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 […]

DEHB

Posted on August 10, 2022 by Noor Awad

DEHB: EVOLUTIONARY HYPERBAND FOR SCALABLE, ROBUST AND EFFICIENT HYPERPARAMETER OPTIMIZATION By Noor Awad, Modern machine learning algorithms crucially rely on several design decisions to achieve strong performance, making the problem of Hyperparameter Optimization (HPO) more important than ever. We believe that a practical, general HPO method must fulfill many desiderata, including: (1) strong anytime performance, […]

Playing Games with Progressive Episode Lengths

Posted on August 3, 2020 by Noor Awad

By A framework of ES-based limited episode’s length