Sparse Federated Learning with Hierarchical Personalization Models. (arXiv:2203.13517v1 [cs.LG])

Federated learning (FL) is widely used in the Internet of Things (IoT),
wireless networks, mobile devices, autonomous vehicles, and human activity due
to its excellent potential in cybersecurity and privacy security. Though FL
method can achieve privacy-safe and reliable collaborative training without
collecting users' privacy data, it suffers from many challenges during both
training and deployment. The main challenges in FL are the difficulty of
non-i.i.d co-training data caused by the statistical diversity of the data from
various participants, and …

arxiv federated learning hierarchical learning personalization