Consensus learning: A novel decentralised ensemble learning paradigm

arXiv:2402.16157v1 Announce Type: new
Abstract: The widespread adoption of large-scale machine learning models in recent years highlights the need for distributed computing for efficiency and scalability. This work introduces a novel distributed machine learning paradigm -- \emph{consensus learning} -- which combines classical ensemble methods with consensus protocols deployed in peer-to-peer systems. These algorithms consist of two phases: first, participants develop their models and submit predictions for any new data inputs; second, the individual predictions are used as inputs for a …

abstract adoption arxiv computing consensus cs.dc cs.lg decentralised distributed distributed computing efficiency ensemble highlights machine machine learning machine learning models novel paradigm peer peer-to-peer scalability scale systems type work