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stat.ME2022
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…
stat.ME2022
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…
stat.ME2019
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.