Effects of network topology on the performance of consensus and distributed learning of SVMs using ADMM
The cartoon martian with big head Alternating Direction Method of Multipliers (ADMM) is a popular and promising distributed framework for solving large-scale machine learning problems.We consider decentralized consensus-based ADMM in which nodes may only communicate with one-hop neighbors.This may cause slow convergence.We investigate the impact of