Federated Bayesian Network Ensembles

arXiv:2402.12142v1 Announce Type: cross
Abstract: Federated learning allows us to run machine learning algorithms on decentralized data when data sharing is not permitted due to privacy concerns. Ensemble-based learning works by training multiple (weak) classifiers whose output is aggregated. Federated ensembles are ensembles applied to a federated setting, where each classifier in the ensemble is trained on one data location.
In this article, we explore the use of federated ensembles of Bayesian networks (FBNE) in a range of experiments and …

algorithms arxiv cs.cr cs.lg data data sharing decentralized decentralized data federated federated learning machine machine learning machine learning algorithms network privacy privacy concerns run sharing training