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I am currently focusing on learning theory in a broader sense. I am particularly interested in how different machine learning problems are interconnected and characterized. Lately, reasoning about supervised learning and data corruption led to a project about Markovian corruption and its associated...

Hello, I'm Rabanus. Since October 2021 I am pursuing my PhD under supervision of Bob Williamson in the group "Foundations of Machine Learning Systems". I am working on the implication of probability theoretical assumptions in machine learning and the quality of forecasts. As part of this endeavour I...

We study foundational questions for machine learning systems. Our style of research is to examine closely a number of things that are taken for granted. We aim for a deep understanding of a small number of things. Our motivation for research is primarily the "joy of finding things out." We are not...

machine learning processes information, but what do we mean by 'information"? One view comes from Information Theory, which was originally developed motivated by problems of communication. But learning problems are different, aren't they? This project explores the notion of information that makes...

I am a mathematician with research experience in differential geometry, geometric analysis, and mathematical relativity. The main goal of my current research is to better understand several key objects in machine learning from a rigorous mathematical point of view. I am convinced that analyzing...

Machine learning is about forecasting. Forecasts, however, obtain their usefulness only through their evaluation. Machine learning has traditionally focused on types of losses and their corresponding regret. Currently, the machine learning community regained interest in calibration. In this project...