5 citations · 5 across the 3 of their papers we have counts for
3 papers
stat.ML2024
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 …
stat.ML2024
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…
stat.ME2019★ 5 cited
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…