464 citations · 989 across the 10 of their papers we have counts for
10 papers
Perturbation techniques for convergence analysis of proximal gradient method and other first-order algorithms via variational analysis
Xiangfeng Wang, Jane Ye, Xiaoming Yuan +2
We develop new perturbation techniques for conducting convergence analysis of various first-order algorithms for a class of nonsmooth optimization problems. We consider the iterati…
Asynchronous Distributed ADMM for Large-Scale Optimization- Part II: Linear Convergence Analysis and Numerical Performance
Tsung-Hui Chang, Wei-Cheng Liao, Mingyi Hong +1
The alternating direction method of multipliers (ADMM) has been recognized as a versatile approach for solving modern large-scale machine learning and signal processing problems ef…
Asynchronous Distributed ADMM for Large-Scale Optimization- Part I: Algorithm and Convergence Analysis
Tsung-Hui Chang, Mingyi Hong, Wei-Cheng Liao +1
Aiming at solving large-scale learning problems, this paper studies distributed optimization methods based on the alternating direction method of multipliers (ADMM). By formulating…
Joint Power Splitting and Secure Beamforming Design in the Multiple Non-regenerative Wireless-powered Relay Networks
Mingxiong Zhao, Xiangfeng Wang, Suili Feng
The physical-layer security issue in the multiple non-regenerative wireless-powered relay (WPR) networks is investigated in this letter, where the idle relay is treated as a potent…
A Scalable Frank-Wolfe based Augmented Lagrangian Method for Linearly Constrained Composite Convex Programming
Ya-Feng Liu, Xiangfeng Wang, Xin Liu +1
In this paper, we consider large-scale linearly constrained composite convex optimization problem, whose objective is a sum of a smooth function and a possibly nonsmooth function.…
Multi-Agent Distributed Optimization via Inexact Consensus ADMM
Tsung-Hui Chang, Mingyi Hong, Xiangfeng Wang
Multi-agent distributed consensus optimization problems arise in many signal processing applications. Recently, the alternating direction method of multipliers (ADMM) has been used…