339 citations · 2.5k across the 73 of their papers we have counts for
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Convergence Analysis of Alternating Direction Method of Multipliers for a Family of Nonconvex Problems
Mingyi Hong, Zhi-Quan Luo, Meisam Razaviyayn
The alternating direction method of multipliers (ADMM) is widely used to solve large-scale linearly constrained optimization problems, convex or nonconvex, in many engineering fiel…
Parallel Direction Method of Multipliers
Huahua Wang, Arindam Banerjee, Zhi-Quan Luo
We consider the problem of minimizing block-separable convex functions subject to linear constraints. While the Alternating Direction Method of Multipliers (ADMM) for two-block lin…
Parallel Successive Convex Approximation for Nonsmooth Nonconvex Optimization
Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo +1
Consider the problem of minimizing the sum of a smooth (possibly non-convex) and a convex (possibly nonsmooth) function involving a large number of variables. A popular approach to…
On the Linear Convergence of the Approximate Proximal Splitting Method for Non-Smooth Convex Optimization
Mojtaba Kadkhodaie, Maziar Sanjabi, Zhi-Quan Luo
Consider the problem of minimizing the sum of two convex functions, one being smooth and the other non-smooth. In this paper, we introduce a general class of approximate proximal s…
A Block Successive Upper Bound Minimization Method of Multipliers for Linearly Constrained Convex Optimization
Mingyi Hong, Tsung-Hui Chang, Xiangfeng Wang +3
Consider the problem of minimizing the sum of a smooth convex function and a separable nonsmooth convex function subject to linear coupling constraints. Problems of this form arise…