2 papers
stat.ML2026
Efficient Group Lasso Regularized Rank Regression with Simulation-Based Tuning
Meixia Lin, Mengjiao Shi, Yunhai Xiao +1
High-dimensional regression often suffers from heavy-tailed noise and outliers, which can severely undermine the reliability of least-squares based methods. To improve robustness,…
stat.ME2025
An Efficient Dual ADMM for Huber Regression with Fused Lasso Penalty
Mengjiao Shi, Yunhai Xiao
The ordinary least squares estimate in linear regression is sensitive to the influence of errors with large variance, which reduces its robustness, especially when dealing with hea…