Deep transfer learning has emerged as a powerful paradigm in image classification, enabling models to leverage knowledge acquired from large, labelled datasets to perform effectively on new tasks with ...

Federated Learning (FL) has gained significant attention as a novel distributed machine learning paradigm that enables collaborative model training while preserving data privacy. However, traditional ...

Transfer learning refers to the process of adapting a model trained on a source task to a target task. While kernel methods are conceptually and computationally simple models that are competitive on a ...

Mingai Li, received her B.Sc. degree and M.Sc. degree from Daqing Petroleum Institute, Heilongjiang, China, in 1987 and 1990 respectively, and Ph.D. degree from Beijing University of Technology, ...

When discussing learning transfer—the ability to apply previous knowledge, skills, and strategies to new contexts or situations—we should also be mindful of our learners’ cognitive load. Cognitive ...