Unsupervised Federated Learning with Device-to-Device Enabled Contrastive Embedding Exchange

Cooperative Federated unsupervised Contrastive Learning (CF-CL) facilitates faster and more efficient global model training in federated learning settings with unlabeled data by enabling smart device-to-device exchange of data or embeddings to improve local model alignment.