136 citations · 223 across the 8 of their papers we have counts for
8 papers
Recent Advances in Text Analysis
Zheng Tracy Ke, Pengsheng Ji, Jiashun Jin +1
Text analysis is an interesting research area in data science and has various applications, such as in artificial intelligence, biomedical research, and engineering. We review popu…
Co-citation and Co-authorship Networks of Statisticians
Pengsheng Ji, Jiashun Jin, Zheng Tracy Ke +1
We collected and cleaned a large data set on publications in statistics. The data set consists of the coauthor relationships and citation relationships of 83, 331 papers published…
Co-embedding of Nodes and Edges with Graph Neural Networks
Xiaodong Jiang, Ronghang Zhu, Pengsheng Ji +1
Graph, as an important data representation, is ubiquitous in many real world applications ranging from social network analysis to biology. How to correctly and effectively learn an…
Spectral Algorithms for Community Detection in Directed Networks
Zhe Wang, Yingbin Liang, Pengsheng Ji
Community detection in large social networks is affected by degree heterogeneity of nodes. The D-SCORE algorithm for directed networks was introduced to reduce this effect by takin…
Coauthorship and Citation Networks for Statisticians
Pengsheng Ji, Jiashun Jin
We have collected and cleaned two network data sets: Coauthorship and Citation networks for statisticians. The data sets are based on all research papers published in four of the t…
Rate optimal multiple testing procedure in high-dimensional regression
Pengsheng Ji, Zhigen Zhao
In the high dimensional regression analysis when the number of predictors is much larger than the sample size, an important question is to select the important variable which are r…
Sharp adaptive nonparametric testing for Sobolev ellipsoids
Pengsheng Ji, Michael Nussbaum
We consider testing for presence of a signal in Gaussian white noise with intensity 1/sqrt(n), when the alternatives are given by smoothness ellipsoids with an L2-ball of (squared)…
UPS delivers optimal phase diagram in high-dimensional variable selection
Pengsheng Ji, Jiashun Jin
Consider a linear model , . Here, , where both and are large, but . We model the rows of as i.i.d. samples from $N(0,\frac{1}{n}…