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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 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…
Semidefinite Relaxation for Two Mixed Binary Quadratically Constrained Quadratic Programs: Algorithms and Approximation Bounds
Zi Xu, Mingyi Hong
This paper develops new semidefinite programming (SDP) relaxation techniques for two classes of mixed binary quadratically constrained quadratic programs (MBQCQP) and analyzes thei…
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…