A Class of Weighted Low Rank Approximation of the Positive Semidefinite Hankel Matrix. - Jianchao Bai; Xuefeng Duan; Kexin Cheng; Xuewei Zhang (J. Appl. Math., 2015)

On the low rank solution of the Q-weighted nearest correlation matrix problem. - Xue-Feng Duan; Jianchao Bai; Jiao-Fen Li; Jing-Jing Peng (Numer. Linear Algebra Appl., 2016)

A general preconditioner for linear complementarity problem with an M-matrix. - Ping-Fan Dai; Jicheng Li; Yao-Tang Li; Jianchao Bai (J. Comput. Appl. Math., 2017)

Generalized symmetric ADMM for separable convex optimization. - Jianchao Bai; Jicheng Li; Fengmin Xu; Hongchao Zhang (Comput. Optim. Appl., 2018)

A class of multilevel structured low-rank approximation arising in material processing. - Jianchao Bai; Jicheng Li; Junkai Deng (Int. J. Comput. Math., 2018)

A novel method for a class of structured low-rank minimizations with equality constraint. - Jianchao Bai; Jicheng Li; Fengmin Xu; Pingfan Dai (J. Comput. Appl. Math., 2018)

A parameterized proximal point algorithm for separable convex optimization. - Jianchao Bai; Hongchao Zhang; Jicheng Li (Optim. Lett., 2018)

A Family of Multi-Parameterized Proximal Point Algorithms. - Jianchao Bai; Ke Guo; Xiaokai Chang (IEEE Access, 2019)

A preconditioned two-step modulus-based matrix splitting iteration method for linear complementarity problem. - Ping-Fan Dai; Jicheng Li; Jianchao Bai; Jinming Qiu (Appl. Math. Comput., 2019)

New error bounds for linear complementarity problems of S-Nekrasov matrices and B-S-Nekrasov matrices. - Ping-Fan Dai; Jicheng Li; Jianchao Bai; Liqiang Dong (Comput. Appl. Math., 2019)

Convergence Revisit on Generalized Symmetric ADMM. - Jianchao Bai; Xiaokai Chang; Jicheng Li; Fengmin Xu (CoRR, 2019)

Accelerated Symmetric ADMM and Its Applications in Signal Processing. - Jianchao Bai; Junli Liang; Ke Guo; Yang Jing (CoRR, 2019)

General parameterized proximal point algorithm with applications in statistical learning. - Jianchao Bai; Jicheng Li; Pingfan Dai; Jiaofen Li (Int. J. Comput. Math., 2019)

Convergence on a symmetric accelerated stochastic ADMM with larger stepsizes. - Jianchao Bai; Deren Han; Hao Sun; Hongchao Zhang (CoRR, 2021)

Iteration complexity analysis of a partial LQP-based alternating direction method of multipliers. - Jianchao Bai; Yuxue Ma; Hao Sun; Miao Zhang (CoRR, 2021)

A New Insight on Augmented Lagrangian Method and Its Extensions. - Jianchao Bai (CoRR, 2021)

A Projected Extrapolated Gradient Method with Larger Step Size for Monotone Variational Inequalities. - Xiaokai Chang; Jianchao Bai (J. Optim. Theory Appl., 2021)

A Joint Analysis of Multi-Paradigm fMRI Data With Its Application to Cognitive Study. - Yuntong Bai; Yun Gong; Jianchao Bai; Jingyu Liu 001; Hong-Wen Deng; Vince D. Calhoun; Yu-Ping Wang 002 (IEEE Trans. Medical Imaging, 2021)

An inexact accelerated stochastic ADMM for separable convex optimization. - Jianchao Bai; William W. Hager; Hongchao Zhang (Comput. Optim. Appl., 2022)

An accelerated stochastic ADMM for nonconvex and nonsmooth finite-sum optimization. - Yuxuan Zeng; Zhiguo Wang; Jianchao Bai; Xiaojing Shen (Autom., 2024)

A systematic DNN weight pruning framework based on symmetric accelerated stochastic ADMM. - Ming Yuan; Jianchao Bai; Feng Jiang; Lin Du (Neurocomputing, 2024)

Reweighted Alternating Direction Method of Multipliers for DNN weight pruning. - Ming Yuan; Lin Du; Feng Jiang; Jianchao Bai; Guanrong Chen (Neural Networks, 2024)

A General Preconditioner for Tensor Complementarity Problems. - Ping-Fan Dai; Jianchao Bai; Jicheng Li (J. Sci. Comput., 2024)

A New Insight on Augmented Lagrangian Method with Applications in Machine Learning. - Jianchao Bai; Linyuan Jia; Zheng Peng 002 (J. Sci. Comput., 2024)

An inexact ADMM for separable nonconvex and nonsmooth optimization. - Jianchao Bai; Miao Zhang; Hongchao Zhang (Comput. Optim. Appl., 2025)

Generalized Asymmetric Forward-Backward-Adjoint Algorithms for Convex-Concave Saddle-Point Problem. - Jianchao Bai; Yang Chen; Xue Yu; Hongchao Zhang (J. Sci. Comput., 2025)