Experimental machine learning uniquely advances ahead of theory.
Practitioners identify and exploit phenomena that are yet theoretically void. We discuss recent research at the intersection of statistics and machine learning. The aim is to stay current on both theoretical and experimental advances.
A nonexhaustive list of topics includes transfer learning, RKHS theory, algebraic statistics, high dimensional statistics, and manifold estimation.
Participants from all fields are welcome to attend and/or get involved.
| Rhythmus | Tag | Uhrzeit | Format / Ort | Zeitraum | |
|---|---|---|---|---|---|
| wöchentlich | Do | 14-16 | V4-116 | 13.04.-24.07.2026 |
Die verbindlichen Modulbeschreibungen enthalten weitere Informationen, auch zu den "Leistungen" und ihren Anforderungen. Sind mehrere "Leistungsformen" möglich, entscheiden die jeweiligen Lehrenden darüber.