Table of Contents

CHAPTER 1 INTRODUCTION
1.1 Feature Selection
1.2 Transfer Learning
1.3 Outline
CHAPTER 2 BACKGROUND
2.1 Notations
2.2 Single-Layer Autoencoder
2.3 Long-Short-Term Memory Network
2.4 Sparse Learning-Based Unsupervised Feature Selection
2.5 Self-Taught Learning
2.6 Few-Shot Learning
2.7 Hyperspectral Signal Analysis
2.8 Human Activity Recognition
CHAPTER 3 FEATURE SELECTION
3.1 Vertical Federated Learning-Based Supervised Feature Selection
3.2 Supervised Hyperspectral Band Selection /05i
3.3 Unsupervised Feature Selection with Data Structure Preservation
CHAPTER 4 TRANSFER LEARNING
4.1 Graph and Autoencoder-Based Self-Taught Learning
4.2 Few-Shot Learning-Based Cross-Domain Human Activity Recognition
BIBLIOGRAPHY

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