7 citations · 21 across the 11 of their papers we have counts for
24 papers · 1 filter
A Dimension Reduction Technique for Large-scale Structured Sparse Optimization Problems with Application to Convex Clustering
Yancheng Yuan, Tsung-Hui Chang, Defeng Sun +1
In this paper, we propose a novel adaptive sieving (AS) technique and an enhanced AS (EAS) technique, which are solver independent and could accelerate optimization algorithms for…
An Inexact Augmented Lagrangian Method for Second-order Cone Programming with Applications
Ling Liang, Defeng Sun, Kim-Chuan Toh
In this paper, we adopt the augmented Lagrangian method (ALM) to solve convex quadratic second-order cone programming problems (SOCPs). Fruitful results on the efficiency of the AL…
Adaptive Sieving with PPDNA: Generating Solution Paths of Exclusive Lasso Models
Meixia Lin, Yancheng Yuan, Defeng Sun +1
The exclusive lasso (also known as elitist lasso) regularization has become popular recently due to its superior performance on structured sparsity. Its complex nature poses diffic…
Estimation of sparse Gaussian graphical models with hidden clustering structure
Meixia Lin, Defeng Sun, Kim-Chuan Toh +1
Estimation of Gaussian graphical models is important in natural science when modeling the statistical relationships between variables in the form of a graph. The sparsity and clust…
Efficient algorithms for multivariate shape-constrained convex regression problems
Meixia Lin, Defeng Sun, Kim-Chuan Toh
Shape-constrained convex regression problem deals with fitting a convex function to the observed data, where additional constraints are imposed, such as component-wise monotonicity…
Mesh Independence of a Majorized ABCD Method for Sparse PDE-constrained Optimization Problems
Xiaoliang Song, Defeng Sun, Kim-Chuan Toh
A majorized accelerated block coordinate descent (mABCD) method in Hilbert space is analyzed to solve a sparse PDE-constrained optimization problem via its dual. The finite element…