Defeng Sun
Orcid: 0000-0002-6699-6272
According to our database1,
Defeng Sun
authored at least 112 papers
between 1997 and 2024.
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Bibliography
2024
An Efficient Sieving-Based Secant Method for Sparse Optimization Problems with Least-Squares Constraints.
SIAM J. Optim., 2024
Optim. Methods Softw., 2024
INFORMS J. Comput., 2024
CoRR, 2024
2023
Zero-norm regularized problems: equivalent surrogates, proximal MM method and statistical error bound.
Comput. Optim. Appl., November, 2023
IEEE Trans. Neural Networks Learn. Syst., September, 2023
A metaheuristic algorithm for a locomotive routing problem arising in the steel industry.
Eur. J. Oper. Res., July, 2023
MARS: A Second-Order Reduction Algorithm for High-Dimensional Sparse Precision Matrices Estimation.
J. Mach. Learn. Res., 2023
Randomly Projected Convex Clustering Model: Motivation, Realization, and Cluster Recovery Guarantees.
CoRR, 2023
Beyond ADMM: A Unified Client-Variance-Reduced Adaptive Federated Learning Framework.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
A Dimension Reduction Technique for Large-Scale Structured Sparse Optimization Problems with Application to Convex Clustering.
SIAM J. Optim., September, 2022
QPPAL: A Two-phase Proximal Augmented Lagrangian Method for High-dimensional Convex Quadratic Programming Problems.
ACM Trans. Math. Softw., 2022
SIAM J. Imaging Sci., 2022
An augmented Lagrangian method with constraint generation for shape-constrained convex regression problems.
Math. Program. Comput., 2022
Int. J. Prod. Res., 2022
Beyond ADMM: A Unified Client-variance-reduced Adaptive Federated Learning Framework.
CoRR, 2022
2021
Semi-proximal Augmented Lagrangian-Based Decomposition Methods for Primal Block-Angular Convex Composite Quadratic Conic Programming Problems.
INFORMS J. Optim., July, 2021
An Efficient Linearly Convergent Regularized Proximal Point Algorithm for Fused Multiple Graphical Lasso Problems.
SIAM J. Math. Data Sci., 2021
An Inexact Augmented Lagrangian Method for Second-Order Cone Programming with Applications.
SIAM J. Optim., 2021
On the equivalence of inexact proximal ALM and ADMM for a class of convex composite programming.
Math. Program., 2021
A Fast Globally Linearly Convergent Algorithm for the Computation of Wasserstein Barycenters.
J. Mach. Learn. Res., 2021
J. Mach. Learn. Res., 2021
An exact algorithm for the unidirectional quay crane scheduling problem with vessel stability.
Eur. J. Oper. Res., 2021
2020
SIAM J. Optim., 2020
An Asymptotically Superlinearly Convergent Semismooth Newton Augmented Lagrangian Method for Linear Programming.
SIAM J. Optim., 2020
Spectral Operators of Matrices: Semismoothness and Characterizations of the Generalized Jacobian.
SIAM J. Optim., 2020
SDPNAL+: A Matlab software for semidefinite programming with bound constraints (version 1.0).
Optim. Methods Softw., 2020
A multi-stage convex relaxation approach to noisy structured low-rank matrix recovery.
Math. Program. Comput., 2020
An efficient Hessian based algorithm for solving large-scale sparse group Lasso problems.
Math. Program., 2020
On the efficient computation of a generalized Jacobian of the projector over the Birkhoff polytope.
Math. Program., 2020
2019
SIAM J. Matrix Anal. Appl., 2019
SIAM J. Optim., 2019
Computing the Best Approximation over the Intersection of a Polyhedral Set and the Doubly Nonnegative Cone.
SIAM J. Optim., 2019
A block symmetric Gauss-Seidel decomposition theorem for convex composite quadratic programming and its applications.
Math. Program., 2019
On the R-superlinear convergence of the KKT residuals generated by the augmented Lagrangian method for convex composite conic programming.
Math. Program., 2019
Solving the OSCAR and SLOPE Models Using a Semismooth Newton-Based Augmented Lagrangian Method.
J. Mach. Learn. Res., 2019
Eur. J. Oper. Res., 2019
A sparse semismooth Newton based proximal majorization-minimization algorithm for nonconvex square-root-loss regression problems.
CoRR, 2019
On the Closed-form Proximal Mapping and Efficient Algorithms for Exclusive Lasso Models.
CoRR, 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
Linear Rate Convergence of the Alternating Direction Method of Multipliers for Convex Composite Programming.
Math. Oper. Res., 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
2017
Characterization of the Robust Isolated Calmness for a Class of Conic Programming Problems.
SIAM J. Optim., 2017
An efficient inexact symmetric Gauss-Seidel based majorized ADMM for high-dimensional convex composite conic programming.
Math. Program., 2017
A note on the convergence of ADMM for linearly constrained convex optimization problems.
Comput. Optim. Appl., 2017
2016
SIAM J. Optim., 2016
A Majorized ADMM with Indefinite Proximal Terms for Linearly Constrained Convex Composite Optimization.
SIAM J. Optim., 2016
Math. Program., 2016
A Schur complement based semi-proximal ADMM for convex quadratic conic programming and extensions.
Math. Program., 2016
A semismooth Newton-CG based dual PPA for matrix spectral norm approximation problems.
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
Comput. Stat. Data Anal., 2016
2015
A Convergent 3-Block SemiProximal Alternating Direction Method of Multipliers for Conic Programming with 4-Type Constraints.
SIAM J. Optim., 2015
SDPNAL \(+\) : a majorized semismooth Newton-CG augmented Lagrangian method for semidefinite programming with nonnegative constraints.
Math. Program. Comput., 2015
A Convergent 3-Block Semi-Proximal ADMM for Convex Minimization Problems with One Strongly Convex Block.
Asia Pac. J. Oper. Res., 2015
Proceedings of the IEEE International Conference on Information and Automation, 2015
2014
SIAM J. Optim., 2014
A partial proximal point algorithm for nuclear norm regularized matrix least squares problems.
Math. Program. Comput., 2014
First order optimality conditions for mathematical programs with semidefinite cone complementarity constraints.
Math. Program., 2014
Proceedings of the IEEE/ASME International Conference on Advanced Intelligent Mechatronics, 2014
2013
Hankel Matrix Rank Minimization with Applications to System Identification and Realization.
SIAM J. Matrix Anal. Appl., 2013
A Proximal Point Algorithm for Log-Determinant Optimization with Group Lasso Regularization.
SIAM J. Optim., 2013
Benders approach for the raw material transportation scheduling problem in steel industry.
Proceedings of the 10th IEEE International Conference on Control and Automation, 2013
2012
An Inexact Accelerated Proximal Gradient Method for Large Scale Linearly Constrained Convex SDP.
SIAM J. Optim., 2012
Math. Program., 2012
2010
SIAM J. Optim., 2010
Solving Log-Determinant Optimization Problems by a Newton-CG Primal Proximal Point Algorithm.
SIAM J. Optim., 2010
Correlation stress testing for value-at-risk: an unconstrained convex optimization approach.
Comput. Optim. Appl., 2010
2009
Nonsmooth and Smoothing Methods for Nonlinear Complementarity Problems and Variational Inequalities.
Proceedings of the Encyclopedia of Optimization, Second Edition, 2009
Calibrating Least Squares Semidefinite Programming with Equality and Inequality Constraints.
SIAM J. Matrix Anal. Appl., 2009
2008
Constraint Nondegeneracy, Strong Regularity, and Nonsingularity in Semidefinite Programming.
SIAM J. Optim., 2008
The SC<sup>1</sup> property of the squared norm of the SOC Fischer-Burmeister function.
Oper. Res. Lett., 2008
The rate of convergence of the augmented Lagrangian method for nonlinear semidefinite programming.
Math. Program., 2008
Math. Oper. Res., 2008
2007
A Dual Optimization Approach to Inverse Quadratic Eigenvalue Problems with Partial Eigenstructure.
SIAM J. Sci. Comput., 2007
2006
A Quadratically Convergent Newton Method for Computing the Nearest Correlation Matrix.
SIAM J. Matrix Anal. Appl., 2006
The Strong Second-Order Sufficient Condition and Constraint Nondegeneracy in Nonlinear Semidefinite Programming and Their Implications.
Math. Oper. Res., 2006
A Smoothing Newton-Type Algorithm of Stronger Convergence for the Quadratically Constrained Convex Quadratic Programming.
Comput. Optim. Appl., 2006
2005
Strong Semismoothness of the Fischer-Burmeister SDC and SOC Complementarity Functions.
Math. Program., 2005
Semismoothness of solutions to generalized equations and the Moreau-Yosida regularization.
Math. Program., 2005
2004
A Squared Smoothing Newton Method for Nonsmooth Matrix Equations and Its Applications in Semidefinite Optimization Problems.
SIAM J. Optim., 2004
Sub-quadratic convergence of a smoothing Newton algorithm for the <i>P</i> <sub><i>0</i></sub>- and monotone LCP.
Math. Program., 2004
2003
Solving Karush--Kuhn--Tucker Systems via the Trust Region and the Conjugate Gradient Methods.
SIAM J. Optim., 2003
Semismooth Homeomorphisms and Strong Stability of Semidefinite and Lorentz Complementarity Problems.
Math. Oper. Res., 2003
Complementarity Functions and Numerical Experiments on Some Smoothing Newton Methods for Second-Order-Cone Complementarity Problems.
Comput. Optim. Appl., 2003
2002
Strong Semismoothness of Eigenvalues of Symmetric Matrices and Its Application to Inverse Eigenvalue Problems.
SIAM J. Numer. Anal., 2002
A feasible semismooth asymptotically Newton method for mixed complementarity problems.
Math. Program., 2002
2001
SIAM J. Optim., 2001
Oper. Res. Lett., 2001
2000
A new look at smoothing Newton methods for nonlinear complementarity problems and box constrained variational inequalities.
Math. Program., 2000
Improving the convergence of non-interior point algorithms for nonlinear complementarity problems.
Math. Comput., 2000
1999
A New Unconstrained Differentiable Merit Function for Box Constrained Variational Inequality Problems and a Damped Gauss-Newton Method.
SIAM J. Optim., 1999
Properties of the Moreau-Yosida regularization of a piecewise C<sup>2</sup> convex function.
Math. Program., 1999
Comput. Optim. Appl., 1999
1998
SIAM J. Optim., 1998
SIAM J. Optim., 1998
Global and superlinear convergence of the smoothing Newton method and its application to general box constrained variational inequalities.
Math. Comput., 1998
1997
Newton and Quasi-Newton Methods for a Class of Nonsmooth Equations and Related Problems.
SIAM J. Optim., 1997