Collaborative Mean Estimation over Intermittently Connected Networks with Peer-To-Peer Privacy. (arXiv:2303.00035v1 [cs.IT])

This work considers the problem of Distributed Mean Estimation (DME) over
networks with intermittent connectivity, where the goal is to learn a global
statistic over the data samples localized across distributed nodes with the
help of a central server. To mitigate the impact of intermittent links, nodes
can collaborate with their neighbors to compute local consensus which they
forward to the central server. In such a setup, the communications between any
pair of nodes must satisfy local differential privacy constraints. …

compute connectivity data distributed forward global impact learn links local networks nodes peer-to-peer privacy problem server statistic work