Xudong Li
Orcid: 0000-0002-9275-1965Affiliations:
- Fudan University, Shanghai, China
- Princeton University, NJ, USA
- National University of Singapore, Singapore
According to our database1,
Xudong Li
authored at least 17 papers
between 2016 and 2024.
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Bibliography
2024
On Geometric Connections of Embedded and Quotient Geometries in Riemannian Fixed-Rank Matrix Optimization.
Math. Oper. Res., 2024
Recursive Importance Sketching for Rank Constrained Least Squares: Algorithms and High-Order Convergence.
Oper. Res., 2024
2022
Hölderian Error Bounds and Kurdyka-Łojasiewicz Inequality for the Trust Region Subproblem.
Math. Oper. Res., November, 2022
QPPAL: A Two-phase Proximal Augmented Lagrangian Method for High-dimensional Convex Quadratic Programming Problems.
ACM Trans. Math. Softw., 2022
Solving Stackelberg Prediction Game with Least Squares Loss via Spherically Constrained Least Squares Reformulation.
Proceedings of the International Conference on Machine Learning, 2022
2021
On the equivalence of inexact proximal ALM and ADMM for a class of convex composite programming.
Math. Program., 2021
Nonconvex Factorization and Manifold Formulations are Almost Equivalent in Low-rank Matrix Optimization.
CoRR, 2021
2020
An Asymptotically Superlinearly Convergent Semismooth Newton Augmented Lagrangian Method for Linear Programming.
SIAM J. Optim., 2020
On the efficient computation of a generalized Jacobian of the projector over the Birkhoff polytope.
Math. Program., 2020
2019
A block symmetric Gauss-Seidel decomposition theorem for convex composite quadratic programming and its applications.
Math. Program., 2019
2018
On Efficiently Solving the Subproblems of a Level-Set Method for Fused Lasso Problems.
SIAM J. Optim., 2018
A Highly Efficient Semismooth Newton Augmented Lagrangian Method for Solving Lasso Problems.
SIAM J. Optim., 2018
QSDPNAL: a two-phase augmented Lagrangian method for convex quadratic semidefinite programming.
Math. Program. Comput., 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
2016
A Schur complement based semi-proximal ADMM for convex quadratic conic programming and extensions.
Math. Program., 2016
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., 2016