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English(EN) Conformal Individual Treatment Effect Estimation under Networked Interference

新方法改进网络化干扰下的处理效应估计

研究人员开发了一种名为干扰调整加权共形预测的新方法,以解决在单位相互影响时估计个体处理效应的挑战。该技术为反事实结果提供了有限样本边际覆盖保证,即使在违反无干扰假设的情况下也是如此。数值实验表明,所提出的方法能够维持名义覆盖率,而现有方法在这种情况下可能会失败。 AI

影响 为复杂系统中的因果推理引入了新的统计框架,有可能提高AI模型的可解释性和决策能力。

排序理由 关于一种新颖统计方法的学术论文。[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 →

新方法改进网络化干扰下的处理效应估计

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关于一种新颖统计方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Matteo Zecchin, Osvaldo Simeone ·

    网络化干扰下的共形个体处理效应估计

    arXiv:2609.15254v1 Announce Type: cross Abstract: Conformal counterfactual prediction constructs prediction sets with finite-sample coverage guarantees for counterfactual outcomes and individual treatment effects under the no-interference assumption. In this work, we relax this a…