associate professor of computer science and engineering. “But most of the work makes use of a handful of data sets, which are very small and do not represent many aspects of federated learning.” ...

IT decision-makers are using artificial intelligence (AI) and machine learning (ML) in big data projects and state-of-the-art data science models ... new approach called Federated Machine Learning.

In federated learning systems, I would say there are two types of user personas: the data owner (who owns the data) and the data scientist (who performs the data science operations). For example ...

Federated Learning is a decentralised and privacy-friendly form of machine learning. This means that there is no need for a central database to hold all of the sensitive data, so these data cannot be ...

federated learning sends algorithms to the data. The updated algorithms are then shared with the participants. This is in direct contrast to traditional data science methods, which require ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More In a blog post today, Google laid out the concept of federated ...

AI is fundamentally dependent on data, but the vast majority of health ... the company in 2019 with the goal of building a federated learning framework that competed with open source approaches ...