Distributed Linearized Alternating Direction Method of Multipliers for Composite Convex Consensus Optimization

• Published in: IEEE transactions on automatic control Vol. 63; no. 1; pp. 5 - 20
• Main Authors: Aybat, N. S., Wang, Z., Lin, T., Ma, S.
• Format: Journal Article
• Language: English
• Published: IEEE 01.01.2018
• Subjects: Alternating direction method of multipliers (ADMM); composite convex function; Convergence; Convex functions; Distributed algorithms; Distributed databases; distributed optimization; first-order method; linearized ADMM; Memory management; Network topology; Optimization

Given an undirected graph G = (N, E) of agents N = {1,..., N} connected with edges in E, we study how to compute an optimal decision on which there is consensus among agents and that minimizes the sum of agent-specific private convex composite functions {Φ i } i∈N , where Φ i ≐ ξ i + f i belongs to...