Kim-Chuan Toh

ORCID

Publication Activity (10 Years)

Years Active: 1996-2024
Publications (10 Years): 90

Top Venues

Publications

Ling Liang, Kim-Chuan Toh, Jia-Jie Zhu
An Inexact Halpern Iteration with Application to Distributionally Robust Optimization. CoRR (2024)
Tianyun Tang, Kim-Chuan Toh
Self-adaptive ADMM for semi-strongly convex problems. Math. Program. Comput. 16 (1) (2024)
Tianyun Tang, Kim-Chuan Toh, Nachuan Xiao, Yinyu Ye
A Riemannian Dimension-Reduced Second-Order Method with Application in Sensor Network Localization. SIAM J. Sci. Comput. 46 (3) (2024)
Ling Liang, Qiyuan Pang, Kim-Chuan Toh, Haizhao Yang
Nesterov's Accelerated Jacobi-Type Methods for Large-scale Symmetric Positive Semidefinite Linear Systems. CoRR (2024)
Tianyun Tang, Kim-Chuan Toh
A Feasible Method for Solving an SDP Relaxation of the Quadratic Knapsack Problem. Math. Oper. Res. 49 (1) (2024)
Tianyun Tang, Kim-Chuan Toh
Solving graph equipartition SDPs on an algebraic variety. Math. Program. 204 (1) (2024)
Anh Duc Nguyen, Tuan Dung Nguyen, Quang Minh Nguyen, Hoang H. Nguyen, Lam M. Nguyen, Kim-Chuan Toh
On Partial Optimal Transport: Revising the Infeasibility of Sinkhorn and Efficient Gradient Methods. AAAI (2024)
Nachuan Xiao, Kuangyu Ding, Xiaoyin Hu, Kim-Chuan Toh
Developing Lagrangian-based Methods for Nonsmooth Nonconvex Optimization. CoRR (2024)
Xingyu Xie, Zhijie Lin, Kim-Chuan Toh, Pan Zhou
LoCo: Low-Bit Communication Adaptor for Large-scale Model Training. CoRR (2024)
Tianyun Tang, Kim-Chuan Toh
A Feasible Method for General Convex Low-Rank SDP Problems. SIAM J. Optim. 34 (3) (2024)
Ling Liang, Kim-Chuan Toh, Haizhao Yang
Vertex Exchange Method for a Class of Quadratic Programming Problems. CoRR (2024)
Lei Yang, Ling Liang, Hong T. M. Chu, Kim-Chuan Toh
A Corrected Inexact Proximal Augmented Lagrangian Method with a Relative Error Criterion for a Class of Group-Quadratic Regularized Optimal Transport Problems. J. Sci. Comput. 99 (3) (2024)
Nachuan Xiao, Xin Liu, Kim-Chuan Toh
Dissolving Constraints for Riemannian Optimization. Math. Oper. Res. 49 (1) (2024)
Heng Yang, Ling Liang, Luca Carlone, Kim-Chuan Toh
An inexact projected gradient method with rounding and lifting by nonlinear programming for solving rank-one semidefinite relaxation of polynomial optimization. Math. Program. 201 (1) (2023)
Kuangyu Ding, Jingyang Li, Kim-Chuan Toh
Nonconvex Stochastic Bregman Proximal Gradient Method with Application to Deep Learning. CoRR (2023)
Kuangyu Ding, Nachuan Xiao, Kim-Chuan Toh
Adam-family Methods with Decoupled Weight Decay in Deep Learning. CoRR (2023)
Kuangyu Ding, Xin Yee Lam, Kim-Chuan Toh
On proximal augmented Lagrangian based decomposition methods for dual block-angular convex composite programming problems. Comput. Optim. Appl. 86 (1) (2023)
Nachuan Xiao, Xiaoyin Hu, Xin Liu, Kim-Chuan Toh
Adam-family Methods for Nonsmooth Optimization with Convergence Guarantees. CoRR (2023)
Nachuan Xiao, Xiaoyin Hu, Kim-Chuan Toh
Convergence Guarantees for Stochastic Subgradient Methods in Nonsmooth Nonconvex Optimization. CoRR (2023)
Anh Duc Nguyen, Tuan Dung Nguyen, Quang Minh Nguyen, Hoang H. Nguyen, Lam M. Nguyen, Kim-Chuan Toh
On Partial Optimal Transport: Revising the Infeasibility of Sinkhorn and Efficient Gradient Methods. CoRR (2023)
Hong T. M. Chu, Ling Liang, Kim-Chuan Toh, Lei Yang
An efficient implementable inexact entropic proximal point algorithm for a class of linear programming problems. Comput. Optim. Appl. 85 (1) (2023)
Xiaoyin Hu, Nachuan Xiao, Xin Liu, Kim-Chuan Toh
An Improved Unconstrained Approach for Bilevel Optimization. SIAM J. Optim. 33 (4) (2023)
Meixia Lin, Defeng Sun, Kim-Chuan Toh
An augmented Lagrangian method with constraint generation for shape-constrained convex regression problems. Math. Program. Comput. 14 (2) (2022)
Hong T. M. Chu, Kim-Chuan Toh, Yangjing Zhang
On Regularized Square-root Regression Problems: Distributionally Robust Interpretation and Fast Computations. J. Mach. Learn. Res. 23 (2022)
Lei Yang, Kim-Chuan Toh
Bregman Proximal Point Algorithm Revisited: A New Inexact Version and Its Inertial Variant. SIAM J. Optim. 32 (3) (2022)
Quoc Tran-Dinh, Ling Liang, Kim-Chuan Toh
A New Homotopy Proximal Variable-Metric Framework for Composite Convex Minimization. Math. Oper. Res. 47 (1) (2022)
Wenjing Li, Wei Bian, Kim-Chuan Toh
Difference-of-Convex Algorithms for a Class of Sparse Group $\ell_0$ Regularized Optimization Problems. SIAM J. Optim. 32 (3) (2022)
Ngoc Hoang Anh Mai, Victor Magron, Jean-Bernard Lasserre, Kim-Chuan Toh
Tractable hierarchies of convex relaxations for polynomial optimization on the nonnegative orthant. CoRR (2022)
Nachuan Xiao, Xiaoyin Hu, Xin Liu, Kim-Chuan Toh
CDOpt: A Python Package for a Class of Riemannian Optimization. CoRR (2022)
Ling Liang, Xudong Li, Defeng Sun, Kim-Chuan Toh
QPPAL: A Two-phase Proximal Augmented Lagrangian Method for High-dimensional Convex Quadratic Programming Problems. ACM Trans. Math. Softw. 48 (3) (2022)
Sunyoung Kim, Masakazu Kojima, Kim-Chuan Toh
Doubly nonnegative relaxations for quadratic and polynomial optimization problems with binary and box constraints. Math. Program. 193 (2) (2022)
Ching-pei Lee, Ling Liang, Tianyun Tang, Kim-Chuan Toh
Escaping Spurious Local Minima of Low-Rank Matrix Factorization Through Convex Lifting. CoRR (2022)
Yancheng Yuan, Tsung-Hui Chang, Defeng Sun, Kim-Chuan Toh
A Dimension Reduction Technique for Large-Scale Structured Sparse Optimization Problems with Application to Convex Clustering. SIAM J. Optim. 32 (3) (2022)
Ying Cui, Ling Liang, Defeng Sun, Kim-Chuan Toh
On Degenerate Doubly Nonnegative Projection Problems. Math. Oper. Res. 47 (3) (2022)
Lei Yang, Jia Li, Defeng Sun, Kim-Chuan Toh
A Fast Globally Linearly Convergent Algorithm for the Computation of Wasserstein Barycenters. J. Mach. Learn. Res. 22 (2021)
Xin Yee Lam, Defeng Sun, Kim-Chuan Toh
Semi-proximal Augmented Lagrangian-Based Decomposition Methods for Primal Block-Angular Convex Composite Quadratic Conic Programming Problems. INFORMS J. Optim. 3 (3) (2021)
Liang Chen, Xudong Li, Defeng Sun, Kim-Chuan Toh
On the equivalence of inexact proximal ALM and ADMM for a class of convex composite programming. Math. Program. 185 (1-2) (2021)
Rui Wang, Naihua Xiu, Kim-Chuan Toh
Subspace quadratic regularization method for group sparse multinomial logistic regression. Comput. Optim. Appl. 79 (3) (2021)
Ning Zhang, Yangjing Zhang, Defeng Sun, Kim-Chuan Toh
An Efficient Linearly Convergent Regularized Proximal Point Algorithm for Fused Multiple Graphical Lasso Problems. SIAM J. Math. Data Sci. 3 (2) (2021)
Sunyoung Kim, Masakazu Kojima, Kim-Chuan Toh
A Newton-bracketing method for a simple conic optimization problem. Optim. Methods Softw. 36 (2-3) (2021)
Ling Liang, Defeng Sun, Kim-Chuan Toh
An Inexact Augmented Lagrangian Method for Second-Order Cone Programming with Applications. SIAM J. Optim. 31 (3) (2021)
Defeng Sun, Kim-Chuan Toh, Yancheng Yuan
Convex Clustering: Model, Theoretical Guarantee and Efficient Algorithm. J. Mach. Learn. Res. 22 (2021)
Heng Yang, Ling Liang, Kim-Chuan Toh, Luca Carlone
STRIDE along Spectrahedral Vertices for Solving Large-Scale Rank-One Semidefinite Relaxations. CoRR (2021)
Chao Ding, Defeng Sun, Jie Sun, Kim-Chuan Toh
Spectral Operators of Matrices: Semismoothness and Characterizations of the Generalized Jacobian. SIAM J. Optim. 30 (1) (2020)
Xudong Li, Defeng Sun, Kim-Chuan Toh
On the efficient computation of a generalized Jacobian of the projector over the Birkhoff polytope. Math. Program. 179 (1) (2020)
Defeng Sun, Kim-Chuan Toh, Yancheng Yuan, Xin-Yuan Zhao
SDPNAL+: A Matlab software for semidefinite programming with bound constraints (version 1.0). Optim. Methods Softw. 35 (1) (2020)
Sunyoung Kim, Masakazu Kojima, Kim-Chuan Toh
Doubly nonnegative relaxations are equivalent to completely positive reformulations of quadratic optimization problems with block-clique graph structures. J. Glob. Optim. 77 (3) (2020)
Yangjing Zhang, Kim-Chuan Toh, Defeng Sun
Learning Graph Laplacian with MCP. CoRR (2020)
Yangjing Zhang, Ning Zhang, Defeng Sun, Kim-Chuan Toh
An efficient Hessian based algorithm for solving large-scale sparse group Lasso problems. Math. Program. 179 (1) (2020)
Sunyoung Kim, Masakazu Kojima, Kim-Chuan Toh
A Geometrical Analysis on Convex Conic Reformulations of Quadratic and Polynomial Optimization Problems. SIAM J. Optim. 30 (2) (2020)
Xudong Li, Defeng Sun, Kim-Chuan Toh
An Asymptotically Superlinearly Convergent Semismooth Newton Augmented Lagrangian Method for Linear Programming. SIAM J. Optim. 30 (3) (2020)
Yangjing Zhang, Ning Zhang, Defeng Sun, Kim-Chuan Toh
A Proximal Point Dual Newton Algorithm for Solving Group Graphical Lasso Problems. SIAM J. Optim. 30 (3) (2020)
Shenglong Hu, Defeng Sun, Kim-Chuan Toh
Best Nonnegative Rank-One Approximations of Tensors. SIAM J. Matrix Anal. Appl. 40 (4) (2019)
Meixia Lin, Yong-Jin Liu, Defeng Sun, Kim-Chuan Toh
Efficient Sparse Semismooth Newton Methods for the Clustered Lasso Problem. SIAM J. Optim. 29 (3) (2019)
Ying Cui, Defeng Sun, Kim-Chuan Toh
Computing the Best Approximation over the Intersection of a Polyhedral Set and the Doubly Nonnegative Cone. SIAM J. Optim. 29 (4) (2019)
Yancheng Yuan, Meixia Lin, Defeng Sun, Kim-Chuan Toh
On the Closed-form Proximal Mapping and Efficient Algorithms for Exclusive Lasso Models. CoRR (2019)
Naoki Ito, Sunyoung Kim, Masakazu Kojima, Akiko Takeda, Kim-Chuan Toh
Algorithm 996: BBCPOP: A Sparse Doubly Nonnegative Relaxation of Polynomial Optimization Problems With Binary, Box, and Complementarity Constraints. ACM Trans. Math. Softw. 45 (3) (2019)
Ying Cui, Defeng Sun, Kim-Chuan Toh
On the R-superlinear convergence of the KKT residuals generated by the augmented Lagrangian method for convex composite conic programming. Math. Program. 178 (1-2) (2019)
Peipei Tang, Chengjing Wang, Defeng Sun, Kim-Chuan Toh
A sparse semismooth Newton based proximal majorization-minimization algorithm for nonconvex square-root-loss regression problems. CoRR (2019)
Ziyan Luo, Defeng Sun, Kim-Chuan Toh, Naihua Xiu
Solving the OSCAR and SLOPE Models Using a Semismooth Newton-Based Augmented Lagrangian Method. J. Mach. Learn. Res. 20 (2019)
Xudong Li, Defeng Sun, Kim-Chuan Toh
A block symmetric Gauss-Seidel decomposition theorem for convex composite quadratic programming and its applications. Math. Program. 175 (1-2) (2019)
Chao Ding, Defeng Sun, Jie Sun, Kim-Chuan Toh
Spectral operators of matrices. Math. Program. 168 (1-2) (2018)
Yancheng Yuan, Defeng Sun, Kim-Chuan Toh
An Efficient Semismooth Newton Based Algorithm for Convex Clustering. CoRR (2018)
Karthik Natarajan, Dongjian Shi, Kim-Chuan Toh
Bounds for Random Binary Quadratic Programs. SIAM J. Optim. 28 (1) (2018)
Tillmann Weißer, Jean B. Lasserre, Kim-Chuan Toh
Sparse-BSOS: a bounded degree SOS hierarchy for large scale polynomial optimization with sparsity. Math. Program. Comput. 10 (1) (2018)
Zhuwen Li, Loong-Fah Cheong, Shuoguang Yang, Kim-Chuan Toh
Simultaneous Clustering and Model Selection: Algorithm, Theory and Applications. IEEE Trans. Pattern Anal. Mach. Intell. 40 (8) (2018)
Xudong Li, Defeng Sun, Kim-Chuan Toh
QSDPNAL: a two-phase augmented Lagrangian method for convex quadratic semidefinite programming. Math. Program. Comput. 10 (4) (2018)
Yancheng Yuan, Defeng Sun, Kim-Chuan Toh
An Efficient Semismooth Newton Based Algorithm for Convex Clustering. ICML (2018)
Xudong Li, Defeng Sun, Kim-Chuan Toh
A Highly Efficient Semismooth Newton Augmented Lagrangian Method for Solving Lasso Problems. SIAM J. Optim. 28 (1) (2018)
Ethan X. Fang, Han Liu, Kim-Chuan Toh, Wen-Xin Zhou
Max-norm optimization for robust matrix recovery. Math. Program. 167 (1) (2018)
Xudong Li, Defeng Sun, Kim-Chuan Toh
On Efficiently Solving the Subproblems of a Level-Set Method for Fused Lasso Problems. SIAM J. Optim. 28 (2) (2018)
Defeng Sun, Kim-Chuan Toh, Yancheng Yuan
Convex Clustering: Model, Theoretical Guarantee and Efficient Algorithm. CoRR (2018)
Naoki Ito, Sunyoung Kim, Masakazu Kojima, Akiko Takeda, Kim-Chuan Toh
Equivalences and differences in conic relaxations of combinatorial quadratic optimization problems. J. Glob. Optim. 72 (4) (2018)
Liang Chen, Defeng Sun, Kim-Chuan Toh
An efficient inexact symmetric Gauss-Seidel based majorized ADMM for high-dimensional convex composite conic programming. Math. Program. 161 (1-2) (2017)
Liang Chen, Defeng Sun, Kim-Chuan Toh
A note on the convergence of ADMM for linearly constrained convex optimization problems. Comput. Optim. Appl. 66 (2) (2017)
Jean B. Lasserre, Kim-Chuan Toh, Shouguang Yang
A bounded degree SOS hierarchy for polynomial optimization. EURO J. Comput. Optim. 5 (1-2) (2017)
Naoki Ito, Akiko Takeda, Kim-Chuan Toh
A Unified Formulation and Fast Accelerated Proximal Gradient Method for Classification. J. Mach. Learn. Res. 18 (2017)
Naohiko Arima, Sunyoung Kim, Masakazu Kojima, Kim-Chuan Toh
A robust Lagrangian-DNN method for a class of quadratic optimization problems. Comput. Optim. Appl. 66 (3) (2017)
Ying Cui, Xudong Li, Defeng Sun, Kim-Chuan Toh
On the Convergence Properties of a Majorized Alternating Direction Method of Multipliers for Linearly Constrained Convex Optimization Problems with Coupled Objective Functions. J. Optim. Theory Appl. 169 (3) (2016)
Defeng Sun, Kim-Chuan Toh, Liuqin Yang
An Efficient Inexact ABCD Method for Least Squares Semidefinite Programming. SIAM J. Optim. 26 (2) (2016)
Min Li, Defeng Sun, Kim-Chuan Toh
A Majorized ADMM with Indefinite Proximal Terms for Linearly Constrained Convex Composite Optimization. SIAM J. Optim. 26 (2) (2016)
Xudong Li, Defeng Sun, Kim-Chuan Toh
A Schur complement based semi-proximal ADMM for convex quadratic conic programming and extensions. Math. Program. 155 (1-2) (2016)
Sunyoung Kim, Masakazu Kojima, Kim-Chuan Toh
A Lagrangian-DNN relaxation: a fast method for computing tight lower bounds for a class of quadratic optimization problems. Math. Program. 156 (1-2) (2016)
Caihua Chen, Yong-Jin Liu, Defeng Sun, Kim-Chuan Toh
A semismooth Newton-CG based dual PPA for matrix spectral norm approximation problems. Math. Program. 155 (1-2) (2016)
Zhuwen Li, Shuoguang Yang, Loong-Fah Cheong, Kim-Chuan Toh
Simultaneous Clustering and Model Selection for Tensor Affinities. CVPR (2016)
Yu-Xiang Wang, Choon Meng Lee, Loong-Fah Cheong, Kim-Chuan Toh
Practical Matrix Completion and Corruption Recovery Using Proximal Alternating Robust Subspace Minimization. Int. J. Comput. Vis. 111 (3) (2015)
Jiming Peng, Tao Zhu, Hezhi Luo, Kim-Chuan Toh
Semi-definite programming relaxation of quadratic assignment problems based on nonredundant matrix splitting. Comput. Optim. Appl. 60 (1) (2015)
Min Li, Defeng Sun, Kim-Chuan Toh
A Convergent 3-Block Semi-Proximal ADMM for Convex Minimization Problems with One Strongly Convex Block. Asia Pac. J. Oper. Res. 32 (4) (2015)
Liuqin Yang, Defeng Sun, Kim-Chuan Toh
SDPNAL $+$ : a majorized semismooth Newton-CG augmented Lagrangian method for semidefinite programming with nonnegative constraints. Math. Program. Comput. 7 (3) (2015)
Defeng Sun, Kim-Chuan Toh, Liuqin Yang
A Convergent 3-Block SemiProximal Alternating Direction Method of Multipliers for Conic Programming with 4-Type Constraints. SIAM J. Optim. 25 (2) (2015)
Chao Ding, Defeng Sun, Kim-Chuan Toh
An introduction to a class of matrix cone programming. Math. Program. 144 (1-2) (2014)
Karthik Natarajan, Dongjian Shi, Kim-Chuan Toh
A Probabilistic Model for Minmax Regret in Combinatorial Optimization. Oper. Res. 62 (1) (2014)
Kaifeng Jiang, Defeng Sun, Kim-Chuan Toh
A partial proximal point algorithm for nuclear norm regularized matrix least squares problems. Math. Program. Comput. 6 (3) (2014)
Bin Wu, Chao Ding, Defeng Sun, Kim-Chuan Toh
On the Moreau-Yosida Regularization of the Vector k-Norm Related Functions. SIAM J. Optim. 24 (2) (2014)
Zheng Gong, Zuowei Shen, Kim-Chuan Toh
Image Restoration with Mixed or Unknown Noises. Multiscale Model. Simul. 12 (2) (2014)
ZhiZhuo Zhang, Guoliang Li, Kim-Chuan Toh, Wing-Kin Sung
3D Chromosome Modeling with Semi-Definite Programming and Hi-C Data. J. Comput. Biol. 20 (11) (2013)
Junfeng Yang, Defeng Sun, Kim-Chuan Toh
A Proximal Point Algorithm for Log-Determinant Optimization with Group Lasso Regularization. SIAM J. Optim. 23 (2) (2013)
Xuan Vinh Doan, Kim-Chuan Toh, Stephen A. Vavasis
A Proximal Point Algorithm for Sequential Feature Extraction Applications. SIAM J. Sci. Comput. 35 (1) (2013)
Yu-Xiang Wang, Choon Meng Lee, Loong-Fah Cheong, Kim-Chuan Toh
Practical Matrix Completion and Corruption Recovery using Proximal Alternating Robust Subspace Minimization. CoRR (2013)
ZhiZhuo Zhang, Guoliang Li, Kim-Chuan Toh, Wing-Kin Sung
Inference of Spatial Organizations of Chromosomes Using Semi-definite Embedding Approach and Hi-C Data. RECOMB (2013)

Kim-Chuan Toh.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Kim-Chuan Toh