Beihang University researchers unveil a new federated learning poisoning-attack mitigation strategy to cap accuracy losses under 1% on MNIST and under 4% on CIFAR-10, bolstering AI security and ...

Federated Learning (FL) is an alternative approach that facilitates training machine learning models on distributed users’ data while preserving privacy. However, clients have different local model ...

Federated Learning (FL) has been widely recognized as a promising promoter for future intelligent wireless networks, by collaboratively training a global machine learning (ML) model in a ...

Learn about data quality, model evaluation, model explainability, and model reliability aspects to consider when working with AI and machine learning models.