Kim-Chuan Toh - RankMe

171 papers A* 4B 1Journal 164Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Exploring Chordal Sparsity in Semidefinite Programming with Sparse plus Low-Rank Data Matrices. SIAM J. Optim. Tianyun Tang, Kim-Chuan Toh
2026	J	`jnl`	Inexact Bregman Proximal Gradient Method and Its Inertial Variant with Absolute and Partial Relative Stopping Criteria. Math. Oper. Res. Lei Yang, Kim-Chuan Toh
2026	J	`jnl`	Slow-Fast Inference: Training-Free Inference Acceleration via Within-Sentence Support Stability. CoRR Xingyu Xie, Zhaochen Yu, Yue Liao, Tao Wang, Kim-Chuan Toh, Shuicheng Yan
2026	J	`jnl`	Wasserstein Distributionally Robust Optimization and Its Tractable Regularization Formulation. J. Optim. Theory Appl. Hong T. M. Chu, Meixia Lin, Kim-Chuan Toh
2025	J	`jnl`	A Squared Smoothing Newton Method for Semidefinite Programming. Math. Oper. Res. Ling Liang, Defeng Sun, Kim-Chuan Toh
2025	J	`jnl`	Adam-family Methods with Decoupled Weight Decay in Deep Learning. Trans. Mach. Learn. Res. Kuangyu Ding, Nachuan Xiao, Kim-Chuan Toh
2025	J	`jnl`	Adaptive sieving: a dimension reduction technique for sparse optimization problems. Math. Program. Comput. Yancheng Yuan, Meixia Lin, Defeng Sun, Kim-Chuan Toh
2025	J	`jnl`	An Inexact Bregman Proximal Difference-of-Convex Algorithm with Two Types of Relative Stopping Criteria. J. Sci. Comput. Lei Yang, Jingjing Hu, Kim-Chuan Toh
2025	J	`jnl`	An Inexact Halpern Iteration with Application to Distributionally Robust Optimization. J. Optim. Theory Appl. Ling Liang, Zusen Xu, Kim-Chuan Toh, Jia-Jie Zhu
2025	J	`jnl`	CDOpt: a Python package for a class of Riemannian optimization. Math. Program. Comput. Nachuan Xiao, Xiaoyin Hu, Xin Liu, Kim-Chuan Toh
2025	J	`jnl`	GRIFFIN: Effective Token Alignment for Faster Speculative Decoding. CoRR Shijing Hu, Jingyang Li, Xingyu Xie, Zhihui Lu, Kim-Chuan Toh, Pan Zhou
2025	—	`conf`	Improved Rates for Stochastic Variance-Reduced Difference-of-Convex Algorithms. CDC Anh Duc Nguyen, Alp Yurtsever, Suvrit Sra, Kim-Chuan Toh
2025	J	`jnl`	Learning-Rate-Free Momentum SGD with Reshuffling Converges in Nonsmooth Nonconvex Optimization. J. Sci. Comput. Xiaoyin Hu, Nachuan Xiao, Xin Liu, Kim-Chuan Toh
2025	J	`jnl`	LoCo: Low-Bit Communication Adaptor for Large-Scale Model Training. IEEE Trans. Pattern Anal. Mach. Intell. Xingyu Xie, Zhijie Lin, Kim-Chuan Toh, Pan Zhou
2025	J	`jnl`	Nesterov's Accelerated Jacobi-Type Methods for Large-Scale Symmetric Positive Semidefinite Linear Systems. SIAM J. Sci. Comput. Ling Liang, Qiyuan Pang, Kim-Chuan Toh, Haizhao Yang
2025	J	`jnl`	NewVEM: A Newton Vertex Exchange Method for a Class of Constrained Self-Concordant Minimization Problems. J. Sci. Comput. Ling Liang, Kim-Chuan Toh, Haizhao Yang
2025	J	`jnl`	Nonconvex Stochastic Bregman Proximal Gradient Method with Application to Deep Learning. J. Mach. Learn. Res. Kuangyu Ding, Jingyang Li, Kim-Chuan Toh
2025	J	`jnl`	On exploration of an interior mirror descent flow for stochastic nonconvex constrained problem. CoRR Kuangyu Ding, Kim-Chuan Toh
2025	J	`jnl`	On solving a rank regularized minimization problem via equivalent factorized column-sparse regularized models. Math. Program. Wenjing Li, Wei Bian, Kim-Chuan Toh
2025	J	`jnl`	Optimization over convex polyhedra via Hadamard parametrizations. Math. Program. Tianyun Tang, Kim-Chuan Toh
2025	J	`jnl`	Quantifying low rank approximations of third order symmetric tensors. Math. Program. Shenglong Hu, Defeng Sun, Kim-Chuan Toh
2025	J	`jnl`	Stochastic Bregman Subgradient Methods for Nonsmooth Nonconvex Optimization Problems. J. Optim. Theory Appl. Kuangyu Ding, Kim-Chuan Toh
2025	J	`jnl`	Towards Understanding Why Data Augmentation Improves Generalization. CoRR Jingyang Li, Jiachun Pan, Kim-Chuan Toh, Pan Zhou
2025	A*	`conf`	Towards Understanding Why FixMatch Generalizes Better Than Supervised Learning. ICLR Jingyang Li, Jiachun Pan, Vincent Y. F. Tan, Kim-Chuan Toh, Pan Zhou
2024	J	`jnl`	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. Lei Yang, Ling Liang, Hong T. M. Chu, Kim-Chuan Toh
2024	J	`jnl`	A Feasible Method for General Convex Low-Rank SDP Problems. SIAM J. Optim. Tianyun Tang, Kim-Chuan Toh
2024	J	`jnl`	A Feasible Method for Solving an SDP Relaxation of the Quadratic Knapsack Problem. Math. Oper. Res. Tianyun Tang, Kim-Chuan Toh
2024	J	`jnl`	A Riemannian Dimension-Reduced Second-Order Method with Application in Sensor Network Localization. SIAM J. Sci. Comput. Tianyun Tang, Kim-Chuan Toh, Nachuan Xiao, Yinyu Ye
2024	J	`jnl`	A Sparse Smoothing Newton Method for Solving Discrete Optimal Transport Problems. ACM Trans. Math. Softw. Di Hou, Ling Liang, Kim-Chuan Toh
2024	J	`jnl`	A highly efficient algorithm for solving exclusive lasso problems. Optim. Methods Softw. Meixia Lin, Yancheng Yuan, Defeng Sun, Kim-Chuan Toh
2024	J	`jnl`	Accelerating Nuclear-norm Regularized Low-rank Matrix Optimization Through Burer-Monteiro Decomposition. J. Mach. Learn. Res. Ching-pei Lee, Ling Liang, Tianyun Tang, Kim-Chuan Toh
2024	J	`jnl`	Adam-family Methods for Nonsmooth Optimization with Convergence Guarantees. J. Mach. Learn. Res. Nachuan Xiao, Xiaoyin Hu, Xin Liu, Kim-Chuan Toh
2024	J	`jnl`	An Inexact Halpern Iteration with Application to Distributionally Robust Optimization. CoRR Ling Liang, Kim-Chuan Toh, Jia-Jie Zhu
2024	J	`jnl`	Developing Lagrangian-based Methods for Nonsmooth Nonconvex Optimization. CoRR Nachuan Xiao, Kuangyu Ding, Xiaoyin Hu, Kim-Chuan Toh
2024	J	`jnl`	Dissolving Constraints for Riemannian Optimization. Math. Oper. Res. Nachuan Xiao, Xin Liu, Kim-Chuan Toh
2024	J	`jnl`	Estimation of Sparse Gaussian Graphical Models with Hidden Clustering Structure. J. Mach. Learn. Res. Meixia Lin, Defeng Sun, Kim-Chuan Toh, Chengjing Wang
2024	J	`jnl`	Learning graph Laplacian with MCP. Optim. Methods Softw. Yangjing Zhang, Kim-Chuan Toh, Defeng Sun
2024	J	`jnl`	LoCo: Low-Bit Communication Adaptor for Large-scale Model Training. CoRR Xingyu Xie, Zhijie Lin, Kim-Chuan Toh, Pan Zhou
2024	J	`jnl`	Memory-Efficient 4-bit Preconditioned Stochastic Optimization. CoRR Jingyang Li, Kuangyu Ding, Kim-Chuan Toh, Pan Zhou
2024	J	`jnl`	Nesterov's Accelerated Jacobi-Type Methods for Large-scale Symmetric Positive Semidefinite Linear Systems. CoRR Ling Liang, Qiyuan Pang, Kim-Chuan Toh, Haizhao Yang
2024	J	`jnl`	On Efficient and Scalable Computation of the Nonparametric Maximum Likelihood Estimator in Mixture Models. J. Mach. Learn. Res. Yangjing Zhang, Ying Cui, Bodhisattva Sen, Kim-Chuan Toh
2024	A*	`conf`	On Partial Optimal Transport: Revising the Infeasibility of Sinkhorn and Efficient Gradient Methods. AAAI Anh Duc Nguyen, Tuan Dung Nguyen, Quang Minh Nguyen, Hoang H. Nguyen, Lam M. Nguyen, Kim-Chuan Toh
2024	J	`jnl`	Optimization Hyper-parameter Laws for Large Language Models. CoRR Xingyu Xie, Kuangyu Ding, Shuicheng Yan, Kim-Chuan Toh, Tianwen Wei
2024	J	`jnl`	Self-adaptive ADMM for semi-strongly convex problems. Math. Program. Comput. Tianyun Tang, Kim-Chuan Toh
2024	J	`jnl`	Solving graph equipartition SDPs on an algebraic variety. Math. Program. Tianyun Tang, Kim-Chuan Toh
2024	J	`jnl`	Towards Understanding Why FixMatch Generalizes Better Than Supervised Learning. CoRR Jingyang Li, Jiachun Pan, Vincent Y. F. Tan, Kim-Chuan Toh, Pan Zhou
2024	J	`jnl`	Vertex Exchange Method for a Class of Quadratic Programming Problems. CoRR Ling Liang, Kim-Chuan Toh, Haizhao Yang
2024	J	`jnl`	Win: Weight-Decay-Integrated Nesterov Acceleration for Faster Network Training. J. Mach. Learn. Res. Pan Zhou, Xingyu Xie, Zhouchen Lin, Kim-Chuan Toh, Shuicheng Yan
2023	J	`jnl`	Adam-family Methods for Nonsmooth Optimization with Convergence Guarantees. CoRR Nachuan Xiao, Xiaoyin Hu, Xin Liu, Kim-Chuan Toh
2023	J	`jnl`	Adam-family Methods with Decoupled Weight Decay in Deep Learning. CoRR Kuangyu Ding, Nachuan Xiao, Kim-Chuan Toh
2023	J	`jnl`	An Improved Unconstrained Approach for Bilevel Optimization. SIAM J. Optim. Xiaoyin Hu, Nachuan Xiao, Xin Liu, Kim-Chuan Toh
2023	J	`jnl`	An efficient implementable inexact entropic proximal point algorithm for a class of linear programming problems. Comput. Optim. Appl. Hong T. M. Chu, Ling Liang, Kim-Chuan Toh, Lei Yang
2023	J	`jnl`	An inexact projected gradient method with rounding and lifting by nonlinear programming for solving rank-one semidefinite relaxation of polynomial optimization. Math. Program. Heng Yang, Ling Liang, Luca Carlone, Kim-Chuan Toh
2023	J	`jnl`	Convergence Guarantees for Stochastic Subgradient Methods in Nonsmooth Nonconvex Optimization. CoRR Nachuan Xiao, Xiaoyin Hu, Kim-Chuan Toh
2023	J	`jnl`	Nonconvex Stochastic Bregman Proximal Gradient Method with Application to Deep Learning. CoRR Kuangyu Ding, Jingyang Li, Kim-Chuan Toh
2023	J	`jnl`	On Partial Optimal Transport: Revising the Infeasibility of Sinkhorn and Efficient Gradient Methods. CoRR Anh Duc Nguyen, Tuan Dung Nguyen, Quang Minh Nguyen, Hoang H. Nguyen, Lam M. Nguyen, Kim-Chuan Toh
2023	J	`jnl`	On proximal augmented Lagrangian based decomposition methods for dual block-angular convex composite programming problems. Comput. Optim. Appl. Kuangyu Ding, Xin Yee Lam, Kim-Chuan Toh
2022	J	`jnl`	A Dimension Reduction Technique for Large-Scale Structured Sparse Optimization Problems with Application to Convex Clustering. SIAM J. Optim. Yancheng Yuan, Tsung-Hui Chang, Defeng Sun, Kim-Chuan Toh
2022	J	`jnl`	A New Homotopy Proximal Variable-Metric Framework for Composite Convex Minimization. Math. Oper. Res. Quoc Tran-Dinh, Ling Liang, Kim-Chuan Toh
2022	J	`jnl`	An augmented Lagrangian method with constraint generation for shape-constrained convex regression problems. Math. Program. Comput. Meixia Lin, Defeng Sun, Kim-Chuan Toh
2022	J	`jnl`	Bregman Proximal Point Algorithm Revisited: A New Inexact Version and Its Inertial Variant. SIAM J. Optim. Lei Yang, Kim-Chuan Toh
2022	J	`jnl`	CDOpt: A Python Package for a Class of Riemannian Optimization. CoRR Nachuan Xiao, Xiaoyin Hu, Xin Liu, Kim-Chuan Toh
2022	J	`jnl`	Difference-of-Convex Algorithms for a Class of Sparse Group $\ell_0$ Regularized Optimization Problems. SIAM J. Optim. Wenjing Li, Wei Bian, Kim-Chuan Toh
2022	J	`jnl`	Doubly nonnegative relaxations for quadratic and polynomial optimization problems with binary and box constraints. Math. Program. Sunyoung Kim, Masakazu Kojima, Kim-Chuan Toh
2022	J	`jnl`	Escaping Spurious Local Minima of Low-Rank Matrix Factorization Through Convex Lifting. CoRR Ching-pei Lee, Ling Liang, Tianyun Tang, Kim-Chuan Toh
2022	J	`jnl`	On Degenerate Doubly Nonnegative Projection Problems. Math. Oper. Res. Ying Cui, Ling Liang, Defeng Sun, Kim-Chuan Toh
2022	J	`jnl`	On Regularized Square-root Regression Problems: Distributionally Robust Interpretation and Fast Computations. J. Mach. Learn. Res. Hong T. M. Chu, Kim-Chuan Toh, Yangjing Zhang
2022	J	`jnl`	QPPAL: A Two-phase Proximal Augmented Lagrangian Method for High-dimensional Convex Quadratic Programming Problems. ACM Trans. Math. Softw. Ling Liang, Xudong Li, Defeng Sun, Kim-Chuan Toh
2022	J	`jnl`	Tractable hierarchies of convex relaxations for polynomial optimization on the nonnegative orthant. CoRR Ngoc Hoang Anh Mai, Victor Magron, Jean-Bernard Lasserre, Kim-Chuan Toh
2021	J	`jnl`	A Fast Globally Linearly Convergent Algorithm for the Computation of Wasserstein Barycenters. J. Mach. Learn. Res. Lei Yang, Jia Li, Defeng Sun, Kim-Chuan Toh
2021	J	`jnl`	A Newton-bracketing method for a simple conic optimization problem. Optim. Methods Softw. Sunyoung Kim, Masakazu Kojima, Kim-Chuan Toh
2021	J	`jnl`	An Efficient Linearly Convergent Regularized Proximal Point Algorithm for Fused Multiple Graphical Lasso Problems. SIAM J. Math. Data Sci. Ning Zhang, Yangjing Zhang, Defeng Sun, Kim-Chuan Toh
2021	J	`jnl`	An Inexact Augmented Lagrangian Method for Second-Order Cone Programming with Applications. SIAM J. Optim. Ling Liang, Defeng Sun, Kim-Chuan Toh
2021	J	`jnl`	Convex Clustering: Model, Theoretical Guarantee and Efficient Algorithm. J. Mach. Learn. Res. Defeng Sun, Kim-Chuan Toh, Yancheng Yuan
2021	J	`jnl`	On the equivalence of inexact proximal ALM and ADMM for a class of convex composite programming. Math. Program. Liang Chen, Xudong Li, Defeng Sun, Kim-Chuan Toh
2021	J	`jnl`	STRIDE along Spectrahedral Vertices for Solving Large-Scale Rank-One Semidefinite Relaxations. CoRR Heng Yang, Ling Liang, Kim-Chuan Toh, Luca Carlone
2021	J	`jnl`	Semi-proximal Augmented Lagrangian-Based Decomposition Methods for Primal Block-Angular Convex Composite Quadratic Conic Programming Problems. INFORMS J. Optim. Xin Yee Lam, Defeng Sun, Kim-Chuan Toh
2021	J	`jnl`	Subspace quadratic regularization method for group sparse multinomial logistic regression. Comput. Optim. Appl. Rui Wang, Naihua Xiu, Kim-Chuan Toh
2020	J	`jnl`	A Geometrical Analysis on Convex Conic Reformulations of Quadratic and Polynomial Optimization Problems. SIAM J. Optim. Sunyoung Kim, Masakazu Kojima, Kim-Chuan Toh
2020	J	`jnl`	A Proximal Point Dual Newton Algorithm for Solving Group Graphical Lasso Problems. SIAM J. Optim. Yangjing Zhang, Ning Zhang, Defeng Sun, Kim-Chuan Toh
2020	J	`jnl`	An Asymptotically Superlinearly Convergent Semismooth Newton Augmented Lagrangian Method for Linear Programming. SIAM J. Optim. Xudong Li, Defeng Sun, Kim-Chuan Toh
2020	J	`jnl`	An efficient Hessian based algorithm for solving large-scale sparse group Lasso problems. Math. Program. Yangjing Zhang, Ning Zhang, Defeng Sun, Kim-Chuan Toh
2020	J	`jnl`	Doubly nonnegative relaxations are equivalent to completely positive reformulations of quadratic optimization problems with block-clique graph structures. J. Glob. Optim. Sunyoung Kim, Masakazu Kojima, Kim-Chuan Toh
2020	J	`jnl`	Learning Graph Laplacian with MCP. CoRR Yangjing Zhang, Kim-Chuan Toh, Defeng Sun
2020	J	`jnl`	On the efficient computation of a generalized Jacobian of the projector over the Birkhoff polytope. Math. Program. Xudong Li, Defeng Sun, Kim-Chuan Toh
2020	J	`jnl`	SDPNAL+: A Matlab software for semidefinite programming with bound constraints (version 1.0). Optim. Methods Softw. Defeng Sun, Kim-Chuan Toh, Yancheng Yuan, Xin-Yuan Zhao
2020	J	`jnl`	Spectral Operators of Matrices: Semismoothness and Characterizations of the Generalized Jacobian. SIAM J. Optim. Chao Ding, Defeng Sun, Jie Sun, Kim-Chuan Toh
2019	J	`jnl`	A block symmetric Gauss-Seidel decomposition theorem for convex composite quadratic programming and its applications. Math. Program. Xudong Li, Defeng Sun, Kim-Chuan Toh
2019	J	`jnl`	A sparse semismooth Newton based proximal majorization-minimization algorithm for nonconvex square-root-loss regression problems. CoRR Peipei Tang, Chengjing Wang, Defeng Sun, Kim-Chuan Toh
2019	J	`jnl`	Algorithm 996: BBCPOP: A Sparse Doubly Nonnegative Relaxation of Polynomial Optimization Problems With Binary, Box, and Complementarity Constraints. ACM Trans. Math. Softw. Naoki Ito, Sunyoung Kim, Masakazu Kojima, Akiko Takeda, Kim-Chuan Toh
2019	J	`jnl`	Best Nonnegative Rank-One Approximations of Tensors. SIAM J. Matrix Anal. Appl. Shenglong Hu, Defeng Sun, Kim-Chuan Toh
2019	J	`jnl`	Computing the Best Approximation over the Intersection of a Polyhedral Set and the Doubly Nonnegative Cone. SIAM J. Optim. Ying Cui, Defeng Sun, Kim-Chuan Toh
2019	J	`jnl`	Efficient Sparse Semismooth Newton Methods for the Clustered Lasso Problem. SIAM J. Optim. Meixia Lin, Yong-Jin Liu, Defeng Sun, Kim-Chuan Toh
2019	J	`jnl`	On the Closed-form Proximal Mapping and Efficient Algorithms for Exclusive Lasso Models. CoRR Yancheng Yuan, Meixia Lin, Defeng Sun, Kim-Chuan Toh
2019	J	`jnl`	On the R-superlinear convergence of the KKT residuals generated by the augmented Lagrangian method for convex composite conic programming. Math. Program. Ying Cui, Defeng Sun, Kim-Chuan Toh
2019	J	`jnl`	Solving the OSCAR and SLOPE Models Using a Semismooth Newton-Based Augmented Lagrangian Method. J. Mach. Learn. Res. Ziyan Luo, Defeng Sun, Kim-Chuan Toh, Naihua Xiu
2018	J	`jnl`	A Highly Efficient Semismooth Newton Augmented Lagrangian Method for Solving Lasso Problems. SIAM J. Optim. Xudong Li, Defeng Sun, Kim-Chuan Toh
2018	A*	`conf`	An Efficient Semismooth Newton Based Algorithm for Convex Clustering. ICML Yancheng Yuan, Defeng Sun, Kim-Chuan Toh
2018	J	`jnl`	An Efficient Semismooth Newton Based Algorithm for Convex Clustering. CoRR Yancheng Yuan, Defeng Sun, Kim-Chuan Toh
2018	J	`jnl`	Bounds for Random Binary Quadratic Programs. SIAM J. Optim. Karthik Natarajan, Dongjian Shi, Kim-Chuan Toh
2018	J	`jnl`	Convex Clustering: Model, Theoretical Guarantee and Efficient Algorithm. CoRR Defeng Sun, Kim-Chuan Toh, Yancheng Yuan
2018	J	`jnl`	Equivalences and differences in conic relaxations of combinatorial quadratic optimization problems. J. Glob. Optim. Naoki Ito, Sunyoung Kim, Masakazu Kojima, Akiko Takeda, Kim-Chuan Toh
2018	J	`jnl`	Max-norm optimization for robust matrix recovery. Math. Program. Ethan X. Fang, Han Liu, Kim-Chuan Toh, Wen-Xin Zhou
2018	J	`jnl`	On Efficiently Solving the Subproblems of a Level-Set Method for Fused Lasso Problems. SIAM J. Optim. Xudong Li, Defeng Sun, Kim-Chuan Toh
2018	J	`jnl`	QSDPNAL: a two-phase augmented Lagrangian method for convex quadratic semidefinite programming. Math. Program. Comput. Xudong Li, Defeng Sun, Kim-Chuan Toh
2018	J	`jnl`	Simultaneous Clustering and Model Selection: Algorithm, Theory and Applications. IEEE Trans. Pattern Anal. Mach. Intell. Zhuwen Li, Loong-Fah Cheong, Shuoguang Yang, Kim-Chuan Toh
2018	J	`jnl`	Sparse-BSOS: a bounded degree SOS hierarchy for large scale polynomial optimization with sparsity. Math. Program. Comput. Tillmann Weißer, Jean B. Lasserre, Kim-Chuan Toh
2018	J	`jnl`	Spectral operators of matrices. Math. Program. Chao Ding, Defeng Sun, Jie Sun, Kim-Chuan Toh
2017	J	`jnl`	A Unified Formulation and Fast Accelerated Proximal Gradient Method for Classification. J. Mach. Learn. Res. Naoki Ito, Akiko Takeda, Kim-Chuan Toh
2017	J	`jnl`	A bounded degree SOS hierarchy for polynomial optimization. EURO J. Comput. Optim. Jean B. Lasserre, Kim-Chuan Toh, Shouguang Yang
2017	J	`jnl`	A note on the convergence of ADMM for linearly constrained convex optimization problems. Comput. Optim. Appl. Liang Chen, Defeng Sun, Kim-Chuan Toh
2017	J	`jnl`	A robust Lagrangian-DNN method for a class of quadratic optimization problems. Comput. Optim. Appl. Naohiko Arima, Sunyoung Kim, Masakazu Kojima, Kim-Chuan Toh
2017	J	`jnl`	An efficient inexact symmetric Gauss-Seidel based majorized ADMM for high-dimensional convex composite conic programming. Math. Program. Liang Chen, Defeng Sun, Kim-Chuan Toh
2016	J	`jnl`	A Lagrangian-DNN relaxation: a fast method for computing tight lower bounds for a class of quadratic optimization problems. Math. Program. Sunyoung Kim, Masakazu Kojima, Kim-Chuan Toh
2016	J	`jnl`	A Majorized ADMM with Indefinite Proximal Terms for Linearly Constrained Convex Composite Optimization. SIAM J. Optim. Min Li, Defeng Sun, Kim-Chuan Toh
2016	J	`jnl`	A Schur complement based semi-proximal ADMM for convex quadratic conic programming and extensions. Math. Program. Xudong Li, Defeng Sun, Kim-Chuan Toh
2016	J	`jnl`	A semismooth Newton-CG based dual PPA for matrix spectral norm approximation problems. Math. Program. Caihua Chen, Yong-Jin Liu, Defeng Sun, Kim-Chuan Toh
2016	J	`jnl`	An Efficient Inexact ABCD Method for Least Squares Semidefinite Programming. SIAM J. Optim. Defeng Sun, Kim-Chuan Toh, Liuqin Yang
2016	J	`jnl`	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. Ying Cui, Xudong Li, Defeng Sun, Kim-Chuan Toh
2016	A*	`conf`	Simultaneous Clustering and Model Selection for Tensor Affinities. CVPR Zhuwen Li, Shuoguang Yang, Loong-Fah Cheong, Kim-Chuan Toh
2015	J	`jnl`	A Convergent 3-Block Semi-Proximal ADMM for Convex Minimization Problems with One Strongly Convex Block. Asia Pac. J. Oper. Res. Min Li, Defeng Sun, Kim-Chuan Toh
2015	J	`jnl`	A Convergent 3-Block SemiProximal Alternating Direction Method of Multipliers for Conic Programming with 4-Type Constraints. SIAM J. Optim. Defeng Sun, Kim-Chuan Toh, Liuqin Yang
2015	J	`jnl`	Practical Matrix Completion and Corruption Recovery Using Proximal Alternating Robust Subspace Minimization. Int. J. Comput. Vis. Yu-Xiang Wang, Choon Meng Lee, Loong-Fah Cheong, Kim-Chuan Toh
2015	J	`jnl`	SDPNAL $+$ : a majorized semismooth Newton-CG augmented Lagrangian method for semidefinite programming with nonnegative constraints. Math. Program. Comput. Liuqin Yang, Defeng Sun, Kim-Chuan Toh
2015	J	`jnl`	Semi-definite programming relaxation of quadratic assignment problems based on nonredundant matrix splitting. Comput. Optim. Appl. Jiming Peng, Tao Zhu, Hezhi Luo, Kim-Chuan Toh
2014	J	`jnl`	A Probabilistic Model for Minmax Regret in Combinatorial Optimization. Oper. Res. Karthik Natarajan, Dongjian Shi, Kim-Chuan Toh
2014	J	`jnl`	A partial proximal point algorithm for nuclear norm regularized matrix least squares problems. Math. Program. Comput. Kaifeng Jiang, Defeng Sun, Kim-Chuan Toh
2014	J	`jnl`	An introduction to a class of matrix cone programming. Math. Program. Chao Ding, Defeng Sun, Kim-Chuan Toh
2014	J	`jnl`	Image Restoration with Mixed or Unknown Noises. Multiscale Model. Simul. Zheng Gong, Zuowei Shen, Kim-Chuan Toh
2014	J	`jnl`	On the Moreau-Yosida Regularization of the Vector k-Norm Related Functions. SIAM J. Optim. Bin Wu, Chao Ding, Defeng Sun, Kim-Chuan Toh
2013	J	`jnl`	3D Chromosome Modeling with Semi-Definite Programming and Hi-C Data. J. Comput. Biol. ZhiZhuo Zhang, Guoliang Li, Kim-Chuan Toh, Wing-Kin Sung
2013	J	`jnl`	A Proximal Point Algorithm for Log-Determinant Optimization with Group Lasso Regularization. SIAM J. Optim. Junfeng Yang, Defeng Sun, Kim-Chuan Toh
2013	J	`jnl`	A Proximal Point Algorithm for Sequential Feature Extraction Applications. SIAM J. Sci. Comput. Xuan Vinh Doan, Kim-Chuan Toh, Stephen A. Vavasis
2013	B	`conf`	Inference of Spatial Organizations of Chromosomes Using Semi-definite Embedding Approach and Hi-C Data. RECOMB ZhiZhuo Zhang, Guoliang Li, Kim-Chuan Toh, Wing-Kin Sung
2013	J	`jnl`	Practical Matrix Completion and Corruption Recovery using Proximal Alternating Robust Subspace Minimization. CoRR Yu-Xiang Wang, Choon Meng Lee, Loong-Fah Cheong, Kim-Chuan Toh
2013	—	`ch.`	Using a Distributed SDP Approach to Solve Simulated Protein Molecular Conformation Problems. Distance Geometry Xingyuan Fang, Kim-Chuan Toh
2012	J	`jnl`	An Inexact Accelerated Proximal Gradient Method for Large Scale Linearly Constrained Convex SDP. SIAM J. Optim. Kaifeng Jiang, Defeng Sun, Kim-Chuan Toh
2012	J	`jnl`	An implementable proximal point algorithmic framework for nuclear norm minimization. Math. Program. Yong-Jin Liu, Defeng Sun, Kim-Chuan Toh
2011	J	`jnl`	A block coordinate gradient descent method for regularized convex separable optimization and covariance selection. Math. Program. Sangwoon Yun, Paul Tseng, Kim-Chuan Toh
2011	J	`jnl`	A coordinate gradient descent method for Comput. Optim. Appl. Sangwoon Yun, Kim-Chuan Toh
2011	J	`jnl`	An Accelerated Proximal Gradient Algorithm for Frame-Based Image Restoration via the Balanced Approach. SIAM J. Imaging Sci. Zuowei Shen, Kim-Chuan Toh, Sangwoon Yun
2010	J	`jnl`	A Newton-CG Augmented Lagrangian Method for Semidefinite Programming. SIAM J. Optim. Xin-Yuan Zhao, Defeng Sun, Kim-Chuan Toh
2010	J	`jnl`	An inexact interior point method for Math. Program. Comput. Lu Li, Kim-Chuan Toh
2010	J	`jnl`	On the implementation of a log-barrier progressive hedging method for multistage stochastic programs. J. Comput. Appl. Math. Xinwei Liu, Kim-Chuan Toh, Gongyun Zhao
2010	J	`jnl`	Solving Log-Determinant Optimization Problems by a Newton-CG Primal Proximal Point Algorithm. SIAM J. Optim. Chengjing Wang, Defeng Sun, Kim-Chuan Toh
2009	J	`jnl`	An SDP-Based Divide-and-Conquer Algorithm for Large-Scale Noisy Anchor-Free Graph Realization. SIAM J. Sci. Comput. Ngai-Hang Z. Leung, Kim-Chuan Toh
2008	J	`jnl`	A Distributed SDP Approach for Large-Scale Noisy Anchor-Free Graph Realization with Applications to Molecular Conformation. SIAM J. Sci. Comput. Pratik Biswas, Kim-Chuan Toh, Yinyu Ye
2008	J	`jnl`	An inexact primal-dual path following algorithm for convex quadratic SDP. Math. Program. Kim-Chuan Toh
2007	J	`jnl`	Behavioral measures and their correlation with IPM iteration counts on semi-definite programming problems. Math. Program. Robert M. Freund, Fernando Ordóñez, Kim-Chuan Toh
2007	J	`jnl`	Preconditioning and iterative solution of symmetric indefinite linear systems arising from interior point methods for linear programming. Comput. Optim. Appl. Joo-Siong Chai, Kim-Chuan Toh
2006	J	`jnl`	Computation of condition numbers for linear programming problems using Peña's method. Optim. Methods Softw. Joo-Siong Chai, Kim-Chuan Toh
2006	J	`jnl`	Semidefinite Programming Approaches for Sensor Network Localization With Noisy Distance Measurements. IEEE Trans Autom. Sci. Eng. Pratik Biswas, Tzu-Chen Liang, Kim-Chuan Toh, Yinyu Ye, Ta-Chung Wang
2006	J	`jnl`	Solving Second Order Cone Programming via a Reduced Augmented System Approach. SIAM J. Optim. Zhi Cai, Kim-Chuan Toh
2005	J	`jnl`	Efficient Algorithms for the Smallest Enclosing Ball Problem. Comput. Optim. Appl. Guanglu Zhou, Kim-Chuan Toh, Jie Sun
2004	J	`jnl`	Convergence Analysis of an Infeasible Interior Point Algorithm Based on a Regularized Central Path for Linear Complementarity Problems. Comput. Optim. Appl. Guanglu Zhou, Kim-Chuan Toh, Gongyun Zhao
2004	J	`jnl`	Polynomiality of an inexact infeasible interior point algorithm for semidefinite programming. Math. Program. Guanglu Zhou, Kim-Chuan Toh
2004	J	`jnl`	Solving Large Scale Semidefinite Programs via an Iterative Solver on the Augmented Systems. SIAM J. Optim. Kim-Chuan Toh
2003	J	`jnl`	Solving semidefinite-quadratic-linear programs using SDPT3. Math. Program. Reha H. Tütüncü, Kim-Chuan Toh, Michael J. Todd
2002	J	`jnl`	A Multiple-Cut Analytic Center Cutting Plane Method for Semidefinite Feasibility Problems. SIAM J. Optim. Kim-Chuan Toh, Gongyun Zhao, Jie Sun
2002	J	`jnl`	A Note on the Calculation of Step-Lengths in Interior-Point Methods for Semidefinite Programming. Comput. Optim. Appl. Kim-Chuan Toh
2002	J	`jnl`	An Analytic Center Cutting Plane Method for Semidefinite Feasibility Problems. Math. Oper. Res. Jie Sun, Kim-Chuan Toh, Gongyun Zhao
2002	J	`jnl`	Solving Some Large Scale Semidefinite Programs via the Conjugate Residual Method. SIAM J. Optim. Kim-Chuan Toh, Masakazu Kojima
2001	J	`jnl`	Computing the Sobolev Regularity of Refinable Functions by the Arnoldi Method. SIAM J. Matrix Anal. Appl. Amos Ron, Zuowei Shen, Kim-Chuan Toh
2000	J	`jnl`	Some New Search Directions for Primal-Dual Interior Point Methods in Semidefinite Programming. SIAM J. Optim. Kim-Chuan Toh
1999	J	`jnl`	Primal-Dual Path-Following Algorithms for Determinant Maximization Problems With Linear Matrix Inequalities. Comput. Optim. Appl. Kim-Chuan Toh
1999	J	`jnl`	The Kreiss Matrix Theorem on a General Complex Domain. SIAM J. Matrix Anal. Appl. Kim-Chuan Toh, Lloyd N. Trefethen
1998	J	`jnl`	From Potential Theory to Matrix Iterations in Six Steps. SIAM Rev. Tobin A. Driscoll, Kim-Chuan Toh, Lloyd N. Trefethen
1998	J	`jnl`	On the Nesterov-Todd Direction in Semidefinite Programming. SIAM J. Optim. Michael J. Todd, Kim-Chuan Toh, Reha H. Tütüncü
1998	J	`jnl`	The Chebyshev Polynomials of a Matrix. SIAM J. Matrix Anal. Appl. Kim-Chuan Toh, Lloyd N. Trefethen
1997	J	`jnl`	GMRES vs. Ideal GMRES. SIAM J. Matrix Anal. Appl. Kim-Chuan Toh
1996	J	`jnl`	Calculation of Pseudospectra by the Arnoldi Iteration. SIAM J. Sci. Comput. Kim-Chuan Toh, Lloyd N. Trefethen