33 citations · 33 across the 1 of their papers we have counts for
4 papers
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…
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…
Adaptive Split Balancing for Optimal Random Forest
Yuqian Zhang, Weijie Ji, Jelena Bradic
In this paper, we propose a new random forest algorithm that constructs the trees using a novel adaptive split-balancing method. Rather than relying on the widely-used random featu…
Causal inference through multi-stage learning and doubly robust deep neural networks
Yuqian Zhang, Jelena Bradic
Deep neural networks (DNNs) have demonstrated remarkable empirical performance in large-scale supervised learning problems, particularly in scenarios where both the sample size …