1 citations · 1 across the 5 of their papers we have counts for
5 papers
DROP: Distributionally Robust Optimization for Multi-task Learning in Graphical Models
Canruo Shen, Xintong Ji, Qiong Li +2
Gaussian Graphical Models (GGMs) are widely used to infer conditional dependence structures in high-dimensional data. However, standard precision matrix estimators are highly sensi…
Adaptive Kernel Regression for Constrained Route Alignment: Theory and Iterative Data Sharpening
Shiyin Du, Yiting Chen, Wenzhi Yang +2
Route alignment design in surveying and transportation engineering frequently involves fixed waypoint constraints, where a path must precisely traverse specific coordinates. While…
DEEPEAST technique to enhance power in two-sample tests via the same-attraction function
Yiting Chen, Min Gao, Wei Lin +3
Data depth has emerged as an invaluable nonparametric measure for the ranking of multivariate samples. The main contribution of depth-based two-sample comparisons is the introducti…
Q statistics in data depth: fundamental theory revisited and variants
Min Gao, Yiting Chen, Xiaoping Shi +1
Recently, data depth has been widely used to rank multivariate data. The study of the depth-based statistic, originally proposed by Liu and Singh (1993), has become increasingl…
Adaptive Penalized Likelihood method for Markov Chains
Yining Zhou, Ming Gao, Yiting Chen +1
Maximum Likelihood Estimation (MLE) and Likelihood Ratio Test (LRT) are widely used methods for estimating the transition probability matrix in Markov chains and identifying signif…