6 citations · 6 across the 6 of their papers we have counts for
6 papers
Simultaneous Best Subset Selection and Dimension Reduction via Primal-Dual Iterations
Canhong Wen, Ruipeng Dong, Xueqin Wang +2
Sparse reduced rank regression is an essential statistical learning method. In the contemporary literature, estimation is typically formulated as a nonconvex optimization that ofte…
Stability Approach to Regularization Selection for Reduced-Rank Regression
Canhong Wen, Qin Wang, Yuan Jiang
The reduced-rank regression model is a popular model to deal with multivariate response and multiple predictors, and is widely used in biology, chemometrics, econometrics, engineer…
The Effects of Stringent Interventions for Coronavirus Pandemic
Ting Tian, Wenxiang Luo, Yukang Jiang +4
The pandemic of COVID-19 has caused severe public health consequences around the world. Many interventions of COVID-19 have been implemented. It is of great public health and socie…
Image denoising via K-SVD with primal-dual active set algorithm
Quan Xiao, Canhong Wen, Zirui Yan
K-SVD algorithm has been successfully applied to image denoising tasks dozens of years but the big bottleneck in speed and accuracy still needs attention to break. For the sparse c…
Best Subset Selection in Reduced Rank Regression
Canhong Wen, Weiyu Li, Junxian Zhu +1
We design a new algorithm on the best subset selection model in reduced rank regression.
BeSS: An R Package for Best Subset Selection in Linear, Logistic and CoxPH Models
Canhong Wen, Aijun Zhang, Shijie Quan +1
We introduce a new R package, BeSS, for solving the best subset selection problem in linear, logistic and Cox's proportional hazard (CoxPH) models. It utilizes a highly efficient a…