| Lerninhalte |
Graphs (or networks) are (almost) everywhere. They can be found in real life in different forms, e.g. naturally (road networks, social networks,…) or as reasonable models (movie recommendation, anomaly detection,…). In this course, we will introduce some of the most common classes of networks and typical problems arising in the study of these networks. Classical and, if possible, ML-based approaches to solve these problems will be discussed. In the last few lectures we will have a brief look at Graph-based approaches to (typical) unsupervised and semi-supervised learning situations. |
