Efficient Federated Learning for AIoT Applications Using Knowledge Distillation. (arXiv:2111.14347v2 [cs.LG] UPDATED)

As a promising distributed machine learning paradigm, Federated Learning (FL)
trains a central model with decentralized data without compromising user
privacy, which has made it widely used by Artificial Intelligence Internet of
Things (AIoT) applications. However, the traditional FL suffers from model
inaccuracy since it trains local models using hard labels of data and ignores
useful information of incorrect predictions with small probabilities. Although
various solutions try to tackle the bottleneck of the traditional FL, most of
them introduce significant …

aiot applications arxiv distillation federated learning knowledge learning