Toward Optimal Disease Surveillance with Graph-Based Active Learning

Mathematics, Information Science, Medicine, Environmental and Public Health,
disease surveillance   active learning   network dynamics   epidemiology   public health  

Toward Optimal Disease Surveillance with Graph-Based Active Learning Academic Background With the acceleration of globalization, the speed and scope of infectious disease transmission have significantly increased. How to effectively monitor and control the spread of infectious diseases has become a critical issue in public health. Traditional disea...

Active Dynamic Weighting for Multi-Domain Adaptation

Information Science, Artificial Intelligence,
multi-source domain adaptation   transfer learning   active learning   distribution alignment   dynamic boundary loss  

Background Introduction Multi-source Unsupervised Domain Adaptation (MUDA) aims to transfer knowledge from multiple labeled source domains to an unlabeled target domain. However, existing methods often merely seek to blend distributions between different domains or combine multiple single-source models in the decision process through weighted fusio...