Optimal Causal Annotations: An Application to Casenotes in Social Services
批量自适应因果标注
机构 * UC Berkeley(加州大学伯克利分校) ; Fordham University(福特汉姆大学) ; University of Southern California(南加州大学)
AI总结 本文提出一种批量自适应方法,通过优化数据采样策略提高因果效应估计效率,减少标注成本,实验证明在缺失数据下能显著降低均方误差。
Comments Extended journal version. A preliminary version was accepted to AISTATS 2026