Conjugate gradient method for the linear complementarity problem with S-matrix. - Dong-Hui Li; Yi-Yong Nie; Jin-Ping Zeng; Qing-Na Li (Math. Comput. Model., 2008)

Newton's Method for Computing the Nearest Correlation Matrix with a Simple Upper Bound. - Qingna Li; Donghui Li; Houduo Qi (J. Optim. Theory Appl., 2010)

Block relaxation and majorization methods for the nearest correlation matrix with factor structure. - Qingna Li; Houduo Qi; Naihua Xiu (Comput. Optim. Appl., 2011)

A projected semismooth Newton method for problems of calibrating least squares covariance matrix. - Qingna Li; Donghui Li (Oper. Res. Lett., 2011)

A Sequential Semismooth Newton Method for the Nearest Low-rank Correlation Matrix Problem. - Qingna Li; Houduo Qi (SIAM J. Optim., 2011)

Unique Decomposition and a New Model for the Ground Moving Target Indication Problem. - Qingna Li; Li He; Lijuan Qi; Robert Wang 001 (J. Optim. Theory Appl., 2017)

Ordinal Distance Metric Learning with MDS for Image Ranking. - Panpan Yu; Qingna Li (Asia Pac. J. Oper. Res., 2018)

A quadratic penalty method for hypergraph matching. - Chunfeng Cui; Qingna Li; Liqun Qi 001; Hong Yan 001 (J. Glob. Optim., 2018)

A semismooth Newton method for support vector classification and regression. - Juan Yin; Qingna Li (Comput. Optim. Appl., 2019)

Feasibility and a fast algorithm for Euclidean distance matrix optimization with ordinal constraints. - Si-Tong Lu; Miao Zhang; Qing-Na Li (Comput. Optim. Appl., 2020)

A Semismooth-Newton's-Method-Based Linearization and Approximation Approach for Kernel Support Vector Machines. - Chen Jiang; Qingna Li (CoRR, 2020)

A Euclidean distance matrix model for protein molecular conformation. - Fengzhen Zhai; Qingna Li (J. Glob. Optim., 2020)

An efficient augmented Lagrangian method for support vector machine. - Yinqiao Yan; Qingna Li (Optim. Methods Softw., 2020)

A Euclidean Distance Matrix Model for Convex Clustering. - Zhao-Wei Wang; Xiao-Wen Liu; Qing-Na Li (CoRR, 2021)

An Efficient Quadratic Programming Relaxation Based Algorithm for Large-Scale MIMO Detection. - Ping-Fan Zhao; Qingna Li; Wei-Kun Chen; Ya-Feng Liu (SIAM J. Optim., 2021)

A Unified Framework and a Case Study for Hyperparameter Selection in Machine Learning via Bilevel Optimization. - Zhen Li; Yaru Qian; Qingna Li (DSIT, 2022)

An Efficient Method for Sample Adversarial Perturbations against Nonlinear Support Vector Machines. - Wen Su; Qingna Li (DSIT, 2022)

An Ordinal Weighted EDM Model for Nonmetric Multidimensional Scaling. - Qing-Na Li; Chi Zhang; Mengzhi Cao (Asia Pac. J. Oper. Res., 2022)

Optimization Models and Interpretations for Three Types of Adversarial Perturbations against Support Vector Machines. - Wen Su; Qingna Li; Chunfeng Cui (CoRR, 2022)

Bilevel hyperparameter optimization for support vector classification: theoretical analysis and a solution method. - Qingna Li; Zhen Li; Alain B. Zemkoho (Math. Methods Oper. Res., 2022)

An Adaptive Sieving Strategy for the Complex Lasso Problem. - Xiaoning Bai; Yuge Ye; Qingna Li (DSIT, 2023)

A majorization penalty method for SVM with sparse constraint. - Si-Tong Lu; Qingna Li (Optim. Methods Softw., 2023)

A facial reduction approach for the single source localization problem. - He Shi; Qingna Li (J. Glob. Optim., 2023)

An Efficient Quadratic Penalty Method for a Class of Graph Clustering Problems. - Wenshun Teng; Qingna Li (CoRR, 2025)