Embedding Alignment for Unsupervised Federated Learning via Smart Data Exchange. (arXiv:2208.02856v1 [cs.LG])

Federated learning (FL) has been recognized as one of the most promising
solutions for distributed machine learning (ML). In most of the current
literature, FL has been studied for supervised ML tasks, in which edge devices
collect labeled data. Nevertheless, in many applications, it is impractical to
assume existence of labeled data across devices. To this end, we develop a
novel methodology, Cooperative Federated unsupervised Contrastive Learning
(CF-CL), for FL across edge devices with unlabeled datasets. CF-CL employs
local device …

alignment arxiv data embedding federated learning learning lg smart smart data unsupervised