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English(EN) Waiting Buys Exactly Two Moments: Endogenous Identification in Prediction-Driven Allocation

新论文分析预算和风险约束下的最优干预时机

作者 PulseAugur 编辑部 · [1 个来源] ·

这篇题为“等待恰好购买两个时刻：预测驱动分配中的内生识别”的论文，探讨了在固定预算和不确定风险情景下的最优干预时机。研究揭示了随着时间推移收集更多信息与干预机会减少（因为高风险个体离开）之间的权衡。研究结果表明，虽然更长的观察期可以消除时机上的模糊性，但最优干预日期可能已经过去。实验表明，bootstrap averaging 和 early stopping 可以改进决策，但 regret weighting 在 pooled mean squared regret 中并未带来额外的好处。 AI

影响 为预测驱动情景下的资源分配优化提供了理论框架，与做出顺序决策的AI系统相关。

排序理由 学术论文发表于arXiv [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 →

新论文分析预算和风险约束下的最优干预时机

本文如何被排名

Signal score
16 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
学术论文发表于arXiv [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
Breaking (< 6h)
Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

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) · Rama AlHamidi, Rasul Khanbayov, Erchin Serpedin, Hasan Kurban ·

    等待恰好购买两个时刻：预测驱动分配中的内生识别

    arXiv:2610.23830v1 Announce Type: new Abstract: A planner with a fixed budget of preventive help must decide whom to help and when. Waiting reveals risk but removes intervention opportunities as higher-risk individuals leave first. We characterize this tradeoff under repeated noi…

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