Below is a list of possible thesis projects within the FMLS group. These should be considered starting points only. An essential part of doing a thesis is the formulation and refinement of the problem itself.
- Bachelor/Master: Mixability Regions - Extending the Scope of an Algorithm Solving the Learning Under Expert Advice Problem (Armando/Rabanus)
- Master: Learning with Coherent Risk Measures in Practice (Chris)
- Master: Surveying the Structures of Supervised Learning Problems (input and output space, epistemic and ontic interpretations) (Chris/Rabanus)
- Master: What do we detect when we do anomaly detection? (Chris)
- Master: Intersectional Fairness through the Lens of Collectives and Hypergraphs (Rabanus)
- Master: Surveying and expanding existing understanding of robust learning models from a statistical point of view (e.g., unbiasedness/consistency of risk estimators) (Laura and Nan)
- Master: Learning under general corruption -- definition and theoretical analysis (Laura)
- Bachelor/Master: Consequences of Markovian corruption on learning -- empirical study, but it can also delve into the theoretical part depending on the student’s interest (Laura and Nan)
Don't hesitate to ask for an informal meet-up with somebody of our group to get a bit more information on the topics (see the names in brackets).