Method(olog)ische Grundlagen der Statistik und ihre Anwendungen
print


Navigationspfad


Inhaltsbereich

Research

Research Interests

Robust Surrogates in Bayesian Optimization
Hyperparamter-Tuning
Superset Learning/Inference
Weak Supervision
(Causal Inference)

Publications

  • Julian Rodemann, Thomas Augustin (2022): Accounting for Gaussian Process Imprecision in Bayesian Optimization. In: Proceedings of the Ninth International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making (IUKM). Ishikawa, Japan. Lecture Notes on Artificial Intelligence, Springer.

Talks

  • Julian Rodemann, Dominik Kreiss, Thomas Augustin, Eyke Hüllermeier (2022): Work In Progress: Levelwise Data Disambiguation by Cautious Superset Classification. Annual Summer Retreat, Department of Statistics.

Servicebereich