49 citations · 91 across the 9 of their papers we have counts for
9 papers
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…
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…
A semi-proximal augmented Lagrangian based decomposition method for primal block angular convex composite quadratic conic programming problems
Xin-Yee Lam, Defeng Sun, Kim-Chuan Toh
We propose a semi-proximal augmented Lagrangian based decomposition method for convex composite quadratic conic programming problems with primal block angular structures. Using our…
On the Asymptotic Superlinear Convergence of the Augmented Lagrangian Method for Semidefinite Programming with Multiple Solutions
Ying Cui, Defeng Sun, Kim-Chuan Toh
Solving large scale convex semidefinite programming (SDP) problems has long been a challenging task numerically. Fortunately, several powerful solvers including SDPNAL, SDPNAL+ and…
A Majorized ADMM with Indefinite Proximal Terms for Linearly Constrained Convex Composite Optimization
Min Li, Defeng Sun, Kim-Chuan Toh
This paper presents a majorized alternating direction method of multipliers (ADMM) with indefinite proximal terms for solving linearly constrained -block convex composite optimi…