Introduction to transfer learning [electronic resource] : algorithms and practice / Jindong Wang, Yiqiang Chen.

Part I. Foundations of Transfer Learning
Chapter 1. Introduction
Chapter 2. From Machine Learning to Transfer Learning
Chapter 3. Overview of Transfer Learning Algorithms
Chapter 4. Instance Weighting Methods
Chapter 5. Statistical Feature Transformation Methods
Chapter 6. Geometrical Feature Transformation Methods
Chapter 7. Theory, Evaluation, and Model Selection
Part II. Modern Transfer Leaning
Chapter 8. Pre-training and Fine-tuning
Chapter 9. Deep Transfer Learning
Chapter 10. Adversarial Transfer Learning
Chapter 11. Generalization in Transfer Learning
Chapter 12. Safe & Robust Transfer Learning
Chapter 13. Transfer Learning in Complex Environments
Chapter 14. Low-resource Learning
Part III. Applications
Chapter 15. Transfer Learning for Computer Vision
Chapter 16. Transfer Learning for Natural language Processing
Chapter 17. Transfer Learning for Speech Recognition
Chapter 18. Transfer Learning for Activity Recognition
Chapter 19. Federated Learning for Personalized Healthcare
Chapter 20. Concluding Remarks.