Achieving geometric convergence for distributed optimization with Barzilai-Borwein step sizes. - Juan Gao; Xin-Wei Liu; Yu-Hong Dai; Yakui Huang; Peng Yang 015 (Sci. China Inf. Sci., 2022)

On the acceleration of the Barzilai-Borwein method. - Yakui Huang; Yu-Hong Dai; Xin-Wei Liu; Hongchao Zhang (Comput. Optim. Appl., 2022)

A gradient-type noise-tolerant finite-time neural network for convex optimization. - Dan Wang; Xin-Wei Liu (Neurocomputing, 2022)

A primal-dual interior-point relaxation method with global and rapidly local convergence for nonlinear programs. - Xin-Wei Liu; Yu-Hong Dai; Yakui Huang (Math. Methods Oper. Res., 2022)

A varying-parameter fixed-time gradient-based dynamic network for convex optimization. - Dan Wang; Xin-Wei Liu (Neural Networks, 2023)

IPRQP: a primal-dual interior-point relaxation algorithm for convex quadratic programming. - Rui-Jin Zhang; Xin-Wei Liu; Yu-Hong Dai (J. Glob. Optim., 2023)

A Robust Fixed-Time Piecewise Dynamic Network for Convex Programming. - Dan Wang; Huiyun Li; Xin-Wei Liu (Neural Process. Lett., 2023)

IPRSDP: a primal-dual interior-point relaxation algorithm for semidefinite programming. - Rui-Jin Zhang; Xin-Wei Liu; Yu-Hong Dai (Comput. Optim. Appl., 2024)