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2020 – today
- 2024
[j52]Hong Zhu, Xiaoxia Liu, Lin Huang, Zhaosong Lu, Jian Lu
, Michael K. Ng:
Augmented Lagrangian method for tensor low-rank and sparsity models in multi-dimensional image recovery. Adv. Comput. Math. 50(4): 75 (2024)- [j51]Oh-Ran Kwon, Zhaosong Lu, Hui Zou:
Exactly Uncorrelated Sparse Principal Component Analysis. J. Comput. Graph. Stat. 33(1): 231-241 (2024) - [j50]Zhaosong Lu, Sanyou Mei:
First-Order Penalty Methods for Bilevel Optimization. SIAM J. Optim. 34(2): 1937-1969 (2024) - [i23]Quanqi Hu, Qi Qi, Zhaosong Lu, Tianbao Yang:
Single-loop Stochastic Algorithms for Difference of Max-Structured Weakly Convex Functions. CoRR abs/2405.18577 (2024) - [i22]Zhaosong Lu, Sanyou Mei, Yifeng Xiao:
Variance-reduced first-order methods for deterministically constrained stochastic nonconvex optimization with strong convergence guarantees. CoRR abs/2409.09906 (2024) - 2023
- [j49]Saghir Alfasly, Jian Lu, Chen Xu, Zaid Al-Huda, Qingtang Jiang, Zhaosong Lu, Charles K. Chui:
FastPicker: Adaptive independent two-stage video-to-video summarization for efficient action recognition. Neurocomputing 516: 231-244 (2023) - [j48]Masaru Ito, Zhaosong Lu, Chuan He:
A Parameter-Free Conditional Gradient Method for Composite Minimization under Hölder Condition. J. Mach. Learn. Res. 24: 166:1-166:34 (2023) - [j47]Zhaosong Lu, Xiaorui Li, Shuhuang Xiang:
Exact penalization for cardinality and rank-constrained optimization problems via partial regularization. Optim. Methods Softw. 38(2): 412-433 (2023) - [j46]Zhaosong Lu, Zirui Zhou:
Iteration-Complexity of First-Order Augmented Lagrangian Methods for Convex Conic Programming. SIAM J. Optim. 33(2): 1159-1190 (2023) - [j45]Chuan He, Zhaosong Lu:
A Newton-CG Based Barrier Method for Finding a Second-Order Stationary Point of Nonconvex Conic Optimization with Complexity Guarantees. SIAM J. Optim. 33(2): 1191-1222 (2023) - [j44]Chuan He, Zhaosong Lu, Ting Kei Pong:
A Newton-CG Based Augmented Lagrangian Method for Finding a Second-Order Stationary Point of Nonconvex Equality Constrained Optimization with Complexity Guarantees. SIAM J. Optim. 33(3): 1734-1766 (2023) - [j43]Zhaosong Lu, Sanyou Mei:
Accelerated First-Order Methods for Convex Optimization with Locally Lipschitz Continuous Gradient. SIAM J. Optim. 33(3): 2275-2310 (2023) - [c6]Ziyi Chen, Yi Zhou, Yingbin Liang, Zhaosong Lu:
Generalized-Smooth Nonconvex Optimization is As Efficient As Smooth Nonconvex Optimization. ICML 2023: 5396-5427 - [i21]Zhaosong Lu, Sanyou Mei:
First-order penalty methods for bilevel optimization. CoRR abs/2301.01716 (2023) - [i20]Zhaosong Lu, Sanyou Mei:
A first-order augmented Lagrangian method for constrained minimax optimization. CoRR abs/2301.02060 (2023) - [i19]Chuan He, Zhaosong Lu, Ting Kei Pong:
A Newton-CG based augmented Lagrangian method for finding a second-order stationary point of nonconvex equality constrained optimization with complexity guarantees. CoRR abs/2301.03139 (2023) - [i18]Chuan He, Heng Huang, Zhaosong Lu:
A Newton-CG based barrier-augmented Lagrangian method for general nonconvex conic optimization. CoRR abs/2301.04204 (2023) - [i17]Chuan He, Zhaosong Lu:
Newton-CG methods for nonconvex unconstrained optimization with Hölder continuous Hessian. CoRR abs/2311.13094 (2023) - 2022
- [j42]Zhaosong Lu, Zhe Sun, Zirui Zhou:
Penalty and Augmented Lagrangian Methods for Constrained DC Programming. Math. Oper. Res. 47(3): 2260-2285 (2022) - [i16]Zhaosong Lu, Sanyou Mei:
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. CoRR abs/2206.00973 (2022) - [i15]Zhaosong Lu, Sanyou Mei:
Accelerated first-order methods for convex optimization with locally Lipschitz continuous gradient. CoRR abs/2206.01209 (2022) - [i14]Chuan He, Zhaosong Lu:
A Newton-CG based barrier method for finding a second-order stationary point of nonconvex conic optimization with complexity guarantees. CoRR abs/2207.05697 (2022) - 2021
- [j41]Peiran Yu, Ting Kei Pong, Zhaosong Lu:
Convergence Rate Analysis of a Sequential Convex Programming Method with Line Search for a Class of Constrained Difference-of-Convex Optimization Problems. SIAM J. Optim. 31(3): 2024-2054 (2021)
2010 – 2019
- 2019
- [j40]Zhaosong Lu, Zirui Zhou, Zhe Sun:
Enhanced proximal DC algorithms with extrapolation for a class of structured nonsmooth DC minimization. Math. Program. 176(1-2): 369-401 (2019) - [j39]Zhaosong Lu, Zirui Zhou:
Nonmonotone Enhanced Proximal DC Algorithms for a Class of Structured Nonsmooth DC Programming. SIAM J. Optim. 29(4): 2725-2752 (2019) - 2018
- [j38]Zhaosong Lu, Xiaojun Chen:
Generalized Conjugate Gradient Methods for ℓ1 Regularized Convex Quadratic Programming with Finite Convergence. Math. Oper. Res. 43(1): 275-303 (2018) - [j37]Zhaosong Lu, Xiaorui Li:
Sparse Recovery via Partial Regularization: Models, Theory, and Algorithms. Math. Oper. Res. 43(4): 1290-1316 (2018) - 2017
- [j36]Zhaosong Lu, Yong Zhang, Jian Lu:
\(\ell _p\) Regularized low-rank approximation via iterative reweighted singular value minimization. Comput. Optim. Appl. 68(3): 619-642 (2017) - [j35]Zhaosong Lu:
Randomized Block Proximal Damped Newton Method for Composite Self-Concordant Minimization. SIAM J. Optim. 27(3): 1910-1942 (2017) - [j34]Xiaojun Chen, Lei Guo, Zhaosong Lu, Jane J. Ye:
An Augmented Lagrangian Method for Non-Lipschitz Nonconvex Programming. SIAM J. Numer. Anal. 55(1): 168-193 (2017) - [j33]Zhaosong Lu, Lin Xiao:
A Randomized Nonmonotone Block Proximal Gradient Method for a Class of Structured Nonlinear Programming. SIAM J. Numer. Anal. 55(6): 2930-2955 (2017) - 2016
- [j32]Fengmin Xu, Zhaosong Lu, Zongben Xu:
An efficient optimization approach for a cardinality-constrained index tracking problem. Optim. Methods Softw. 31(2): 258-271 (2016) - [j31]Xiaojun Chen, Zhaosong Lu, Ting Kei Pong:
Penalty Methods for a Class of Non-Lipschitz Optimization Problems. SIAM J. Optim. 26(3): 1465-1492 (2016) - [i13]Zhaosong Lu:
Randomized block proximal damped Newton method for composite self-concordant minimization. CoRR abs/1607.00101 (2016) - 2015
- [j30]Zhaosong Lu, Lin Xiao:
On the complexity analysis of randomized block-coordinate descent methods. Math. Program. 152(1-2): 615-642 (2015) - [j29]Zhaosong Lu, Yong Zhang, Xiaorui Li:
Penalty decomposition methods for rank minimization. Optim. Methods Softw. 30(3): 531-558 (2015) - [j28]Sen Yang, Zhaosong Lu, Xiaotong Shen, Peter Wonka, Jieping Ye:
Fused Multiple Graphical Lasso. SIAM J. Optim. 25(2): 916-943 (2015) - [j27]Qihang Lin, Zhaosong Lu, Lin Xiao:
An Accelerated Randomized Proximal Coordinate Gradient Method and its Application to Regularized Empirical Risk Minimization. SIAM J. Optim. 25(4): 2244-2273 (2015) - [j26]Zheng Wang, Ming-Jun Lai, Zhaosong Lu, Wei Fan, Hasan Davulcu, Jieping Ye:
Orthogonal Rank-One Matrix Pursuit for Low Rank Matrix Completion. SIAM J. Sci. Comput. 37(1) (2015) - [j25]Michael Ulbrich, Zaiwen Wen, Chao Yang, Dennis Klöckner, Zhaosong Lu:
A Proximal Gradient Method for Ensemble Density Functional Theory. SIAM J. Sci. Comput. 37(4) (2015) - [i12]Zhaosong Lu:
A Nonmonotone Projected Gradient Method for Optimization over Sparse Symmetric Sets. CoRR abs/1509.08581 (2015) - [i11]Zhaosong Lu, Xiaorui Li:
Sparse Recovery via Partial Regularization: Models, Theory and Algorithms. CoRR abs/1511.07293 (2015) - [i10]Zhaosong Lu, Xiaojun Chen:
Generalized Conjugate Gradient Methods for ℓ1 Regularized Convex Quadratic Programming with Finite Convergence. CoRR abs/1511.07837 (2015) - 2014
- [j24]Zhaosong Lu:
Iterative hard thresholding methods for l0 regularized convex cone programming. Math. Program. 147(1-2): 125-154 (2014) - [j23]Zhaosong Lu:
Iterative reweighted minimization methods for lp regularized unconstrained nonlinear programming. Math. Program. 147(1-2): 277-307 (2014) - [c5]Zheng Wang, Ming-Jun Lai, Zhaosong Lu, Wei Fan, Hasan Davulcu, Jieping Ye:
Rank-One Matrix Pursuit for Matrix Completion. ICML 2014: 91-99 - [c4]Qihang Lin, Zhaosong Lu, Lin Xiao:
An Accelerated Proximal Coordinate Gradient Method. NIPS 2014: 3059-3067 - [i9]Zheng Wang, Ming-Jun Lai, Zhaosong Lu, Wei Fan, Hasan Davulcu, Jieping Ye:
Orthogonal Rank-One Matrix Pursuit for Low Rank Matrix Completion. CoRR abs/1404.1377 (2014) - 2013
- [j22]Dan Zhang, Zhaosong Lu:
Assessing the Value of Dynamic Pricing in Network Revenue Management. INFORMS J. Comput. 25(1): 102-115 (2013) - [j21]Yong Zhang, Bin Dong, Zhaosong Lu:
ℓ0 Minimization for wavelet frame based image restoration. Math. Comput. 82(282): 995-1015 (2013) - [j20]Zhaosong Lu:
Primal-dual first-order methods for a class of cone programming. Optim. Methods Softw. 28(6): 1262-1281 (2013) - [j19]Zhaosong Lu, Yong Zhang:
Sparse Approximation via Penalty Decomposition Methods. SIAM J. Optim. 23(4): 2448-2478 (2013) - [j18]Zhaosong Lu, Ting Kei Pong:
Computing Optimal Experimental Designs via Interior Point Method. SIAM J. Matrix Anal. Appl. 34(4): 1556-1580 (2013) - [c3]Pinghua Gong, Changshui Zhang, Zhaosong Lu, Jianhua Huang, Jieping Ye:
A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems. ICML (2) 2013: 37-45 - [c2]Jiayu Zhou, Zhaosong Lu, Jimeng Sun, Lei Yuan, Fei Wang, Jieping Ye:
FeaFiner: biomarker identification from medical data through feature generalization and selection. KDD 2013: 1034-1042 - [i8]Pinghua Gong, Changshui Zhang, Zhaosong Lu, Jianhua Huang, Jieping Ye:
A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems. CoRR abs/1303.4434 (2013) - [i7]Zhaosong Lu, Lin Xiao:
On the Complexity Analysis of Randomized Block-Coordinate Descent Methods. CoRR abs/1305.4723 (2013) - [i6]Zhaosong Lu, Lin Xiao:
Randomized Block Coordinate Non-Monotone Gradient Method for a Class of Nonlinear Programming. CoRR abs/1306.5918 (2013) - 2012
- [j17]Zhaosong Lu, Ting Kei Pong, Yong Zhang:
An alternating direction method for finding Dantzig selectors. Comput. Stat. Data Anal. 56(12): 4037-4046 (2012) - [j16]Zhaosong Lu, Renato D. C. Monteiro, Ming Yuan:
Convex optimization methods for dimension reduction and coefficient estimation in multivariate linear regression. Math. Program. 131(1-2): 163-194 (2012) - [j15]Zhaosong Lu, Yong Zhang:
An augmented Lagrangian approach for sparse principal component analysis. Math. Program. 135(1-2): 149-193 (2012) - [i5]Zhaosong Lu, Yong Zhang:
Sparse Approximation via Penalty Decomposition Methods. CoRR abs/1205.2334 (2012) - [i4]Zhaosong Lu:
Iterative Reweighted Minimization Methods for $l_p$ Regularized Unconstrained Nonlinear Programming. CoRR abs/1210.0066 (2012) - [i3]Zhaosong Lu:
Iterative Hard Thresholding Methods for $l_0$ Regularized Convex Cone Programming. CoRR abs/1211.0056 (2012) - 2011
- [j14]Guanghui Lan, Zhaosong Lu, Renato D. C. Monteiro:
Primal-dual first-order methods with O(1/e) iteration-complexity for cone programming. Math. Program. 126(1): 1-29 (2011) - [j13]Zhaosong Lu:
A computational study on robust portfolio selection based on a joint ellipsoidal uncertainty set. Math. Program. 126(1): 193-201 (2011) - [j12]Zhaosong Lu:
Robust portfolio selection based on a joint ellipsoidal uncertainty set. Optim. Methods Softw. 26(1): 89-104 (2011) - [j11]Zhaosong Lu, Ting Kei Pong:
Minimizing Condition Number via Convex Programming. SIAM J. Matrix Anal. Appl. 32(4): 1193-1211 (2011) - [c1]Yong Zhang, Zhaosong Lu:
Penalty Decomposition Methods for Rank Minimization. NIPS 2011: 46-54 - [i2]Yong Zhang, Bin Dong, Zhaosong Lu:
ℓ0 Minimization for Wavelet Frame Based Image Restoration. CoRR abs/1105.2782 (2011) - 2010
- [j10]Zhaosong Lu:
Adaptive First-Order Methods for General Sparse Inverse Covariance Selection. SIAM J. Matrix Anal. Appl. 31(4): 2000-2016 (2010)
2000 – 2009
- 2009
- [j9]Zhaosong Lu, Renato D. C. Monteiro, Jerome W. O'Neal:
An iterative solver-based long-step infeasible primal-dual path-following algorithm for convex QP based on a class of preconditioners. Optim. Methods Softw. 24(1): 123-143 (2009) - [j8]Zhaosong Lu:
Smooth Optimization Approach for Sparse Covariance Selection. SIAM J. Optim. 19(4): 1807-1827 (2009) - [i1]Zhaosong Lu, Yong Zhang:
An Augmented Lagrangian Approach for Sparse Principal Component Analysis. CoRR abs/0907.2079 (2009) - 2007
- [j7]Zhaosong Lu, Arkadi Nemirovski, Renato D. C. Monteiro:
Large-scale semidefinite programming via a saddle point Mirror-Prox algorithm. Math. Program. 109(2-3): 211-237 (2007) - [j6]Zhaosong Lu, Renato D. C. Monteiro:
A modified nearly exact method for solving low-rank trust region subproblem. Math. Program. 109(2-3): 385-411 (2007) - [j5]Zhaosong Lu, Renato D. C. Monteiro:
Limiting behavior of the Alizadeh-Haeberly-Overton weighted paths in semidefinite programming. Optim. Methods Softw. 22(5): 849-870 (2007) - 2006
- [j4]Zhaosong Lu, Renato D. C. Monteiro, Jerome W. O'Neal:
An Iterative Solver-Based Infeasible Primal-Dual Path-Following Algorithm for Convex Quadratic Programming. SIAM J. Optim. 17(1): 287-310 (2006) - 2005
- [j3]Zhaosong Lu, Renato D. C. Monteiro:
Error Bounds and Limiting Behavior of Weighted Paths Associated with the SDP Map X1/2SX1/2. SIAM J. Optim. 15(2): 348-374 (2005) - [j2]Zhaosong Lu, Renato D. C. Monteiro:
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. SIAM J. Optim. 15(4): 1147-1154 (2005) - 2004
- [j1]Cláudio Nogueira de Meneses, Zhaosong Lu, Carlos A. S. Oliveira, Panos M. Pardalos:
Optimal Solutions for the Closest-String Problem via Integer Programming. INFORMS J. Comput. 16(4): 419-429 (2004)
Coauthor Index
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