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新的校准预测驱动推断方法增强了半监督估计

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员推出了一种名为校准预测驱动推断（CPPI）的新型半监督均值估计方法。CPPI通过在应用于半监督估计之前，对标记样本上的预测分数进行事后校准，从而增强了现有的增强逆概率加权（AIPW）等技术。此校准步骤可以是线性的或等渗的，旨在提高预测准确性和所得估计量的效率。在模拟和真实世界实验中，该方法与AIPW和其他预测驱动推断方法相比，表现出具有竞争力或更优的性能。 AI

排序理由 该集群包含一篇详细介绍新统计推断方法的论文。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.AI 阅读 →

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新的校准预测驱动推断方法增强了半监督估计

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该集群包含一篇详细介绍新统计推断方法的论文。[lever_c_demoted from research: ic=1 ai=0.7]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Lars van der Laan, Mark Van Der Laan ·

    Calibeating 预测驱动的推理

    arXiv:2604.21260v2 Announce Type: replace-cross Abstract: We study semisupervised mean estimation with a small labeled sample, a large unlabeled sample, and a black-box prediction model whose output may be miscalibrated. A standard approach in this setting is augmented inverse-pr…

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