7 citations · 8 across the 2 of their papers we have counts for
2 papers
math.OC2017★ 7 cited
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…
math.OC2017★ 1 cited
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…