4 citations · 6 across the 5 of their papers we have counts for
6 papers
Stochastic Approximation Proximal Subgradient Method for Stochastic Convex-Concave Minimax Optimization
Yu-Hong Dai, Jiani Wang, Liwei Zhang
This paper presents a stochastic approximation proximal subgradient (SAPS) method for stochastic convex-concave minimax optimization. By accessing unbiased and variance bounded app…
Exact penalty method for D-stationary point of nonlinear optimization
Xin-Wei Liu, Yu-Hong Dai
We consider the nonlinear optimization problem with least -norm measure of constraint violations and introduce the concepts of the D-stationary point, the DL-stationary poi…
A primal-dual majorization-minimization method for large-scale linear programs
Xin-Wei Liu, Yu-Hong Dai, Ya-Kui Huang
We present a primal-dual majorization-minimization method for solving large-scale linear programs. A smooth barrier augmented Lagrangian (SBAL) function with strict convexity for t…
Geometric Convergence for Distributed Optimization with Barzilai-Borwein Step Sizes
Juan Gao, Xinwei Liu, Yu-Hong Dai +2
We consider a distributed multi-agent optimization problem over a time-invariant undirected graph, where each agent possesses a local objective function and all agents collaborativ…
A unified recovery bound estimation for noise-aware Lq optimization model in compressed sensing
Zhi-Long Dong, Xiaoqi Yang, Yu-Hong Dai
In this letter, we present a unified result for the stable recovery bound of Lq(0 < q < 1) optimization model in compressed sensing, which is a constrained Lq minimization problem…
A Smoothing SQP Framework for a Class of Composite Minimization over Polyhedron
Ya-Feng Liu, Shiqian Ma, Yu-Hong Dai +1
The composite minimization problem over a general polyhedron has received various applications in machine learning, wireless communications, image restoration, signal…