论文标题
高维线性模型的$ C $ - 最佳实验的设计
Design of $c$-Optimal Experiments for High dimensional Linear Models
论文作者
论文摘要
我们研究了当可用的大量未标记数据但测量相应的响应昂贵时，我们研究了偏离套索估计量的渐近方差的随机设计。最佳采样分布作为半限定程序的解决方案。这些最佳设计产生的效率提高将通过仿真实验来证明。
We study random designs that minimize the asymptotic variance of a de-biased lasso estimator when a large pool of unlabeled data is available but measuring the corresponding responses is costly. The optimal sampling distribution arises as the solution of a semidefinite program. The improvements in efficiency that result from these optimal designs are demonstrated via simulation experiments.
