109 citations · 565 across the 64 of their papers we have counts for
8 papers · 1 filter
An efficient Hessian based algorithm for solving large-scale sparse group Lasso problems
Yangjing Zhang, Ning Zhang, Defeng Sun +1
The sparse group Lasso is a widely used statistical model which encourages the sparsity both on a group and within the group level. In this paper, we develop an efficient augmented…
SDPNAL+: A Matlab software for semidefinite programming with bound constraints (version 1.0)
Defeng Sun, Kim-Chuan Toh, Yancheng Yuan +1
SDPNAL+ is a {\sc Matlab} software package that implements an augmented Lagrangian based method to solve large scale semidefinite programming problems with bound constraints. The i…
On the R-superlinear convergence of the KKT residues generated by the augmented Lagrangian method for convex composite conic programming
Ying Cui, Defeng Sun, Kim-Chuan Toh
Due to the possible lack of primal-dual-type error bounds, the superlinear convergence for the Karush-Kuhn-Tucker (KKT) residues of the sequence generated by augmented Lagrangian m…
On efficiently solving the subproblems of a level-set method for fused lasso problems
Xudong Li, Defeng Sun, Kim-Chuan Toh
In applying the level-set method developed in [Van den Berg and Friedlander, SIAM J. on Scientific Computing, 31 (2008), pp.~890--912 and SIAM J. on Optimization, 21 (2011), pp.~12…
A multi-stage convex relaxation approach to noisy structured low-rank matrix recovery
Shujun Bi, Shaohua Pan, Defeng Sun
This paper concerns with a noisy structured low-rank matrix recovery problem which can be modeled as a structured rank minimization problem. We reformulate this problem as a mathem…
A block symmetric Gauss-Seidel decomposition theorem for convex composite quadratic programming and its applications
Xudong Li, Defeng Sun, Kim-Chuan Toh
For a symmetric positive semidefinite linear system of equations , where is partitioned into blocks, with …
A complete characterization on the robust isolated calmness of the nuclear norm regularized convex optimization problems
Ying Cui, Defeng Sun
In this paper, we provide a complete characterization on the robust isolated calmness of the Karush-Kuhn-Tucker (KKT) solution mapping for convex constrained optimization problems…
On the efficient computation of a generalized Jacobian of the projector over the Birkhoff polytope
Xudong Li, Defeng Sun, Kim-Chuan Toh
We derive an explicit formula, as well as an efficient procedure, for constructing a generalized Jacobian for the projector of a given square matrix onto the Birkhoff polytope, i.e…