Can Fairness be Automated?

Posted on April 3, 2023 by Hilde Weerts, Florian Pfisterer, Matthias Feurer, Katharina Eggensperger, Eddie Bergman, Noor Awad, Mykola Pechenizkiy, Joaquin Vanschoren, Bernd Bischl, Frank Hutter

At the risk of sounding cliché, “with great power comes great responsibility.” While we don’t want to suggest that machine learning (ML) practitioners are superheroes, what was true for Spiderman is also true for those building predictive models – and even more so for those building AutoML tools. Only last year, the Netherlands Institute for […]

Auto-Sklearn – What happened in 2020

Posted on February 26, 2021 by Katharina Eggensperger, Matthias Feurer

2020 is over. Time to look back at the amazing major features we introduced to Auto-Sklearn.

Auto-Sklearn 2.0: The Next Generation

Posted on July 13, 2020 by Katharina Eggensperger, Matthias Feurer

Since our initial release of auto-sklearn 0.0.1 in May 2016 and the publication of the NeurIPS paper “Efficient and Robust Automated Machine Learning” in 2015, we have spent a lot of time on maintaining, refactoring and improving code, but also on new research. Now, we’re finally ready to share the next version of our flagship […]

We did it again: world champions in AutoML

Posted on July 13, 2018 by André Biedenkapp, Katharina Eggensperger, Matthias Feurer, Frank Hutter

By Our ML Freiburg lab is the world champion in automatic machine learning (AutoML) again! After winning the first international AutoML challenge (2015-2016), we also just won the second international AutoML challenge (2017-2018). Our system PoSH-Auto-sklearn outperformed all other 41 participating AutoML systems.