4 citations · 10 across the 4 of their papers we have counts for
9 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…
Equipping Barzilai-Borwein method with two dimensional quadratic termination property
Yakui Huang, Yu-Hong Dai, Xin-Wei Liu
A novel gradient stepsize is derived at the motivation of equipping the Barzilai-Borwein (BB) method with two dimensional quadratic termination property. A remarkable feature of th…
On the acceleration of the Barzilai-Borwein method
Yakui Huang, Yu-Hong Dai, Xin-Wei Liu +1
The Barzilai-Borwein (BB) gradient method is efficient for solving large-scale unconstrained problems to the modest accuracy and has a great advantage of being easily extended to s…
On the asymptotic convergence and acceleration of gradient methods
Yakui Huang, Yu-Hong Dai, Xin-Wei Liu +1
We consider the asymptotic behavior of a family of gradient methods, which include the steepest descent and minimal gradient methods as special instances. It is proved that each me…
Gradient methods exploiting spectral properties
Yakui Huang, Yu-Hong Dai, Xin-Wei Liu +1
We propose a new stepsize for the gradient method. It is shown that this new stepsize will converge to the reciprocal of the largest eigenvalue of the Hessian, when Dai-Yang's asym…