9 citations · 34 across the 17 of their papers we have counts for
4 papers · 1 filter
Learning the hub graphical Lasso model with the structured sparsity via an efficient algorithm
Chengjing Wang, Peipei Tang, Wenling He +1
Graphical models have exhibited their performance in numerous tasks ranging from biological analysis to recommender systems. However, graphical models with hub nodes are computatio…
A Highly Efficient Algorithm for Solving Exclusive Lasso Problems
Meixia Lin, Yancheng Yuan, Defeng Sun +1
The exclusive lasso (also known as elitist lasso) regularizer has become popular recently due to its superior performance on intra-group feature selection. Its complex nature poses…
Adaptive sieving: A dimension reduction technique for sparse optimization problems
Yancheng Yuan, Meixia Lin, Defeng Sun +1
In this paper, we propose an adaptive sieving (AS) strategy for solving general sparse machine learning models by effectively exploring the intrinsic sparsity of the solutions, whe…
A positive and moment-preserving Fourier spectral method
Zhenning Cai, Bo Lin, Meixia Lin
This paper presents a novel Fourier spectral method that utilizes optimization techniques to ensure the positivity and conservation of moments in the space of trigonometric polynom…