6 citations · 12 across the 4 of their papers we have counts for
4 papers · 1 filter
Semi-Supervised Quantile Estimation: Robust and Efficient Inference in High Dimensional Settings
Abhishek Chakrabortty, Guorong Dai, Raymond J. Carroll
We consider quantile estimation in a semi-supervised setting, characterized by two available data sets: (i) a small or moderate sized labeled data set containing observations for a…
A General Framework for Treatment Effect Estimation in Semi-Supervised and High Dimensional Settings
Abhishek Chakrabortty, Guorong Dai
In this article, we aim to provide a general and complete understanding of semi-supervised (SS) causal inference for treatment effects. Specifically, we consider two such estimands…
Penalized regression with multiple loss functions and selection by vote
Guorong Dai, Ursula U. Müller
This article considers a linear model in a high dimensional data scenario. We propose a process which uses multiple loss functions both to select relevant predictors and to estimat…
Data integration in high dimension with multiple quantiles
Guorong Dai, Ursula U. Müller, Raymond J. Carroll
This article deals with the analysis of high dimensional data that come from multiple sources (experiments) and thus have different possibly correlated responses, but share the sam…