Kim-Chuan Toh

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Kim-Chuan Toh is affiliated with the following schools: National University of Singapore, Cornell University

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Kim-Chuan Toh

Mathematics

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#6573

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Measure Theory

#2050

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#2484

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Mathematics

Why Is Kim-Chuan Toh Influential?

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According to Wikipedia, Kim-Chuan Toh is a Singaporean mathematician, and Leo Tan Professor in Science at the National University of Singapore . He is known for his contributions to the theory, practice, and application of convex optimization, especially semidefinite programming and conic programming.

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Kim-Chuan Toh's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

SDPT3 -- A Matlab Software Package for Semidefinite Programming (1996) (1957)
Solving semidefinite-quadratic-linear programs using SDPT3 (2003) (1244)
An accelerated proximal gradient algorithm for nuclear norm regularized linear least squares problems (2009) (941)
Semidefinite Programming Approaches for Sensor Network Localization With Noisy Distance Measurements (2006) (470)
An accelerated proximal gradient algorithm for nuclear norm regularized least squares problems (2009) (388)
A Newton-CG Augmented Lagrangian Method for Semidefinite Programming (2010) (377)
On the Nesterov-Todd Direction in Semidefinite Programming (1998) (319)
SDPT3 — a Matlab software package for semidefinite-quadratic-linear programming, version 3.0 (2001) (245)
On the Implementation and Usage of SDPT3 – A Matlab Software Package for Semidefinite-Quadratic-Linear Programming, Version 4.0 (2012) (239)
SDPNAL$$+$$+: a majorized semismooth Newton-CG augmented Lagrangian method for semidefinite programming with nonnegative constraints (2014) (185)
A Convergent 3-Block SemiProximal Alternating Direction Method of Multipliers for Conic Programming with 4-Type Constraints (2014) (154)
SIAM Journal on Optimization (2012) (152)
A Schur complement based semi-proximal ADMM for convex quadratic conic programming and extensions (2014) (138)
An efficient inexact symmetric Gauss–Seidel based majorized ADMM for high-dimensional convex composite conic programming (2015) (138)
An implementable proximal point algorithmic framework for nuclear norm minimization (2012) (136)
Pseudozeros of polynomials and pseudospectra of companion matrices (1994) (123)
An inexact interior point method for L1-regularized sparse covariance selection (2010) (122)
From Potential Theory to Matrix Iterations in Six Steps (1998) (120)
A coordinate gradient descent method for ℓ1-regularized convex minimization (2011) (117)
A Highly Efficient Semismooth Newton Augmented Lagrangian Method for Solving Lasso Problems (2016) (117)
3D Chromosome Modeling with Semi-Definite Programming and Hi-C Data (2013) (113)
An inexact primal–dual path following algorithm for convex quadratic SDP (2007) (111)
Solving Log-Determinant Optimization Problems by a Newton-CG Primal Proximal Point Algorithm (2010) (110)
An Inexact Accelerated Proximal Gradient Method for Large Scale Linearly Constrained Convex SDP (2012) (108)
A Distributed SDP Approach for Large-Scale Noisy Anchor-Free Graph Realization with Applications to Molecular Conformation (2008) (107)
A Convergent 3-Block Semi-Proximal ADMM for Convex Minimization Problems with One Strongly Convex Block (2014) (98)
Calculation of Pseudospectra by the Arnoldi Iteration (1996) (91)
An Accelerated Proximal Gradient Algorithm for Frame-Based Image Restoration via the Balanced Approach (2011) (89)
A bounded degree SOS hierarchy for polynomial optimization (2015) (88)
Superlinear Convergence of a Newton-Type Algorithm for Monotone Equations (2005) (88)
A Majorized ADMM with Indefinite Proximal Terms for Linearly Constrained Convex Composite Optimization (2014) (87)
Solving Large Scale Semidefinite Programs via an Iterative Solver on the Augmented Systems (2003) (80)
An introduction to a class of matrix cone programming (2014) (80)
Sparse-BSOS: a bounded degree SOS hierarchy for large scale polynomial optimization with sparsity (2016) (79)
Inexact primal-dual path-following algorithms for a special class of convex quadratic SDP and related problems (2005) (74)
A Lagrangian–DNN relaxation: a fast method for computing tight lower bounds for a class of quadratic optimization problems (2016) (67)
An efficient diagonal preconditioner for finite element solution of Biot's consolidation equations (2002) (64)
QSDPNAL: a two-phase augmented Lagrangian method for convex quadratic semidefinite programming (2015) (63)
Solving Some Large Scale Semidefinite Programs via the Conjugate Residual Method (2002) (62)
A note on the convergence of ADMM for linearly constrained convex optimization problems (2015) (62)
SDPNAL+: A Matlab software for semidefinite programming with bound constraints (version 1.0) (2017) (56)
Block preconditioners for symmetric indefinite linear systems (2004) (53)
Image Restoration with Mixed or Unknown Noises (2014) (52)
Efficient Algorithms for the Smallest Enclosing Ball Problem (2005) (51)
An SDP-Based Divide-and-Conquer Algorithm for Large-Scale Noisy Anchor-Free Graph Realization (2009) (48)
Question classification for e-learning by artificial neural network (2003) (47)
An efficient Hessian based algorithm for solving large-scale sparse group Lasso problems (2017) (47)
Axisymmetric Lower-Bound Limit Analysis Using Finite Elements and Second-Order Cone Programming (2014) (47)
The Chebyshev Polynomials of a Matrix (1999) (45)
On the implementation of SDPT3 (version 3.1) - a MATLAB software package for semidefinite-quadratic-linear programming (2004) (45)
On the convergence properties of a majorized ADMM for linearly constrained convex optimization problems with coupled objective functions (2015) (43)
A block symmetric Gauss–Seidel decomposition theorem for convex composite quadratic programming and its applications (2017) (42)
A modified SSOR preconditioner for sparse symmetric indefinite linear systems of equations (2006) (42)
Preconditioning and iterative solution of symmetric indefinite linear systems arising from interior point methods for linear programming (2007) (42)
Convex Clustering: Model, Theoretical Guarantee and Efficient Algorithm (2018) (41)
Lower-Bound Limit Analysis of Seismic Passive Earth Pressure on Rigid Walls (2014) (40)
Primal-Dual Path-Following Algorithms for Determinant Maximization Problems With Linear Matrix Inequalities (1999) (40)
On the Moreau-Yosida Regularization of the Vector k-Norm Related Functions (2014) (40)
Inference of Spatial Organizations of Chromosomes Using Semi-definite Embedding Approach and Hi-C Data (2013) (39)
The Kreiss Matrix Theorem on a General Complex Domain (1999) (38)
Effect of footing width on Nγ and failure envelope of eccentrically and obliquely loaded strip footings on sand (2015) (38)
GMRES vs. Ideal GMRES (1997) (37)
On the Convergence Properties of a Majorized Alternating Direction Method of Multipliers for Linearly Constrained Convex Optimization Problems with Coupled Objective Functions (2016) (37)
On the equivalence of inexact proximal ALM and ADMM for a class of convex composite programming (2018) (36)
On the R-superlinear convergence of the KKT residuals generated by the augmented Lagrangian method for convex composite conic programming (2017) (35)
A Proximal Point Algorithm for Log-Determinant Optimization with Group Lasso Regularization (2013) (34)
Behavioral measures and their correlation with IPM iteration counts on semi-definite programming problems (2007) (32)
An Efficient Inexact ABCD Method for Least Squares Semidefinite Programming (2015) (31)
On the efficient computation of a generalized Jacobian of the projector over the Birkhoff polytope (2017) (31)
Polynomiality of an inexact infeasible interior point algorithm for semidefinite programming (2004) (31)
A partial proximal point algorithm for nuclear norm regularized matrix least squares problems (2014) (30)
Fast Algorithms for Large-Scale Generalized Distance Weighted Discrimination (2016) (30)
A Note on the Calculation of Step-Lengths in Interior-Point Methods for Semidefinite Programming (1999) (29)
Max-norm optimization for robust matrix recovery (2016) (29)
A Fast Globally Linearly Convergent Algorithm for the Computation of Wasserstein Barycenters (2018) (28)
An Analytic Center Cutting Plane Method for Semidefinite Feasibility Problems (2002) (27)
On Efficiently Solving the Subproblems of a Level-Set Method for Fused Lasso Problems (2017) (27)
Some New Search Directions for Primal-Dual Interior Point Methods in Semidefinite Programming (2000) (26)
A block coordinate gradient descent method for regularized convex separable optimization and covariance selection (2011) (25)
On the Asymptotic Superlinear Convergence of the Augmented Lagrangian Method for Semidefinite Programming with Multiple Solutions (2016) (24)
B-475 Lagrangian-Conic Relaxations, Part I: A Unified Framework and Its Applications to Quadratic Optimization Problems (2014) (24)
A Convergent Proximal Alternating Direction Method of Multipliers for Conic Programming with 4-Block Constraints (2014) (24)
A Unified Formulation and Fast Accelerated Proximal Gradient Method for Classification (2017) (23)
An Asymptotically Superlinearly Convergent Semismooth Newton Augmented Lagrangian Method for Linear Programming (2019) (22)
Spectral operators of matrices (2014) (21)
Using a Distributed SDP Approach to Solve Simulated Protein Molecular Conformation Problems (2013) (21)
An Efficient Semismooth Newton Based Algorithm for Convex Clustering (2018) (21)
A Multiple-Cut Analytic Center Cutting Plane Method for Semidefinite Feasibility Problems (2002) (21)
A Probabilistic Model for Minmax Regret in Combinatorial Optimization (2014) (20)
Fast iterative solution of large undrained soil‐structure interaction problems (2003) (20)
Practical Matrix Completion and Corruption Recovery Using Proximal Alternating Robust Subspace Minimization (2013) (19)
Simultaneous Clustering and Model Selection: Algorithm, Theory and Applications (2018) (18)
Solving the OSCAR and SLOPE Models Using a Semismooth Newton-Based Augmented Lagrangian Method (2018) (18)
Solving Nuclear Norm Regularized and Semidefinite Matrix Least Squares Problems with Linear Equality Constraints (2013) (18)
Computing the Sobolev Regularity of Refinable Functions by the Arnoldi Method (2001) (17)
Efficient Sparse Semismooth Newton Methods for the Clustered Lasso Problem (2018) (17)
A semismooth Newton-CG based dual PPA for matrix spectral norm approximation problems (2016) (17)
Semi-definite programming relaxation of quadratic assignment problems based on nonredundant matrix splitting (2015) (16)
Comparison between iterative solution of symmetric and non‐symmetric forms of Biot's FEM equations using the generalized Jacobi preconditioner (2008) (14)
A polynomial-time inexact interior-point method for convex quadratic symmetric cone programming (2010) (14)
A robust Lagrangian-DNN method for a class of quadratic optimization problems (2017) (14)
B-355 a Note on the Calculation of Step-lengths in Interior-point Methods for Semideenite Programming (1999) (13)
Matrix Approximation Problems and Nonsymmetric Iterative Methods (1996) (12)
A polynomial-time inexact primal-dual infeasible path-following algorithm for convex quadratic SDP (2008) (12)
Analytic Center Cutting-Plane Method with Deep Cuts for Semidefinite Feasibility Problems (2004) (11)
Partitioned versus global Krylov subspace iterative methods for FE solution of 3-D Biot's problem (2007) (10)
QSDPNAL : A two-phase Newton-CG proximal augmented Lagrangian method for convex quadratic semidefinite programming problems (2015) (10)
Solving Second Order Cone Programming via a Reduced Augmented System Approach (2006) (10)
An inexact projected gradient method with rounding and lifting by nonlinear programming for solving rank-one semidefinite relaxation of polynomial optimization (2021) (10)
A Newton-bracketing method for a simple conic optimization problem (2019) (9)
A sparse semismooth Newton based proximal majorization-minimization algorithm for nonconvex square-root-loss regression problems (2019) (8)
Simultaneous Clustering and Model Selection for Tensor Affinities (2016) (8)
Spectral Operators of Matrices: Semismoothness and Characterizations of the Generalized Jacobian (2018) (8)
Block constrained versus generalized Jacobi preconditioners for iterative solution of large-scale Biot’s FEM equations (2004) (8)
User guide for QSDP-0 – a Matlab software package for convex quadratic semidefinite programming (2010) (8)
A Semismooth Newton-CG Dual Proximal Point Algorithm for Matrix Spectral Norm Approximation Problems (2012) (8)
Efficient algorithms for multivariate shape-constrained convex regression problems (2020) (7)
A Penalized Quadratic Convex Reformulation Method for Random Quadratic Unconstrained Binary Optimization (2013) (7)
Performance of Zero-Level Fill-In Preconditioning Techniques for Iterative Solutions with Geotechnical Applications (2012) (7)
Equivalences and differences in conic relaxations of combinatorial quadratic optimization problems (2017) (6)
Doubly nonnegative relaxations are equivalent to completely positive reformulations of quadratic optimization problems with block-clique graph structures (2019) (6)
ACCELERATED PROXIMAL GRADIENT ALGORITHM FOR FRAME BASED IMAGE RESTORATIONS (2010) (6)
Learning Graph Laplacian with MCP (2020) (6)
A Unified Algorithmic Framework of Symmetric Gauss-Seidel Decomposition Based Proximal Admms for Convex Composite Programming (2018) (5)
The Impact of Applications on Mathematics (2014) (5)
An augmented Lagrangian method with constraint generation for shape-constrained convex regression problems (2020) (5)
Bregman Proximal Point Algorithm Revisited: A New Inexact Version and its Variant (2021) (5)
A Geometrical Analysis on Convex Conic Reformulations of Quadratic and Polynomial Optimization Problems (2020) (5)
A Proximal Point Algorithm for Sequential Feature Extraction Applications (2011) (5)
Solving graph equipartition SDPs on an algebraic variety (2021) (5)
Algorithm 996 (2018) (5)
Computing the Best Approximation over the Intersection of a Polyhedral Set and the Doubly Nonnegative Cone (2018) (4)
Doubly nonnegative relaxations for quadratic and polynomial optimization problems with binary and box constraints (2020) (4)
Effective block diagonal preconditioners for Biot's consolidation equations in piled‐raft foundations (2013) (4)
LAGRANGIAN-CONIC RELAXATIONS, PART II: APPLICATIONS TO POLYNOMIAL OPTIMIZATION PROBLEMS (2020) (4)
A Constraint Dissolving Approach for Nonsmooth Optimization over the Stiefel Manifold (2022) (4)
DC algorithms for a class of sparse group $\ell_0$ regularized optimization problems (2021) (4)
An Improved Unconstrained Approach for Bilevel Optimization (2022) (4)
Classification for E-learning by Artificial Neural Network (2003) (4)
An efficient implementable inexact entropic proximal point algorithm for a class of linear programming problems (2020) (4)
Matrix Iterations: The Six Gaps Between Potential Theory and Convergence (1996) (4)
Inexact Block Diagonal Preconditioners to Mitigate the Effects of Relative Differences in Material Stiffnesses (2013) (4)
On the implementation of a log-barrier progressive hedging method for multistage stochastic programs (2010) (3)
An efficient linearly convergent semismooth Netwon-CG augmented Lagrangian method for Lasso problems (2016) (3)
A Geometrical Analysis of a Class of Nonconvex Conic Programs for Convex Conic Reformulations of Quadratic and Polynomial Optimization Problems (2019) (3)
Semi-definite Relaxation of Quadratic Assignment Problems based on Nonredundant Matrix Splitting (2011) (3)
Solving Challenging Large Scale QAPs (2021) (3)
A Lagrangian–DNN relaxation: a fast method for computing tight lower bounds for a class of quadratic optimization problems (2015) (3)
Globally and Quadratically Convergent Algorithm for Minimizing the Sum of Euclidean Norms (2003) (3)
Constraint Dissolving Approaches for Riemannian Optimization (2022) (3)
Convergence Analysis of an Infeasible Interior Point Algorithm Based on a Regularized Central Path for Linear Complementarity Problems (2004) (3)
A Proximal Point Dual Newton Algorithm for Solving Group Graphical Lasso Problems (2019) (2)
A dual Newton based preconditioned proximal point algorithm for exclusive lasso models (2019) (2)
STRIDE along Spectrahedral Vertices for Solving Large-Scale Rank-One Semidefinite Relaxations (2021) (2)
A generalised Jacobi preconditioner for finite element solution of large-scale consolidation problems (2003) (2)
A Feasible Method for Solving an SDP Relaxation of the Quadratic Knapsack Problem (2023) (2)
A New Homotopy Proximal Variable-Metric Framework for Composite Convex Minimization (2018) (2)
On implementation of a Lagrangian dual method forsolving multi-stage stochastic programming problems (2000) (2)
User manual of NewtBracket: “A Newton-Bracketing method for a simple conic optimization problem” [10] with applications to QOPs in binary variables (2020) (2)
Preconditioned IDR(s) iterative solver for non‐symmetric linear system associated with FEM analysis of shallow foundation (2013) (2)
Computation of condition numbers for linear programming problems using Peña’s method (2006) (2)
Difference-of-Convex Algorithms for a Class of Sparse Group $\ell_0$ Regularized Optimization Problems (2022) (2)
Vaccine Appointment Scheduling: The Second Dose Challenge (2021) (2)
An Efficient Linearly Convergent Regularized Proximal Point Algorithm for Fused Multiple Graphical Lasso Problems (2019) (2)
An Inexact Augmented Lagrangian Method for Second-Order Cone Programming with Applications (2020) (2)
On Regularized Square-root Regression Problems: Distributionally Robust Interpretation and Fast Computations (2021) (2)
Adaptive Sieving with PPDNA: Generating Solution Paths of Exclusive Lasso Models (2020) (2)
Best Nonnegative Rank-One Approximations of Tensors (2018) (1)
On Efficient and Scalable Computation of the Nonparametric Maximum Likelihood Estimator in Mixture Models (2022) (1)
Accelerating nuclear-norm regularized low-rank matrix optimization through Burer-Monteiro decomposition (2022) (1)
Subspace quadratic regularization method for group sparse multinomial logistic regression (2021) (1)
An inexact Bregman proximal gradient method and its inertial variant (2021) (1)
A Dimension Reduction Technique for Large-Scale Structured Sparse Optimization Problems with Application to Convex Clustering (2021) (1)
PRIMAL-DUAL PATH-FOLLOWING ALGORITHMS FOR A SPECIAL CLASS OF CONVEX QUADRATIC SDP AND RELATED PROBLEMS (2005) (1)
Efficient sparse Hessian based algorithms for the clustered lasso problem (2018) (1)
The impact of applications on mathematics : proceedings of the Forum of Mathematics for Industry 2013 (2014) (1)
Semi-proximal Augmented Lagrangian-Based Decomposition Methods for Primal Block-Angular Convex Composite Quadratic Conic Programming Problems (2018) (1)
Nonlinear Modelling of the Highest and Best Use in the Valuation of Mixed-Use Development Sites (2011) (1)
Bounds for Random Binary Quadratic Programs (2018) (1)
A Fast Unified Classification Algorithm Based on Accelerated Proximal Gradient Method (2015) (1)
Dissolving Constraints for Riemannian Optimization (2022) (1)
Symmetric Indefinite Preconditioners for FE Solution of Biot's Consolidation Problem (2006) (1)
An efficient Hessian based algorithm for solving large-scale sparse group Lasso problems (2018) (0)
Doubly nonnegative relaxations are equivalent to completely positive reformulations of quadratic optimization problems with block-clique graph structures (2020) (0)
Localization based Ms-Mac Protocol to Enhance the Energy Efficiency in Sensor Networks (2018) (0)
Spectral operators of matrices (2017) (0)
Mesh Independence of a Majorized ABCD Method for Sparse PDE-constrained Optimization Problems (2020) (0)
On proximal augmented Lagrangian based decomposition methods for dual block-angular convex composite programming problems (2023) (0)
Electronic EditionPseudozeros of polynomials and pseudospectraof companion matrices ? (1994) (0)
An introduction to a class of matrix cone programming (2012) (0)
Application of Block Preconditioners for Non-Symmetric Linear System Associated with Biot’s Consolidation Analysis (2013) (0)
Estimation of sparse Gaussian graphical models with hidden clustering structure (2020) (0)
Semi-definite programming relaxation of quadratic assignment problems based on nonredundant matrix splitting (2014) (0)
A semismooth Newton-CG based dual PPA for matrix spectral norm approximation problems (2014) (0)
Bregman Proximal Point Algorithm Revisited: A New Inexact Version and Its Inertial Variant (2021) (0)
On Degenerate Doubly Nonnegative Projection Problems (2020) (0)
Max-norm optimization for robust matrix recovery (2017) (0)
Projecting Onto the Degenerate Doubly Nonnegative Cone (2020) (0)
A block symmetric Gauss–Seidel decomposition theorem for convex composite quadratic programming and its applications (2018) (0)
Equivalences and differences in conic relaxations of combinatorial quadratic optimization problems (2018) (0)
A RIEMANNIAN DIMENTION-REDUCED SECOND ORDER METHOD WITH APPLICATION IN SENSOR NETWORK LOCALIZATION (2023) (0)
On the Closed-form Proximal Mapping and Efficient Algorithms for Exclusive Lasso Models (2019) (0)
A partial proximal point algorithm for nuclear norm regularized matrix least squares problems (2014) (0)
SDPNAL+\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$+$$\end{document}: a majorized semismooth Newton-CG augmented L (2015) (0)
Convergence estimates for iterative methods via the Kriess Matrix Theorem on a general complex domain (1994) (0)
On the equivalence of inexact proximal ALM and ADMM for a class of convex composite programming (2019) (0)
QSDPNAL: a two-phase augmented Lagrangian method for convex quadratic semidefinite programming (2018) (0)
On the Convergence Properties of a Majorized Alternating Direction Method of Multipliers for Linearly Constrained Convex Optimization Problems with Coupled Objective Functions (2016) (0)
A note on the convergence of ADMM for linearly constrained convex optimization problems (2016) (0)
A robust Lagrangian-DNN method for a class of quadratic optimization problems (2016) (0)
A Partial Exact Penalty Function Approach for Constrained Optimization (2023) (0)
A Schur complement based semi-proximal ADMM for convex quadratic conic programming and extensions (2014) (0)
NEW SEARCH DIRECTIONS FOR SEMIDEFINITE PROGRAMMING 225 Given the strengths and weaknesses of the AHO , HKM (2000) (0)
An implementable proximal point algorithmic framework for nuclear norm minimization (2011) (0)
An efficient inexact symmetric Gauss–Seidel based majorized ADMM for high-dimensional convex composite conic programming (2016) (0)
On the R-superlinear convergence of the KKT residuals generated by the augmented Lagrangian method for convex composite conic programming (2018) (0)
Sparse-BSOS: a bounded degree SOS hierarchy for large scale polynomial optimization with sparsity (2017) (0)
Tractable hierarchies of convex relaxations for polynomial optimization on the nonnegative orthant (2022) (0)
A Riemannian Dimension-reduced Second Order Method with Application in Sensor Network Localization (2023) (0)
QPPAL: A Two-phase Proximal Augmented Lagrangian Method for High-dimensional Convex Quadratic Programming Problems (2021) (0)
Solving symmetric indefinite systems in an interior-point method for second order cone programming (2002) (0)
CDOpt: A Python Package for a Class of Riemannian Optimization (2022) (0)
Effective Solution of Large-Scale Soil-Structure Interaction Problems (2011) (0)
On the efficient computation of a generalized Jacobian of the projector over the Birkhoff polytope (2018) (0)
Escaping Spurious Local Minima of Low-Rank Matrix Factorization Through Convex Lifting (2022) (0)
A squared smoothing Newton method for semidefinite programming (2023) (0)
Practical Matrix Completion and Corruption Recovery Using Proximal Alternating Robust Subspace Minimization (2014) (0)

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What Schools Are Affiliated With Kim-Chuan Toh?

Kim-Chuan Toh is affiliated with the following schools: