Active Subsampling for Measurement-Constrained M-Estimation of Individualized Thresholds with High-Dimensional Data
高维数据下测量受限个体化阈值的主动子抽样M估计
Measurement-constrained problems frequently arise in modern applications such as electronic health record studies. In such problems, despite the availability of large datasets, collecting labeled data can be highly costly or time-consuming, allowing only a small portion of the data to be labeled within a given budget. This raises a critical question: which data points are most beneficial to label given the budget constraint? We study this question in the context of…