13 citations · 27 across the 7 of their papers we have counts for
7 papers
An optimal transport approach for selecting a representative subsample with application in efficient kernel density estimation
Jingyi Zhang, Cheng Meng, Jun Yu +3
Subsampling methods aim to select a subsample as a surrogate for the observed sample. Such methods have been used pervasively in large-scale data analytics, active learning, and pr…
Oversampling Divide-and-conquer for Response-skewed Kernel Ridge Regression
Jingyi Zhang, Xiaoxiao Sun
The divide-and-conquer method has been widely used for estimating large-scale kernel ridge regression estimates. Unfortunately, when the response variable is highly skewed, the div…
Large-scale optimal transport map estimation using projection pursuit
Cheng Meng, Yuan Ke, Jingyi Zhang +3
This paper studies the estimation of large-scale optimal transport maps (OTM), which is a well-known challenging problem owing to the curse of dimensionality. Existing literature a…
Ensemble machine learning approach for screening of coronary heart disease based on echocardiography and risk factors
Jingyi Zhang, Huolan Zhu, Yongkai Chen +5
Background: Extensive clinical evidence suggests that a preventive screening of coronary heart disease (CHD) at an earlier stage can greatly reduce the mortality rate. We use 64 tw…
Sufficient dimension reduction for classification using principal optimal transport direction
Cheng Meng, Jun Yu, Jingyi Zhang +2
Sufficient dimension reduction is used pervasively as a supervised dimension reduction approach. Most existing sufficient dimension reduction methods are developed for data with a…
A Review on Modern Computational Optimal Transport Methods with Applications in Biomedical Research
Jingyi Zhang, Wenxuan Zhong, Ping Ma
Optimal transport has been one of the most exciting subjects in mathematics, starting from the 18th century. As a powerful tool to transport between two probability measures, optim…
More efficient approximation of smoothing splines via space-filling basis selection
Cheng Meng, Xinlian Zhang, Jingyi Zhang +2
We consider the problem of approximating smoothing spline estimators in a nonparametric regression model. When applied to a sample of size , the smoothing spline estimator can b…