1

Effects of network topology on the performance of consensus and distributed learning of SVMs using ADMM

ugfgmvxfo07n0h
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.animationbengal.com/
Report this page

Comments

    HTML is allowed

Who Upvoted this Story