Definition
A machine learning approach where a shared, global model is trained across multiple decentralized local devices or servers that hold local data samples, without exchanging the raw data itself.
In short: A machine learning approach where a shared, global model is trained across multiple decentralized local devices or servers that hold local data samples, without exchanging the raw data itself.