Machine learning for wireless networks

The course presents the application of machine learning techniques to relevant problems in the area of wireless networking and mobile computing, including but not limited to:
- Classification and discussion of learning problems in wireless networks' settings, e.g., physical layer control, classification problems, network slicing;
- In depth analysis of some key algorithms in this context, e.g., reinforcement learning, federated learning, Generative Adversarial Networks;
- Projects: identification of research problems, simulation/dataset tools, and resolution methodologies
Students will be proposed to work (together with the instructor) on a paper that collects results from the project and brings together the course’s topics and the students’ main research line.