Abstract
Generative Adversarial Nets (GAN) is one of the most popular research topics in recent years. In this chapter, we introduce adversarial transfer learning methods, which belongs to the implicit feature transformation methods. Specifically, we will introduce GAN-based transfer learning with applications to distribution adaptation and maximum classifier discrepancy. Data generation is another important research topic in adversarial transfer learning. Finally, we present some practice.
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Wang, J., Chen, Y. (2023). Adversarial Transfer Learning. In: Introduction to Transfer Learning. Machine Learning: Foundations, Methodologies, and Applications. Springer, Singapore. https://doi.org/10.1007/978-981-19-7584-4_10
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DOI: https://doi.org/10.1007/978-981-19-7584-4_10
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