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math.OC2025
On the B-subdifferential of proximal operators of affine-constrained regularizer
Xudong Li, Meixia Lin, Kim-Chuan Toh
In this work, we study the affine-constrained regularizers, which frequently arise in statistical and machine learning problems across a variety of applications, including…
stat.ML2025
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,…
math.OC2025
Inexact Accelerated Proximal Gradient Method Revisit: An Economical Variant via Shadow Points
Lei Yang, Meixia Lin
We consider the problem of optimizing the sum of a smooth convex function and a non-smooth convex function via the inexact accelerated proximal gradient (APG) method. A key limitat…