Framework Construction of an Adversarial Federated Transfer Learning Classifier. (arXiv:2211.04734v1 [cs.LG])

As the Internet grows in popularity, more and more classification jobs, such
as IoT, finance industry and healthcare field, rely on mobile edge computing to
advance machine learning. In the medical industry, however, good diagnostic
accuracy necessitates the combination of large amounts of labeled data to train
the model, which is difficult and expensive to collect and risks jeopardizing
patients' privacy. In this paper, we offer a novel medical diagnostic framework
that employs a federated learning platform to ensure patient …

adversarial construction framework