The 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. https://www.roneverhart.com/Western-Digital-Ultrastar-DC-HC550-WUH721816ALE6L0-0F38460-16TB-7-2K-RPM-SATA-6Gb-s-512e-ISE-3-5in-Hard-Drive/