Optimal Solutions for the Closest-String Problem via Integer Programming. - Cláudio Nogueira de Meneses; Zhaosong Lu; Carlos A. S. Oliveira; Panos M. Pardalos (INFORMS J. Comput., 2004)

Error Bounds and Limiting Behavior of Weighted Paths Associated with the SDP Map X1/2SX1/2. - Zhaosong Lu; Renato D. C. Monteiro (SIAM J. Optim., 2005)

A Note on the Local Convergence of a Predictor-Corrector Interior-Point Algorithm for the Semidefinite Linear Complementarity Problem Based on the Alizadeh–Haeberly–Overton Search Direction. - Zhaosong Lu; Renato D. C. Monteiro (SIAM J. Optim., 2005)

Algorithm Design and Analysis for Large-Scale Semidefinite Programming and Nonlinear Programming. - Zhaosong Lu (2005)

An Iterative Solver-Based Infeasible Primal-Dual Path-Following Algorithm for Convex Quadratic Programming. - Zhaosong Lu; Renato D. C. Monteiro; Jerome W. O'Neal (SIAM J. Optim., 2006)

A modified nearly exact method for solving low-rank trust region subproblem. - Zhaosong Lu; Renato D. C. Monteiro (Math. Program., 2007)

Large-scale semidefinite programming via a saddle point Mirror-Prox algorithm. - Zhaosong Lu; Arkadi Nemirovski; Renato D. C. Monteiro (Math. Program., 2007)

Limiting behavior of the Alizadeh-Haeberly-Overton weighted paths in semidefinite programming. - Zhaosong Lu; Renato D. C. Monteiro (Optim. Methods Softw., 2007)

An iterative solver-based long-step infeasible primal-dual path-following algorithm for convex QP based on a class of preconditioners. - Zhaosong Lu; Renato D. C. Monteiro; Jerome W. O'Neal (Optim. Methods Softw., 2009)

Smooth Optimization Approach for Sparse Covariance Selection. - Zhaosong Lu (SIAM J. Optim., 2009)

Adaptive First-Order Methods for General Sparse Inverse Covariance Selection. - Zhaosong Lu (SIAM J. Matrix Anal. Appl., 2010)

Penalty Decomposition Methods for Rank Minimization. - Yong Zhang 004; Zhaosong Lu (NIPS, 2011)

Primal-dual first-order methods with O(1/e) iteration-complexity for cone programming. - Guanghui Lan; Zhaosong Lu; Renato D. C. Monteiro (Math. Program., 2011)

A computational study on robust portfolio selection based on a joint ellipsoidal uncertainty set. - Zhaosong Lu (Math. Program., 2011)

Robust portfolio selection based on a joint ellipsoidal uncertainty set. - Zhaosong Lu (Optim. Methods Softw., 2011)

Minimizing Condition Number via Convex Programming. - Zhaosong Lu; Ting Kei Pong (SIAM J. Matrix Anal. Appl., 2011)

Iterative Reweighted Minimization Methods for $l_p$ Regularized Unconstrained Nonlinear Programming - Zhaosong Lu (CoRR, 2012)

Iterative Hard Thresholding Methods for $l_0$ Regularized Convex Cone Programming - Zhaosong Lu (CoRR, 2012)

An alternating direction method for finding Dantzig selectors. - Zhaosong Lu; Ting Kei Pong; Yong Zhang 004 (Comput. Stat. Data Anal., 2012)

Convex optimization methods for dimension reduction and coefficient estimation in multivariate linear regression. - Zhaosong Lu; Renato D. C. Monteiro; Ming Yuan 001 (Math. Program., 2012)

An augmented Lagrangian approach for sparse principal component analysis. - Zhaosong Lu; Yong Zhang 004 (Math. Program., 2012)

A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems. - Pinghua Gong; Changshui Zhang; Zhaosong Lu; Jianhua Huang; Jieping Ye (ICML (2), 2013)

FeaFiner: biomarker identification from medical data through feature generalization and selection. - Jiayu Zhou; Zhaosong Lu; Jimeng Sun 001; Lei Yuan 001; Fei Wang 001; Jieping Ye (KDD, 2013)

Randomized Block Coordinate Non-Monotone Gradient Method for a Class of Nonlinear Programming. - Zhaosong Lu; Lin Xiao (CoRR, 2013)

Assessing the Value of Dynamic Pricing in Network Revenue Management. - Dan Zhang 005; Zhaosong Lu (INFORMS J. Comput., 2013)

ℓ0 Minimization for wavelet frame based image restoration. - Yong Zhang 004; Bin Dong 001; Zhaosong Lu (Math. Comput., 2013)

Primal-dual first-order methods for a class of cone programming. - Zhaosong Lu (Optim. Methods Softw., 2013)

Sparse Approximation via Penalty Decomposition Methods. - Zhaosong Lu; Yong Zhang 004 (SIAM J. Optim., 2013)

Computing Optimal Experimental Designs via Interior Point Method. - Zhaosong Lu; Ting Kei Pong (SIAM J. Matrix Anal. Appl., 2013)

Rank-One Matrix Pursuit for Matrix Completion. - Zheng Wang 011; Ming-Jun Lai; Zhaosong Lu; Wei Fan 001; Hasan Davulcu; Jieping Ye (ICML, 2014)

An Accelerated Proximal Coordinate Gradient Method. - Qihang Lin; Zhaosong Lu; Lin Xiao (NIPS, 2014)

Iterative hard thresholding methods for l0 regularized convex cone programming. - Zhaosong Lu (Math. Program., 2014)

Iterative reweighted minimization methods for lp regularized unconstrained nonlinear programming. - Zhaosong Lu (Math. Program., 2014)

A Nonmonotone Projected Gradient Method for Optimization over Sparse Symmetric Sets. - Zhaosong Lu (CoRR, 2015)

Generalized Conjugate Gradient Methods for ℓ1 Regularized Convex Quadratic Programming with Finite Convergence. - Zhaosong Lu; Xiaojun Chen 001 (CoRR, 2015)

On the complexity analysis of randomized block-coordinate descent methods. - Zhaosong Lu; Lin Xiao (Math. Program., 2015)

Penalty decomposition methods for rank minimization. - Zhaosong Lu; Yong Zhang 004; Xiaorui Li (Optim. Methods Softw., 2015)

An Accelerated Randomized Proximal Coordinate Gradient Method and its Application to Regularized Empirical Risk Minimization. - Qihang Lin; Zhaosong Lu; Lin Xiao (SIAM J. Optim., 2015)

Fused Multiple Graphical Lasso. - Sen Yang 004; Zhaosong Lu; Xiaotong Shen; Peter Wonka; Jieping Ye (SIAM J. Optim., 2015)

A Proximal Gradient Method for Ensemble Density Functional Theory. - Michael Ulbrich; Zaiwen Wen; Chao Yang 001; Dennis Klöckner; Zhaosong Lu (SIAM J. Sci. Comput., 2015)

Orthogonal Rank-One Matrix Pursuit for Low Rank Matrix Completion. - Zheng Wang 011; Ming-Jun Lai; Zhaosong Lu; Wei Fan 001; Hasan Davulcu; Jieping Ye (SIAM J. Sci. Comput., 2015)

An efficient optimization approach for a cardinality-constrained index tracking problem. - Fengmin Xu; Zhaosong Lu; Zongben Xu (Optim. Methods Softw., 2016)

Penalty Methods for a Class of Non-Lipschitz Optimization Problems. - Xiaojun Chen 001; Zhaosong Lu; Ting Kei Pong (SIAM J. Optim., 2016)

( ell _p ) Regularized low-rank approximation via iterative reweighted singular value minimization. - Zhaosong Lu; Yong Zhang 004; Jian Lu 002 (Comput. Optim. Appl., 2017)

Randomized Block Proximal Damped Newton Method for Composite Self-Concordant Minimization. - Zhaosong Lu (SIAM J. Optim., 2017)

An Augmented Lagrangian Method for Non-Lipschitz Nonconvex Programming. - Xiaojun Chen 001; Lei Guo 016; Zhaosong Lu; Jane J. Ye (SIAM J. Numer. Anal., 2017)

A Randomized Nonmonotone Block Proximal Gradient Method for a Class of Structured Nonlinear Programming. - Zhaosong Lu; Lin Xiao (SIAM J. Numer. Anal., 2017)

Generalized Conjugate Gradient Methods for ℓ1 Regularized Convex Quadratic Programming with Finite Convergence. - Zhaosong Lu; Xiaojun Chen 001 (Math. Oper. Res., 2018)

Sparse Recovery via Partial Regularization: Models, Theory, and Algorithms. - Zhaosong Lu; Xiaorui Li (Math. Oper. Res., 2018)

Enhanced proximal DC algorithms with extrapolation for a class of structured nonsmooth DC minimization. - Zhaosong Lu; Zirui Zhou; Zhe Sun (Math. Program., 2019)

Nonmonotone Enhanced Proximal DC Algorithms for a Class of Structured Nonsmooth DC Programming. - Zhaosong Lu; Zirui Zhou (SIAM J. Optim., 2019)

Convergence Rate Analysis of a Sequential Convex Programming Method with Line Search for a Class of Constrained Difference-of-Convex Optimization Problems. - Peiran Yu; Ting Kei Pong; Zhaosong Lu (SIAM J. Optim., 2021)

Primal-dual extrapolation methods for monotone inclusions under local Lipschitz continuity with applications to variational inequality, conic constrained saddle point, and convex conic optimization problems. - Zhaosong Lu; Sanyou Mei (CoRR, 2022)

Penalty and Augmented Lagrangian Methods for Constrained DC Programming. - Zhaosong Lu; Zhe Sun; Zirui Zhou (Math. Oper. Res., 2022)

Generalized-Smooth Nonconvex Optimization is As Efficient As Smooth Nonconvex Optimization. - Ziyi Chen 002; Yi Zhou 017; Yingbin Liang; Zhaosong Lu (ICML, 2023)

Newton-CG methods for nonconvex unconstrained optimization with Hölder continuous Hessian. - Chuan He 004; Zhaosong Lu (CoRR, 2023)

FastPicker: Adaptive independent two-stage video-to-video summarization for efficient action recognition. - Saghir Alfasly; Jian Lu 002; Chen Xu 004; Zaid Al-Huda; Qingtang Jiang; Zhaosong Lu; Charles K. Chui (Neurocomputing, 2023)

A Parameter-Free Conditional Gradient Method for Composite Minimization under Hölder Condition. - Masaru Ito; Zhaosong Lu; Chuan He 004 (J. Mach. Learn. Res., 2023)

Exact penalization for cardinality and rank-constrained optimization problems via partial regularization. - Zhaosong Lu; Xiaorui Li; Shuhuang Xiang (Optim. Methods Softw., 2023)

A Newton-CG Based Barrier Method for Finding a Second-Order Stationary Point of Nonconvex Conic Optimization with Complexity Guarantees. - Chuan He 004; Zhaosong Lu (SIAM J. Optim., 2023)

Iteration-Complexity of First-Order Augmented Lagrangian Methods for Convex Conic Programming. - Zhaosong Lu; Zirui Zhou (SIAM J. Optim., 2023)

A Newton-CG Based Augmented Lagrangian Method for Finding a Second-Order Stationary Point of Nonconvex Equality Constrained Optimization with Complexity Guarantees. - Chuan He 004; Zhaosong Lu; Ting Kei Pong (SIAM J. Optim., 2023)

Accelerated First-Order Methods for Convex Optimization with Locally Lipschitz Continuous Gradient. - Zhaosong Lu; Sanyou Mei (SIAM J. Optim., 2023)

Single-Loop Stochastic Algorithms for Difference of Max-Structured Weakly Convex Functions. - Quanqi Hu; Qi Qi 006; Zhaosong Lu; Tianbao Yang (NeurIPS, 2024)

Variance-reduced first-order methods for deterministically constrained stochastic nonconvex optimization with strong convergence guarantees. - Zhaosong Lu; Sanyou Mei; Yifeng Xiao (CoRR, 2024)

Exactly Uncorrelated Sparse Principal Component Analysis. - Oh-Ran Kwon; Zhaosong Lu; Hui Zou (J. Comput. Graph. Stat., 2024)

First-Order Penalty Methods for Bilevel Optimization. - Zhaosong Lu; Sanyou Mei (SIAM J. Optim., 2024)

Augmented Lagrangian method for tensor low-rank and sparsity models in multi-dimensional image recovery. - Hong Zhu 012; Xiaoxia Liu; Lin Huang; Zhaosong Lu; Jian Lu 002; Michael K. Ng 001 (Adv. Comput. Math., 2024)

A Newton-CG based barrier-augmented Lagrangian method for general nonconvex conic optimization. - Chuan He 004; Heng Huang; Zhaosong Lu (Comput. Optim. Appl., 2024)

Nested Stochastic Gradient Descent for (Generalized) Sinkhorn Distance-Regularized Distributionally Robust Optimization. - Yufeng Yang; Yi Zhou 017; Zhaosong Lu (CoRR, 2025)

Complexity of normalized stochastic first-order methods with momentum under heavy-tailed noise. - Chuan He 004; Zhaosong Lu; Defeng Sun; Zhanwang Deng (CoRR, 2025)

First-order methods for stochastic and finite-sum convex optimization with deterministic constraints. - Zhaosong Lu; Yifeng Xiao (CoRR, 2025)

A first-order method for nonconvex-nonconcave minimax problems under a local Kurdyka-Łojasiewicz condition. - Zhaosong Lu; Xiangyuan Wang (CoRR, 2025)

A first-order augmented Lagrangian method for constrained minimax optimization. - Zhaosong Lu; Sanyou Mei (Math. Program., 2025)