Developments in Transfer Learning

Dear Colleagues,

There has been a growing interest in transfer learning approaches with the rapid development of deep learning over the past decade. Even though such strategies for leveraging the transferability of knowledge from one domain to another related domain or a subdomain have been around for quite some time in the machine learning literature, large pre-trained deep learning models on large amounts of data from broader domains such as computer vision and NLP have been finetuned with fewer data and limited computational resources for applications in many specific real-world problems, such as medical imaging, etc. However, transfer learning methods have not been extensively studied in tabular data, limiting their applications in many real-world situations, such as financial data, medical history data, etc.

We are organizing this Special Issue to help to promote development in both theoretical aspects and applications of transfer learning in diverse domains. We invite and welcome review, expository, and original research articles dealing with recent theoretical advances in transfer learning techniques and their multidisciplinary applications.

Dr. Sourav Sen
Guest Editor

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