Abstract
In this chapter, we introduce statistical feature transformation methods for transfer learning. This kind of approaches is extremely popular in existing literature with good results. Especially, they are often implemented in deep neural networks in recent research, demonstrating remarkable performance. Thus, it is important that we understand its very basic knowledge. Note that we will focus on its basics and will not introduce its deep learning extensions, which will be introduced in later sections.
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Wang, J., Chen, Y. (2023). Statistical Feature Transformation Methods. In: Introduction to Transfer Learning. Machine Learning: Foundations, Methodologies, and Applications. Springer, Singapore. https://doi.org/10.1007/978-981-19-7584-4_5
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DOI: https://doi.org/10.1007/978-981-19-7584-4_5
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