65 citations · 159 across the 23 of their papers we have counts for
6 papers · 1 filter
Naive Automated Machine Learning
Felix Mohr, Marcel Wever
An essential task of Automated Machine Learning (AutoML) is the problem of automatically finding the pipeline with the best generalization performance on a given dataset. This prob…
Towards Green Automated Machine Learning: Status Quo and Future Directions
Tanja Tornede, Alexander Tornede, Jonas Hanselle +3
Automated machine learning (AutoML) strives for the automatic configuration of machine learning algorithms and their composition into an overall (software) solution - a machine lea…
Automated Machine Learning, Bounded Rationality, and Rational Metareasoning
Eyke Hüllermeier, Felix Mohr, Alexander Tornede +1
The notion of bounded rationality originated from the insight that perfectly rational behavior cannot be realized by agents with limited cognitive or computational resources. Resea…
Algorithm Selection on a Meta Level
Alexander Tornede, Lukas Gehring, Tanja Tornede +2
The problem of selecting an algorithm that appears most suitable for a specific instance of an algorithmic problem class, such as the Boolean satisfiability problem, is called inst…
Annotation Uncertainty in the Context of Grammatical Change
Marie-Luis Merten, Marcel Wever, Michaela Geierhos +2
This paper elaborates on the notion of uncertainty in the context of annotation in large text corpora, specifically focusing on (but not limited to) historical languages. Such unce…
Naive Automated Machine Learning -- A Late Baseline for AutoML
Felix Mohr, Marcel Wever
Automated Machine Learning (AutoML) is the problem of automatically finding the pipeline with the best generalization performance on some given dataset. AutoML has received enormou…