156 citations · 441 across the 39 of their papers we have counts for
5 papers · 1 filter
Unsupervised Pseudo-Labeling for Extractive Summarization on Electronic Health Records
Xiangan Liu, Keyang Xu, Pengtao Xie +1
Extractive summarization is very useful for physicians to better manage and digest Electronic Health Records (EHRs). However, the training of a supervised model requires disease-sp…
Stackelberg GAN: Towards Provable Minimax Equilibrium via Multi-Generator Architectures
Hongyang Zhang, Susu Xu, Jiantao Jiao +3
We study the problem of alleviating the instability issue in the GAN training procedure via new architecture design. The discrepancy between the minimax and maximin objective value…
Multimodal Machine Learning for Automated ICD Coding
Keyang Xu, Mike Lam, Jingzhi Pang +9
This study presents a multimodal machine learning model to predict ICD-10 diagnostic codes. We developed separate machine learning models that can handle data from different modali…
Missing Value Imputation Based on Deep Generative Models
Hongbao Zhang, Pengtao Xie, Eric Xing
Missing values widely exist in many real-world datasets, which hinders the performing of advanced data analytics. Properly filling these missing values is crucial but challenging,…
Orthogonality-Promoting Distance Metric Learning: Convex Relaxation and Theoretical Analysis
Pengtao Xie, Wei Wu, Yichen Zhu +1
Distance metric learning (DML), which learns a distance metric from labeled "similar" and "dissimilar" data pairs, is widely utilized. Recently, several works investigate orthogona…