131 citations · 192 across the 29 of their papers we have counts for
8 papers · 1 filter
Majorized Semi-proximal Alternating Coordinate Method for Nonsmooth Convex-Concave Minimax Optimization
Yu-Hong Dai, Jiani Wang, Liwei Zhang
Minimax optimization problems are an important class of optimization problems arising from modern machine learning and traditional research areas. While there have been many numeri…
Optimization with Least Constraint Violation
Yu-Hong Dai, Liwei Zhang
Study about theory and algorithms for constrained optimization usually assumes that the feasible region of the optimization problem is nonempty. However, there are many important p…
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…
Linear convergence of random dual coordinate incremental aggregated gradient methods
Hui Zhang, Yu-Hong Dai, Lei Guo
In this paper, we consider the dual formulation of minimizing with the index sets and being large. To address the…
A primal-dual interior-point relaxation method with global and rapidly local convergence for nonlinear programs
Xin-Wei Liu, Yu-Hong Dai, Ya-Kui Huang
Based on solving an equivalent parametric equality constrained mini-max problem of the classic logarithmic-barrier subproblem, we present a novel primal-dual interior-point relaxat…