2 papers
stat.ME2026
High-dimensional semi-supervised learning: in search for optimal inference of the mean
Yuqian Zhang, Jelena Bradic
A fundamental challenge in semi-supervised learning lies in the observed data's disproportional size when compared with the size of the data collected with missing outcomes. An imp…
stat.ME2025
Semi-supervised linear regression: enhancing efficiency and robustness in high dimensions
Kai Chen, Yuqian Zhang
In semi-supervised learning, the prevailing understanding suggests that observing additional unlabeled samples improves estimation accuracy for linear parameters only in the case o…