Federated learning (FL) has nourished a promising method for data silos, which enables
multiple participants to construct a joint model collaboratively without centralizing data. The …

Edge intelligent computing is widely used in the fields, such as the Internet of Medical
Things (IoMT), which has advantages, including high data processing efficiency, strong real …

Over the past years, the increasingly severe data island problem has spawned an emerging
distributed deep learning framework—federated learning, in which the global model can be …

Federated learning (FL) is a collaborative, decentralized privacy‐preserving method to
attach the challenges of storing data and data privacy. Artificial intelligence, machine …

Privacy-preserving federated learning, as one of the privacy-preserving computation
techniques, is a promising distributed and privacy-preserving machine learning (ML) …

Privacy-preserving federated learning is distributed machine learning where multiple
collaborators train a model through protected gradients. To achieve robustness to users …

In the business of Life Insurance, evaluating a customer's application to assign a risk level is
a task of utmost importance, as it helps in formulating policies and deciding the premium that …

With the advance of machine learning technology and especially the explosive growth of big
data, federated learning, which allows multiple participants to jointly train a high-quality …

With the penetration of renewable generation, the reliability of modern power systems is
increasingly challenged. This is especially true for power systems with comparatively low …