4 citations · 8 across the 5 of their papers we have counts for
5 papers
A novel augmented Lagrangian method of multipliers for optimization with general inequality constraints
Xin-Wei Liu, Yu-Hong Dai, Ya-Kui Huang +1
We introduce a twice differentiable augmented Lagrangian for nonlinear optimization with general inequality constraints and show that a strict local minimizer of the original probl…
A variable metric mini-batch proximal stochastic recursive gradient algorithm with diagonal Barzilai-Borwein stepsize
Tengteng Yu, Xin-Wei Liu, Yu-Hong Dai +1
Variable metric proximal gradient methods with different metric selections have been widely used in composite optimization. Combining the Barzilai-Borwein (BB) method with a diagon…
Spectral operators of matrices: semismoothness and characterizations of the generalized Jacobian
Chao Ding, Defeng Sun, Jie Sun +1
Spectral operators of matrices proposed recently in [C. Ding, D.F. Sun, J. Sun, and K.C. Toh, Math. Program. {\bf 168}, 509--531 (2018)] are a class of matrix valued functions, whi…
A primal-dual interior-point method capable of rapidly detecting infeasibility for nonlinear programs
Yu-Hong Dai, Xin-Wei Liu, Jie Sun
With the help of a logarithmic barrier augmented Lagrangian function, we can obtain closed-form solutions of slack variables of logarithmic-barrier problems of nonlinear programs.…
Spectral Operators of Matrices
Chao Ding, Defeng Sun, Jie Sun +1
The class of matrix optimization problems (MOPs) has been recognized in recent years to be a powerful tool by researchers far beyond the optimization community to model many import…