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实体 Local Covariate Selection for Average Causal Effect Estimation without Pretreatment and Causal Sufficiency Assumptions

Local Covariate Selection for Average Causal Effect Estimation without Pretreatment and Causal Sufficiency Assumptions

PulseAugur coverage of Local Covariate Selection for Average Causal Effect Estimation without Pretreatment and Causal Sufficiency Assumptions — every cluster mentioning Local Covariate Selection for Average Causal Effect Estimation without Pretreatment and Causal Sufficiency Assumptions across labs, papers, and developer communities, ranked by signal.

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  1. RESEARCH · CL_43548 ·

    新方法放宽假设,简化因果效应估计

    研究人员开发了一种新的局部学习方法来选择因果效应估计中的协变量,无需预处理或因果充分性假设。该方法确定了一个局部边界,用于高效搜索有效的调整集,提高了计算效率。在合成数据和真实世界数据上的实验表明,该方法能够准确估计因果效应,并显著加快了速度。