Kim-Chuan Toh
Kim-Chuan Toh
Professor of Mathematics, National University of Singapore
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Cited by
Cited by
SDPT3—a MATLAB software package for semidefinite programming, version 1.3
KC Toh, MJ Todd, RH Tütüncü
Optimization Methods and Software 11 (1-4), 545-581, 1999
Solving semidefinite-quadratic-linear programs using SDPT3
RH Tütüncü, KC Toh, MJ Todd
Mathematical programming 95 (2), 189-217, 2003
An accelerated proximal gradient algorithm for nuclear norm regularized linear least squares problems
KC Toh, S Yun
Pacific Journal of Optimization 6, 615--640, 2010
Semidefinite programming approaches for sensor network localization with noisy distance measurements
P Biswas, TC Liang, KC Toh, Y Ye, TC Wang
IEEE transactions on automation science and engineering 3 (4), 360-371, 2006
A Newton-CG augmented Lagrangian method for semidefinite programming
XY Zhao, D Sun, KC Toh
SIAM J. Optimization 20, 1737--1765, 2010
On the Nesterov--Todd direction in semidefinite programming
MJ Todd, KC Toh, RH Tütüncü
SIAM Journal on Optimization 8 (3), 769-796, 1998
On the implementation and usage of SDPT3–a Matlab software package for semidefinite-quadratic-linear programming, version 4.0
KC Toh, MJ Todd, RH Tütüncü
Handbook on Semidefinite, Conic and Polynomial Optimization, 715-754, 2012
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
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 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
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
An inexact interior point method for L 1-regularized sparse covariance selection
L Li, KC Toh
Mathematical Programming Computation 2, 291-315, 2010
From potential theory to matrix iterations in six steps
TA Driscoll, KC Toh, LN Trefethen
SIAM review, 547-578, 1998
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
3D chromosome modeling with semi-definite programming and Hi-C data
ZZ Zhang, G Li, KC Toh, WK Sung
Journal of computational biology 20 (11), 831-846, 2013
A distributed SDP approach for large-scale noisy anchor-free graph realization with applications to molecular conformation
P Biswas, KC Toh, Y Ye
SIAM Journal on Scientific Computing 30 (3), 1251--1277, 2008
Pseudozeros of polynomials and pseudospectra of companion matrices
KC Toh, LN Trefethen
Numerische Mathematik 68 (3), 403-425, 1994
Solving log-determinant optimization problems by a Newton-CG primal proximal point algorithm
C Wang, D Sun, KC Toh
SIAM Journal on Optimization 20 (6), 2994--3013, 2010
A coordinate gradient descent method for 1-regularized convex minimization
S Yun, KC Toh
Computational Optimization and Applications 48, 273-307, 2011
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