A label-efficient paradigm in computer vision is based on self-supervised contrastive pre-training unlabeled data followed by fine-tuning with a small number of labels. Making practical use federated computing environment the clinical domain and learning medical images poses specific challenges. In this work, we propose FedMoCo, robust (FCL) framework, which makes efficient decentralized data. ...