Julia Herbinger

About

I started as a PhD student at the working group for Statistical Learning and Data Science at the Ludwig-Maximilians-University Munich in August 2020. My main research focus is on Interpretable Machine Learning.

I obtained a Bachelor's Degree (B.A.) in Business Administration from DHBW Heidenheim and a Master's Degree (M.Sc.) in Statistics from the Ludwig-Maximilians-University Munich.

Contact

Institut für Statistik

Ludwig-Maximilians-Universität München

Ludwigstraße 33

D-80539 München

Julia.Herbinger [at] stat.uni-muenchen.de

References

  1. Molnar C, König G, Herbinger J et al. (2020) Pitfalls to Avoid when Interpreting Machine Learning Models. arXiv preprint arXiv:2007.04131.
    LINK: arXiv:2007.04131
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  2. Fink H, Geissel S, Herbinger J, Seifried FT (2019) Portfolio Optimization with Optimal Expected Utility Risk Measures. Available at SSRN.
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