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Xudong Li 0004
Person information
- affiliation: Fudan University, Shanghai, China
- affiliation: Princeton University, NJ, USA
- affiliation: National University of Singapore, Singapore
Other persons with the same name
- Xudong Li — disambiguation page
- Xudong Li 0001
— University of Electronic Science and Technology of China, Chengdu, China
- Xudong Li 0002 — Shanghai Jiao Tong University, Shanghai, China
- Xudong Li 0003
— University of Chinese Academy of Science, Beijing, China (and 1 more)
- Xudong Li 0005 — Xihua University, Chengdu, China
- Xudong Li 0006
— Nanjing University of Science and Technology, School of Mechanical Engineering, China
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2020 – today
- 2024
- [j14]Yuetian Luo, Wen Huang
, Xudong Li
, Anru Zhang
:
Recursive Importance Sketching for Rank Constrained Least Squares: Algorithms and High-Order Convergence. Oper. Res. 72(1): 237-256 (2024) - [j13]Yuetian Luo, Xudong Li
, Anru R. Zhang
:
On Geometric Connections of Embedded and Quotient Geometries in Riemannian Fixed-Rank Matrix Optimization. Math. Oper. Res. 49(2): 782-825 (2024) - 2022
- [j12]Ziwei Zhu
, Xudong Li, Mengdi Wang
, Anru Zhang
:
Learning Markov Models Via Low-Rank Optimization. Oper. Res. 70(4): 2384-2398 (2022) - [j11]Rujun Jiang
, Xudong Li
:
Hölderian Error Bounds and Kurdyka-Łojasiewicz Inequality for the Trust Region Subproblem. Math. Oper. Res. 47(4): 3025-3050 (2022) - [j10]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): 33:1-33:27 (2022) - [c2]Jiali Wang, Wen Huang, Rujun Jiang, Xudong Li, Alex L. Wang:
Solving Stackelberg Prediction Game with Least Squares Loss via Spherically Constrained Least Squares Reformulation. ICML 2022: 22665-22679 - 2021
- [j9]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): 111-161 (2021) - [i4]Yuetian Luo, Xudong Li, Anru R. Zhang:
Nonconvex Factorization and Manifold Formulations are Almost Equivalent in Low-rank Matrix Optimization. CoRR abs/2108.01772 (2021) - [i3]Yuetian Luo, Xudong Li, Anru R. Zhang:
On Geometric Connections of Embedded and Quotient Geometries in Riemannian Fixed-rank Matrix Optimization. CoRR abs/2110.12121 (2021) - 2020
- [j8]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): 419-446 (2020) - [j7]Xudong Li
, Defeng Sun, Kim-Chuan Toh:
An Asymptotically Superlinearly Convergent Semismooth Newton Augmented Lagrangian Method for Linear Programming. SIAM J. Optim. 30(3): 2410-2440 (2020) - [i2]Yuetian Luo, Wen Huang, Xudong Li, Anru R. Zhang:
Recursive Importance Sketching for Rank Constrained Least Squares: Algorithms and High-order Convergence. CoRR abs/2011.08360 (2020)
2010 – 2019
- 2019
- [j6]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): 395-418 (2019) - 2018
- [j5]Xudong Li
, Defeng Sun
, Kim-Chuan Toh:
QSDPNAL: a two-phase augmented Lagrangian method for convex quadratic semidefinite programming. Math. Program. Comput. 10(4): 703-743 (2018) - [j4]Xudong Li
, Defeng Sun
, Kim-Chuan Toh:
A Highly Efficient Semismooth Newton Augmented Lagrangian Method for Solving Lasso Problems. SIAM J. Optim. 28(1): 433-458 (2018) - [j3]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): 1842-1866 (2018) - [c1]Xudong Li, Mengdi Wang, Anru Zhang:
Estimation of Markov Chain via Rank-constrained Likelihood. ICML 2018: 3039-3048 - [i1]Xudong Li, Mengdi Wang, Anru Zhang:
Estimation of Markov Chain via Rank-constrained Likelihood. CoRR abs/1804.00795 (2018) - 2016
- [j2]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): 1013-1041 (2016) - [j1]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): 333-373 (2016)
Coauthor Index
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last updated on 2024-09-04 01:23 CEST by the dblp team
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