activity
20202025
most citedMultiple Imputation via Generative Adversarial Network for High-dimensional Blockwise Missing Value Problems

3 citations · 5 across the 7 of their papers we have counts for

collaborators

7 papers

cs.AI20252 cited

The Amazon Nova Family of Models: Technical Report and Model Card

Amazon AGI, Aaron Langford, Aayush Shah +783

We present Amazon Nova, a new generation of state-of-the-art foundation models that deliver frontier intelligence and industry-leading price performance. Amazon Nova Pro is a highl…

cs.LG2023

On the accuracy and efficiency of group-wise clipping in differentially private optimization

Zhiqi Bu, Ruixuan Liu, Yu-Xiang Wang +2

Recent advances have substantially improved the accuracy, memory cost, and training speed of differentially private (DP) deep learning, especially on large vision and language mode…

cs.LG2023

Coupling public and private gradient provably helps optimization

Ruixuan Liu, Zhiqi Bu, Yu-xiang Wang +2

The success of large neural networks is crucially determined by the availability of data. It has been observed that training only on a small amount of public data, or privately on…

stat.ME2023

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…

stat.ME2022

CEDAR: Communication Efficient Distributed Analysis for Regressions

Changgee Chang, Zhiqi Bu, Qi Long

Electronic health records (EHRs) offer great promises for advancing precision medicine and, at the same time, present significant analytical challenges. Particularly, it is often t…

cs.LG20213 cited

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…