“Anything that uses machine learning on end-user data could be federated,” Chowdhury says. “Applications should be able to learn and improve how they provide their services without actually ...

Sid Roy is Manager of Machine Learning Engineering at Devron, a federated machine learning platform dedicated to unlocking the innovation and insight of data while preserving privacy. Learn more ...

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 ...

In recent decades, computer scientists have been developing increasingly advanced machine learning techniques that can learn ...

Federated learning lets a network of participants collaboratively train algorithms on data while keeping each stakeholder’s data within its home location. Instead of sending data to a single ...

While federated analytics is closely related to federated learning, an AI technique that trains an algorithm across multiple devices holding local samples, it only supports basic data science needs.

PARIS and NEW YORK, Dec. 2, 2019 /PRNewswire/ -- Owkin, which is developing Federated Learning and AI technologies to advance medical research, an... Menu icon A vertical stack of three evenly ...

Apheris’s new funding comes in the wake of a pivot. Originally, Röhm and his co-founder Michael Höh started the company in 2019 with the goal of building a federated learning framework that ...