Lingchen Kong

发表

Exact Low-Rank Matrix Recovery via Nonconvex Schatten P-Minimization

Naihua Xiu, Lingchen Kong, 2013, Asia Pac. J. Oper. Res..

Sufficient Conditions for Low-rank Matrix Recovery, Translated from Sparse Signal Recovery pdf

Naihua Xiu, Levent Tunçel, Lingchen Kong, 2011, ArXiv.

The solution set structure of monotone linear complementarity problems over second-order cone

Naihua Xiu, Lingchen Kong, Jiye Han, 2008, Oper. Res. Lett..

Monotonicity of Löwner operators and its applications to symmetric cone complementarity problems

Naihua Xiu, Levent Tunçel, Lingchen Kong, 2012, Math. Program..

New RIC Bounds via l_q-minimization with 0 pdf

Naihua Xiu, Shenglong Zhou, Ziyan Luo, 2013, ArXiv.

Iterative reweighted methods for $$\ell _1-\ell _p$$ℓ1-ℓp minimization

Yan Li, Houduo Qi, Lingchen Kong, 2018, Comput. Optim. Appl..

Existence and Uniqueness of Solutions for Homogeneous Cone Complementarity Problems

Naihua Xiu, Levent Tunçel, Lingchen Kong, 2012, J. Optim. Theory Appl..

Classical Multidimensional Scaling: A Subspace Perspective, Over-Denoising, and Outlier Detection

Lingchen Kong, Hou-Duo Qi, Chuanqi Qi, 2019, IEEE Transactions on Signal Processing.

Alternating direction method of multipliers for nonconvex fused regression problems

Ling Li, Wanquan Liu, Lingchen Kong, 2019, Comput. Stat. Data Anal..

The Uniqueness and Greedy Method for Quadratic Compressive Sensing

Jun Fan, Naihua Xiu, Liqun Wang, 2016, 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA).

The linearized alternating direction method of multipliers for sparse group LAD model

Huifang Wang, Lingchen Kong, Jiyuan Tao, 2019, Optim. Lett..

Equivalent Conditions for Jacobian Nonsingularity in Linear Symmetric Cone Programming

Naihua Xiu, Levent Tunçel, Lingchen Kong, 2010, J. Optim. Theory Appl..

Rank-One and Transformed Sparse Decomposition for Dynamic Cardiac MRI

Lingchen Kong, Xianchao Xiu, Lingchen Kong, 2015, BioMed research international.

A Highly Efficient Joint Sparsity Constrained Robust Principal Component Analysis for Fault Diagnosis

Wanquan Liu, Lingchen Kong, Xianchao Xiu, 2020, 2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS).

A semismooth Newton method for nonlinear symmetric cone programming

Qingmin Meng, Lingchen Kong, 2012, Math. Methods Oper. Res..

l1-norm quantile regression screening rule via the dual circumscribed sphere

Lingchen Kong, Pan Shang, 2020 .

Adaptive trajectory tracking control strategy of intelligent vehicle

Xuan Zhao, Yue Hao, Lingchen Kong, 2020 .

Double fused Lasso penalized LAD for matrix regression

Mei Li, Lingchen Kong, Lingchen Kong, 2019, Appl. Math. Comput..

ADMM for High-Dimensional Sparse Penalized Quantile Regression

Shiqian Ma, Jun Fan, Hui Zou, 2018, Technometrics.

New smooth C-functions for symmetric cone complementarity problems

Naihua Xiu, Lingchen Kong, 2007, Optim. Lett..

A note on an inequality involving Jordan product in Euclidean Jordan algebras

Lingchen Kong, Guo-Qiang Wang, Jiyuan Tao, 2016, Optim. Lett..

tSSNALM: A fast two-stage semi-smooth Newton augmented Lagrangian method for sparse CCA

Ying Yang, Wanquan Liu, Lingchen Kong, 2020, Appl. Math. Comput..

Sufficiency of linear transformations on Euclidean Jordan algebras

Lingchen Kong, Jiye Han, Linxia Qin, 2009, Optim. Lett..

Exact Recovery for Sparse Signal via Weighted l_1 Minimization pdf

Naihua Xiu, Shenglong Zhou, Lingchen Kong, 2013, ArXiv.

Linear Program Relaxation of Sparse Nonnegative Recovery in Compressive Sensing Microarrays

Yu Li, Naihua Xiu, Lingchen Kong, 2012, Comput. Math. Methods Medicine.

Laplacian regularized robust principal component analysis for process monitoring

Ying Yang, Lingchen Kong, Xianchao Xiu, 2020 .

Safe feature screening rules for the regularized Huber regression

Lingchen Kong, Pan Shang, Shanshan Pan, 2020, Appl. Math. Comput..

The Nonnegative Zero-Norm Minimization Under Generalized Z-Matrix Measurement

Naihua Xiu, Ziyan Luo, Lingchen Kong, 2014, J. Optim. Theory Appl..

Nonconvex mixed matrix minimization

Ying Yang, Lingchen Kong, Meijuan Shang, 2019, Math. Found. Comput..

RANK-MIN-ONE AND SPARSE TENSOR DECOMPOSITIONFOR SURVEILLANCE VIDEO

Lingchen Kong, Xianchao Xiu, 2015 .

Data-Driven Process Monitoring Using Structured Joint Sparse Canonical Correlation Analysis

Ying Yang, Wanquan Liu, Lingchen Kong, 2021, IEEE Transactions on Circuits and Systems II: Express Briefs.

A Regularized Smoothing Newton Method for Symmetric Cone Complementarity Problems

Naihua Xiu, Lingchen Kong, Jie Sun, 2008, SIAM J. Optim..

A Novel Convex Clustering Method for High-Dimensional Data Using Semiproximal ADMM

Yan Li, Lingchen Kong, Huangyue Chen, 2020, Mathematical Problems in Engineering.

Vector-Valued Implicit Lagrangian for Symmetric Cone complementarity Problems

Naihua Xiu, Levent Tunçel, Lingchen Kong, 2009, Asia Pac. J. Oper. Res..

Regularization parameter selection for low rank matrix recovery

Lingchen Kong, Pan Shang, Lingchen Kong, 2019, 1909.06960.

Double fused Lasso regularized regression with both matrix and vector valued predictors

Lingchen Kong, Zhihua Su, Mei Li, 2021, Electronic Journal of Statistics.

S-semigoodness for Low-Rank Semidefinite Matrix Recovery

Naihua Xiu, Lingchen Kong, Jie Sun, 2014 .

The Fischer-Burmeister Complementarity Function on Euclidean Jordan Algebras∗

Naihua Xiu, Levent Tunçel, Lingchen Kong, 2008 .

New Bounds for RIC in Compressed Sensing

Naihua Xiu, Lingchen Kong, Shenglong Zhou, 2013 .

Exact Low-rank Matrix Recovery via Nonconvex M p-Minimization

Naihua Xiu, Lingchen Kong, N. Xiu, 2011 .

Sparse and Low-Rank Covariance Matrix Estimation

Naihua Xiu, Shenglong Zhou, Ziyan Luo, 2015 .

Robust two-stage stochastic linear programs with moment constraints

Lingchen Kong, Sarah Yini Gao, Jie Sun, 2014 .

Clarke Generalized Jacobian of the Projection onto Symmetric Cones

Naihua Xiu, Levent Tunçel, Lingchen Kong, 2009 .

A smoothing iterative method for quantile regression with nonconvex \begin{document}$ \ell_p $\end{document} penalty

Yan Li, Shenglong Zhou, Lingchen Kong, 2016 .

$s$-Goodness for Low-Rank Matrix Recovery

Naihua Xiu, Levent Tunçel, Lingchen Kong, 2013 .