activity
20192022
most citedModelling EHR timeseries by restricting feature interaction

6 citations · 8 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG2022

Cost Effective MLaaS Federation: A Combinatorial Reinforcement Learning Approach

Shuzhao Xie, Yuan Xue, Yifei Zhu +1

With the advancement of deep learning techniques, major cloud providers and niche machine learning service providers start to offer their cloud-based machine learning tools, also k…

cs.LG20201 cited

Learning Unstable Dynamical Systems with Time-Weighted Logarithmic Loss

Kamil Nar, Yuan Xue, Andrew M. Dai

When training the parameters of a linear dynamical model, the gradient descent algorithm is likely to fail to converge if the squared-error loss is used as the training loss functi…

cs.LG20191 cited

Deep Physiological State Space Model for Clinical Forecasting

Yuan Xue, Denny Zhou, Nan Du +4

Clinical forecasting based on electronic medical records (EMR) can uncover the temporal correlations between patients' conditions and outcomes from sequences of longitudinal clinic…

cs.LG20196 cited

Modelling EHR timeseries by restricting feature interaction

Kun Zhang, Yuan Xue, Gerardo Flores +3

Time series data are prevalent in electronic health records, mostly in the form of physiological parameters such as vital signs and lab tests. The patterns of these values may be s…

cs.LG2019

Learning the Graphical Structure of Electronic Health Records with Graph Convolutional Transformer

Edward Choi, Zhen Xu, Yujia Li +4

Effective modeling of electronic health records (EHR) is rapidly becoming an important topic in both academia and industry. A recent study showed that using the graphical structure…