Federated learning lets a network of participants collaboratively train algorithms on data while keeping each stakeholder's data in its home location.

Federated learning and machine learning are related, but distinct, concepts. Machine learning refers to the development of algorithms and statistical models that enable computers to improve their ...

Federated learning is essentially machine learning for inaccessible data—the data could be private, or the data owner may not want to lose ownership.

Currently, there is a slight additional computational cost for developing federated learning models as well as a limitation to neural networks as the main supported algorithm by the most common ...

Federated learning can elevate AI. By securing model training, it unlocks a myriad of use cases that can change the world as we know it.

IBM’s Federated Learning Framework IBM FL is built with a Python library designed to support the machine learning process in a distributed environment.

Essentially, your phone’s CPU is being recruited to help train Google’s AI. Google is currently testing Federated Learning using its keyboard app, Gboard, on Android devices.

Gynecological cancers, including breast, ovarian, and cervical malignancies, account for a significant global health burden among women. The review outlines how a spectrum of machine learning (ML) ...