3 papers
stat.ME2024
Tuning parameter selection for the adaptive nuclear norm regularized trace regression
Pan Shang, Lingchen Kong, Yiting Ma
Regularized models have been applied in lots of areas, with high-dimensional data sets being popular. Because tuning parameter decides the theoretical performance and computational…
stat.CO2024
Safe Feature Identification Rule for Fused Lasso by An Extra Dual Variable
Pan Shang, Huangyue Chen, Lingchen Kong
Fused Lasso was proposed to characterize the sparsity of the coefficients and the sparsity of their successive differences for the linear regression. Due to its wide applications,…
stat.ME2024
Safe subspace screening for the adaptive nuclear norm regularized trace regression
Pan Shang, Lingchen Kong
Matrix form data sets arise in many areas, so there are lots of works about the matrix regression models. One special model of these models is the adaptive nuclear norm regularized…