Technical Reports from 2019

Here follows a list of all Technical Reports from 2019. By following the respective links, you can have a look at a report´s abstract or the pdf version. Generally, the abstracts are written in English, since most of the reports are in this language.

Report Nr.294, June 2019 (PDF)
Klaus Greff, Aaron Klein; Martin Chovanec, Frank Hutter; Jürgen Schmidhuber.
The Sacred Infrastructure for Computational Research.
(Abstract)

Report Nr.293, June 2019 (PDF)
Jan N. van Rijn, Frank Hutter.
An Empirical Study of Hyperparameter Importance Across Datasets.
(Abstract)

Report Nr.292, June 2019 (PDF)
Aaron Klein, Stefan Falkner, Numair Mansur, Frank Hutter.
RoBO : A Flexible and Robust Bayesian Optimization Framework in Python.
(Abstract)

Report Nr.291, June 2019 (PDF)
Aaron Klein, Stefan Falkner, Jost Tobias Springenberg, Frank Hutter.
Learning Curve Prediction with Bayesian Neural Networks.
(Abstract)

Report Nr.290, June 2019 (PDF)
Stefan Falkner, Aaron Klein, Frank Hutter.
Combining Hyperband and Bayesian Optimization.
(Abstract)

Report Nr.289, June 2019 (PDF)
Aaron Klein, Stefan Falkner, Simon Bartels, Philipp Hennig, Frank Hutter.
Fast Bayesian hyperparameter optimization on large datasets.
(Abstract)

Report Nr.288, June 2019 (PDF)
Alexander Heinz, Martin Wehrle, Sergiy Bogomolov, Daniele Magazzeni, Marius Greitschus, Andreas Podelski.
Temporal Planning as Refinement-Based Model Checking: Proofs and Additional Descriptions.
(Abstract)