49 citations · 82 across the 14 of their papers we have counts for
6 papers · 1 filter
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…
A Schur Complement Based Semi-Proximal ADMM for Convex Quadratic Conic Programming and Extensions
Xudong Li, Defeng Sun, Kim-Chuan Toh
This paper is devoted to the design of an efficient and convergent {semi-proximal} alternating direction method of multipliers (ADMM) for finding a solution of low to medium accura…
SDPNAL: A Majorized Semismooth Newton-CG Augmented Lagrangian Method for Semidefinite Programming with Nonnegative Constraints
Liuqin Yang, Defeng Sun, Kim-Chuan Toh
In this paper, we present a majorized semismooth Newton-CG augmented Lagrangian method, called SDPNAL, for semidefinite programming (SDP) with partial or full nonnegative constr…
A Convergent 3-Block Semi-Proximal Alternating Direction Method of Multipliers for Conic Programming with -Type of Constraints
Defeng Sun, Kim-Chuan Toh, Liuqin Yang
The objective of this paper is to design an efficient and convergent alternating direction method of multipliers (ADMM) for finding a solution of medium accuracy to conic programmi…