Centaur: Federated Learning for Constrained Edge Devices. (arXiv:2211.04175v2 [cs.LG] UPDATED)

Federated learning (FL) on deep neural networks facilitates new applications
at the edge, especially for wearable and Internet-of-Thing devices. Such
devices capture a large and diverse amount of data, but they have memory,
compute, power, and connectivity constraints which hinder their participation
in FL. We propose Centaur, a multitier FL framework, enabling ultra-constrained
devices to efficiently participate in FL on large neural nets. Centaur combines
two major ideas: (i) a data selection scheme to choose a portion of samples
that …

arxiv centaur devices edge edge devices federated learning