Defeng Sun  (孙德锋)
Defeng Sun (孙德锋)
Chair Professor of Applied Optimization and OR, The Hong Kong Polytechnic University
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Cited by
Cited by
Hankel matrix rank minimization with applications to system identification and realization
M Fazel, TK Pong, D Sun, P Tseng
SIAM Journal on Matrix Analysis and Applications 34 (3), 946-977, 2013
A new look at smoothing Newton methods for nonlinear complementarity problems and box constrained variational inequalities
L Qi, D Sun, G Zhou
Mathematical programming 87, 1-35, 2000
A Newton-CG augmented Lagrangian method for semidefinite programming
XY Zhao, D Sun, KC Toh
SIAM Journal on Optimization 20 (4), 1737-1765, 2010
Global and superlinear convergence of the smoothing Newton method and its application to general box constrained variational inequalities
X Chen, L Qi, D Sun
Mathematics of computation 67 (222), 519-540, 1998
A quadratically convergent Newton method for computing the nearest correlation matrix
H Qi, D Sun
SIAM journal on matrix analysis and applications 28 (2), 360-385, 2006
Convergence properties of nonlinear conjugate gradient methods
Y Dai, J Han, G Liu, D Sun, H Yin, Y Yuan
SIAM Journal on Optimization 10 (2), 345-358, 2000
Semismooth matrix-valued functions
D Sun, J Sun
Mathematics of Operations Research 27 (1), 150-169, 2002
SDPNAL: a majorized semismooth Newton-CG augmented Lagrangian method for semidefinite programming with nonnegative constraints
L Yang, D Sun, KC Toh
Mathematical Programming Computation 7 (3), 331-366, 2015
Complementarity functions and numerical experiments on some smoothing Newton methods for second-order-cone complementarity problems
XD Chen, D Sun, J Sun
Computational optimization and applications 25, 39-56, 2003
On NCP-functions
D Sun, L Qi
Computational Optimization and Applications 13, 201-220, 1999
The strong second-order sufficient condition and constraint nondegeneracy in nonlinear semidefinite programming and their implications
D Sun
Mathematics of Operations Research 31 (4), 761-776, 2006
A highly efficient semismooth Newton augmented Lagrangian method for solving Lasso problems
X Li, D Sun, KC Toh
SIAM Journal on Optimization 28 (1), 433-458, 2018
A class of iterative methods for solving nonlinear projection equations
D Sun
Journal of Optimization Theory and Applications 91, 123-140, 1996
A convergent 3-block semiproximal alternating direction method of multipliers for conic programming with 4-type constraints
D Sun, KC Toh, L Yang
SIAM journal on Optimization 25 (2), 882-915, 2015
Semismooth homeomorphisms and strong stability of semidefinite and Lorentz complementarity problems
JS Pang, D Sun, J Sun
Mathematics of Operations Research 28 (1), 39-63, 2003
The rate of convergence of the augmented Lagrangian method for nonlinear semidefinite programming
D Sun, J Sun, L Zhang
Mathematical Programming 114 (2), 349-391, 2008
L÷wner's operator and spectral functions in Euclidean Jordan algebras
D Sun, J Sun
Mathematics of Operations Research 33 (2), 421-445, 2008
An efficient inexact symmetric Gauss–Seidel based majorized ADMM for high-dimensional convex composite conic programming
L Chen, D Sun, KC Toh
Mathematical Programming 161, 237-270, 2017
A Schur complement based semi-proximal ADMM for convex quadratic conic programming and extensions
X Li, D Sun, KC Toh
Mathematical Programming 155 (1), 333-373, 2016
An implementable proximal point algorithmic framework for nuclear norm minimization
YJ Liu, D Sun, KC Toh
Mathematical programming 133, 399-436, 2012
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