HealthTech Magazine

Federated Machine Learning Gives Healthcare Organizations a Competitive AI Advantage

By bringing the training of ML models to users, health systems can advance their AI ambitions while maintaining data security ...

New AI framework autonomously optimizes training data, architectures and algorithms — outperforming human baselines

EVOLVE, an agentic framework that autonomously optimizes AI training data, model architectures, and learning algorithms — ...

The Man Behind AlphaGo Thinks AI Is Taking the Wrong Path

In 2016, an AI program he developed at Google DeepMind, AlphaGo, taught itself to play the famously difficult game of Go with ...
Frontiers

Brain-inspired learning and adaptation in large models

Recent advances in large-scale AI models, including large language and vision-language-action models, have significantly expanded the capabilities of ...
IEEE

Sparse Decentralized Federated Learning

Abstract: Decentralized Federated Learning (DFL) enables collaborative model training without a central server but faces challenges in efficiency, stability, and trustworthiness due to communication ...
IEEE

Federated Function-on-function Regression with an Efficient Gradient Boosting Algorithm for Privacy-Preserving Telemedicine

Abstract: Federated Learning (FL) is an emerging computing paradigm to collaboratively train Machine Learning (ML) models across multi-source data while preserving privacy. The major challenge of ...