Researchers have built a federated, explainable deep learning framework that detects attacks on Internet of Medical Things ...

A Scientific Reports study presents a causal-enhanced federated transfer learning framework that improved cross-domain ...

New York, Jan. 11, 2024 (GLOBE NEWSWIRE) -- According to research by Market.us, The Worldwide Federated Learning Market size was projected to be USD 133.1 billion in 2023. By the end of 2024, the ...

To improve features like smartphone text input prediction, it is necessary to learn from a large amount of usage data.

One of the key challenges of machine learning is the need for large amounts of data. Gathering training datasets for machine learning models poses privacy, security, and processing risks that ...

The healthcare landscape stands poised for a groundbreaking transformation, driven by a powerful, privacy-preserving machine learning technique: federated learning. In the past, leveraging vast ...

An approach called federated learning trains machine learning models on devices like smartphones and laptops, rather than requiring the transfer of private data to central servers. The biggest ...

Training machine learning and deep learning models requires massive compute resources, but a new approach called federated learning is emerging as a way to train models for AI over distributed clients ...

As machine learning becomes more pervasive in the data center and the cloud there will be a need to share and aggregate information and knowledge but without exposing or moving the underlying data.