Stefan Coors

About

I started as a PhD student at the working group for Computational Statistics at the Ludwig-Maximilians-University Munich on June 2018 after being a student assistant. My main research focus is on automatic and classical Machine Learning .

I obtained a Bachelor's Degree (B.Sc.) and Master's Degree (M.Sc.) in Business Mathematics from the University of Bielefeld and a Master's Degree (M.Sc.) in Statistics from the LMU Munich.

Contact

Institut für Statistik

Ludwig-Maximilians-Universität München

Ludwigstraße 33

D-80539 München

Room 344, 3rd floor

Phone: +49 89 2180 3196

Stefan.Coors [at] stat.uni-muenchen.de

Research Interests

You Can Find me on

References

  1. Bischl B, Binder M, Lang M, Pielok T, Richter J, Coors S, Thomas J, Ullmann T, Becker M, Boulesteix A-L, Deng D, Lindauer M (2023) Hyperparameter Optimization: Foundations, Algorithms, Best Practices, and Open Challenges. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, e1484.
  2. Karl F, Pielok T, Moosbauer J, Pfisterer F, Coors S, Binder M, Schneider L, Thomas J, Richter J, Lang M, Garrido-Merchán EC, Branke J, Bischl B (2023) Multi-Objective Hyperparameter Optimization in Machine Learning – An Overview. ACM Transactions on Evolutionary Learning and Optimization 3, 1–50.
  3. Böhme R, Coors S, Oster P, Munser-Kiefer M, Hilbert S (2022) Machine learning for spelling acquisition - How accurate is the prediction of specific spelling errors in German primary school students?
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  4. Gijsbers P, Bueno MLP, Coors S, LeDell E, Poirier S, Thomas J, Bischl B, Vanschoren J (2022) AMLB: an AutoML Benchmark. arXiv preprint arXiv:2207.12560.
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  5. Hilbert S, Coors S, Kraus E, Bischl B, Lindl A, Frei M, Wild J, Krauss S, Goretzko D, Stachl C (2021) Machine learning for the educational sciences. Review of Education 9, e3310.
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  6. Goerigk S, Hilbert S, Jobst A, Falkai P, Bühner M, Stachl C, Bischl B, Coors S, Ehring T, Padberg F, Sarubin N (2020) Predicting instructed simulation and dissimulation when screening for depressive symptoms. European Archives of Psychiatry and Clinical Neuroscience 270, 153–168.
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  7. Pfisterer F, Coors S, Thomas J, Bischl B (2019) Multi-Objective Automatic Machine Learning with AutoxgboostMC. arXiv preprint arXiv:1908.10796.
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  8. Lang M, Binder M, Richter J, Schratz P, Pfisterer F, Coors S, Au Q, Casalicchio G, Kotthoff L, Bischl B (2019) mlr3: A modern object-oriented machine learning framework in R. Journal of Open Source Software 4, 1903.
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  9. Thomas J, Coors S, Bischl B (2018) Automatic Gradient Boosting. ICML AutoML Workshop.
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  10. Stüber AT, Coors S, Schachtner B, Weber T, Rügamer D, Bender A, Mittermeier A, Öcal O, Seidensticker M, Ricke J, others (2023) A Comprehensive Machine Learning Benchmark Study for Radiomics-Based Survival Analysis of CT Imaging Data in Patients With Hepatic Metastases of CRC. Investigative Radiology, 10–1097.
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