type: "Concept"
title: "Federated learning"
description: "Many clients train a shared model under orchestration while data stays decentralised."
resource: "https://arxiv.org/abs/1602.05629"
tags: [fl, federated]
generated: { by: human:crpage, at: 2026-07-09T09:44:00Z }
status: stable
sources: [{ id: primary, resource: "https://arxiv.org/abs/1602.05629" }]

Federated learning

A machine-learning setting in which many clients collaborate to train a shared model while keeping training data decentralised, distinguished from ordinary distributed learning by heterogeneous data, intermittent participation and decentralised control. Federated AI reduces the need to centralise raw data, but does not remove the need for privacy engineering or governance — updates can still leak information.

Relates to: The federation layer, FedAvg, Secure aggregation.