3 papers
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…
stat.ME2020
l1-norm quantile regression screening rule via the dual circumscribed sphere
Pan Shang, Lingchen Kong
l1-norm quantile regression is a common choice if there exists outlier or heavy-tailed error in high-dimensional data sets. However, it is computationally expensive to solve this p…