1. Introduction

2. Preliminary knowledge

3. Seminal divergence-based learning bounds

4. Hardness results for domain adaptation

5. Learning bounds with integral probability metrics

6. PAC-Bayesian theory for domain adaptation

7. Domain adaptation theory based on algorithmic properties

8. Conclusions and discussion