an abstention budget $\alpha$, we propos…