Machine learning typically relies on the assumption that training and testing distributions are
identical and that data is centrally stored for training and testing. However, in real-world …

Federated Learning (FL) is a privacy-preserving distributed learning approach that is rapidly
developing in an era where privacy protection is increasingly valued. It is this rapid …

Reliability and operational efficiency of equipment are crucial in the manufacturing of
consumer electronics. Existing fault detection methods often face limitations such as dataset …

Hematoxylin and Eosin (H&E) staining of whole slide images (WSIs) is considered the gold
standard for pathologists and medical practitioners for tumor diagnosis, surgical planning …

Gradient alignment has shown empirical success in federated domain generalization, yet a
theoretical foundation for this approach remains unexplored. To address this gap, we …