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Prof. Frank Hutter

Frank Hutter


Machine Learning Lab

Georges-Köhler-Allee 74
79110 Freiburg im Breisgau
Gebäude 74, Raum 00-017


Automatic machine learning (AutoML)

We aim to democratize machine learning by means of open-source software that allows even non-experts to use effective machine learning solutions for their data. We are multiple-time world champions in the AutoML challenge series.

Deep learning

We particularly focus on efficient training algorithms, efficient neural architecture search and hyperparameter optimization, and Bayesian deep learning.

Automated algorithm design

We develop automated methods for algorithm configuration, algorithm selection, and algorithm analysis.Typical application domains are NP-hard problems, such as SAT solving, AI planning, or TSP solving.

Bayesian Optimization

This entails sequential experimental design under uncertainty for sample-efficient global zeroth order optimization.