8 citations · 13 across the 5 of their papers we have counts for
5 papers
MISNN: Multiple Imputation via Semi-parametric Neural Networks
Zhiqi Bu, Zongyu Dai, Yiliang Zhang +1
Multiple imputation (MI) has been widely applied to missing value problems in biomedical, social and econometric research, in order to avoid improper inference in the downstream da…
Multiple Imputation with Neural Network Gaussian Process for High-dimensional Incomplete Data
Zongyu Dai, Zhiqi Bu, Qi Long
Missing data are ubiquitous in real world applications and, if not adequately handled, may lead to the loss of information and biased findings in downstream analysis. Particularly,…
Integrative Learning of Structured High-Dimensional Data from Multiple Datasets
Changgee Chang, Zongyu Dai, Jihwan Oh +1
Integrative learning of multiple datasets has the potential to mitigate the challenge of small and large that is often encountered in analysis of big biomedical data such a…
Multiple Imputation via Generative Adversarial Network for High-dimensional Blockwise Missing Value Problems
Zongyu Dai, Zhiqi Bu, Qi Long
Missing data are present in most real world problems and need careful handling to preserve the prediction accuracy and statistical consistency in the downstream analysis. As the go…
On the Convergence and Calibration of Deep Learning with Differential Privacy
Zhiqi Bu, Hua Wang, Zongyu Dai +1
Differentially private (DP) training preserves the data privacy usually at the cost of slower convergence (and thus lower accuracy), as well as more severe mis-calibration than its…